Full-automatic mixing production method of copper concentrate

Abstract

The application discloses a kind of copper concentrate full-automatic mixing production method, belong to mineral processing and metallurgical automation technical field.The method includes: after multiple copper concentrates are concentrated and unloaded, it is sent to raw material bin by closed belt conveyor, belt conveyor is sequentially opened and reversely stopped interlock, and is equipped with deviation, plugging, tearing, overload detection;Automatic stocker is stacked in partition and layer, to realize homogeneous storage by multilayer paving and cross distribution;Automatic material taking machine is linked with stacking, batching system, reciprocating scraper material taking realizes constant current feeding;Control system is according to grade and impurity parameter and is divided into warehouse distribution, according to smelting process index control each batching bin simultaneously to metering belt conveyor unloading, real-time measurement and adjust to preset ratio;After batching, material is sent into finished product bin after stirring and humidifying and is evenly distributed and loaded;Each equipment is centrally controlled by control system, dust removal system is linked with dust production equipment and dust is recycled and used in batching system circulation.The method is used for the automatic mixing production of copper concentrate.

Description

Technical Field

[0001] This invention belongs to the field of mineral processing and metallurgical automation technology, specifically relating to a fully automated production method for blending copper concentrate. Background Technology

[0002] Copper concentrate blending is a preliminary step in copper pyrometallurgical smelting. The uniformity and stability of the blended material composition directly affect the stability of the subsequent smelting process and the metal recovery rate. As the sources of copper concentrate become increasingly diverse and their quality fluctuates more significantly, the requirements for the precision and stability of the blending process are constantly increasing.

[0003] Chinese patent CN103614569A discloses a mixing process for multiple copper concentrates with different compositions. The process first involves separately testing each copper concentrate to determine the content of copper, sulfur, or impurity elements in each concentrate. Then, a proportion is set and batched according to the grade requirements of the mixed copper concentrate. Finally, the batched copper concentrate is transported to a material mixer for further mixing. This method employs multiple mixing operations in the mixing stage, including crushing, lifting, and spiral mixing, which improves the uniformity of material mixing to some extent. However, the batching and mixing stages still rely heavily on manual coordination, with each process relatively independent, and the entire process from batching to mixing has not yet been fully automated.

[0004] In existing copper concentrate blending production, the process model represented by CN103614569A is quite common. This means that each process step—such as raw material siloing, batching and metering, material mixing, humidification, and finished product storage—often operates independently, with material transfer and operational coordination between steps relying on manual labor. This segmented production method results in weak continuity throughout the blending process, lacking unified coordination and control between steps. Because each step operates independently, fluctuations or delays in any one step are difficult for other steps to perceive and respond to in a timely manner, hindering overall production efficiency. Furthermore, the presence of manual coordination not only increases labor intensity but also limits the possibility of further development towards continuous and automated production processes. In addition, in traditional blending production, raw material storage relies mostly on manual or semi-mechanical methods, lacking automated methods for material homogenization and constant flow material handling. The material supply flow fluctuates greatly, making it difficult to ensure the stability of the material composition and moisture content entering the batching system. The belt conveyor system lacks unified interlocking control, and it cannot achieve full-line linkage shutdown protection when equipment malfunctions. Dust control in various dust-generating links mostly relies on local dust removal or manual water spraying. There is a lack of linkage between the dust removal system and the production equipment, and the collected dust cannot be effectively recycled and utilized. Summary of the Invention

[0005] One object of the present invention is to solve at least the above-mentioned problems and to provide at least the advantages that will be described later.

[0006] To achieve these objectives and other advantages of the present invention, a fully automated production method for blending copper concentrate is provided, comprising the following steps: S1: Multiple types of copper concentrate are centrally unloaded through the unloading device. The unloaded material is then transported to the raw material silo via a closed belt conveyor. The belt conveyor adopts automated interlock control and implements forward start and reverse stop operation logic. Each belt conveyor is equipped with sensors for deviation, blockage, tearing, and overload detection. When an abnormality is detected, the entire line is linked to interlock and shut down and an alarm is triggered. S2: The automatic stacker is connected to the central control system and automatically completes walking, lifting, and flat stacking operations according to the preset process program. The control system automatically divides and stacks copper concentrate in different layers according to different batches. It adopts a multi-layer flat and cross-laying intelligent stacking mode to evenly stack different batches of raw materials and achieve homogeneous stacking. S3: The automatic material handling machine is linked and matched with the stacking system and the batching system. It uses a reciprocating scraper material handling process to cut the material pile evenly as a whole. It automatically adjusts the material handling speed and walking frequency according to the real-time load of the production line to ensure continuous, stable and uniform output flow and avoid problems such as pulse feeding, material deviation and material interruption. S4: The control system controls the distribution equipment to feed each type of copper concentrate into the corresponding batching bins based on the grade and impurity parameters of each type of copper concentrate. S5: The control system controls each batching bin to simultaneously unload material to the corresponding metering belt conveyor according to the preset smelting process parameters. Each metering belt conveyor measures the material discharge of its corresponding batching bin in real time and adjusts the unloading speed of each batching bin according to the measurement results, so that the material discharge of each type of copper concentrate reaches the preset ratio. Among them, the batching bin has automatic material level monitoring, automatic arch breaking, anti-blocking and pressure stabilization functions, which can continuously and stably discharge material and eliminate bridging, blockage and material interruption. S6: The mixed materials after proportioning are fed into the mixer via belt conveyor. The mixer is intelligently linked with the front-end batching and conveying system. It automatically adapts the mixing speed and material residence time according to the total incoming material flow to mix the mixed materials. The control system monitors the mixer's operating load and material status in real time and has automatic interlock protection functions for overload, material blockage, and idling. S7: The mixed material is fed into the humidifying mixer by a belt conveyor. The humidifying mixer is equipped with a water spraying device. The control system adjusts the amount of humidifying water from the water spraying device according to the moisture content detection value of the material and the current production capacity value. The humidifying mixer stirs the humidified material. S8: After humidification, the finished material is conveyed to the finished material silo by a belt conveyor, and the finished material distribution equipment evenly feeds the finished material into the finished material silo. S9: Finished materials in the finished material silo are transported to the transport vehicle through the unloading gate and unloading chute to complete loading; In the above steps, the operation of the belt conveyor and the start and stop of each piece of equipment are all centrally controlled by the control system; the dust removal system is integrated with all dust-generating equipment in the line, and the dust removal system starts synchronously when the dust-generating equipment starts and stops after a delay when it stops, and the collected dust is uniformly returned to the batching system for recycling; the control system monitors parameters such as equipment current, temperature, pressure, flow rate, and material level in real time, and alarms and automatically protects and shuts down in case of abnormalities; the control system records and stores the proportioning data, output data and equipment operating parameters in real time, realizing the visual traceability of production data.

[0007] Preferably, in step S4, the control system controls the silo distribution equipment to feed each type of copper concentrate into its corresponding batching silo based on the grade and impurity parameters of each type of copper concentrate. Specifically, the control system pre-stores the correspondence between the silo number of each batching silo and the ranges of copper grade, sulfur content, and arsenic content values ​​of each type of copper concentrate. The control system obtains the copper grade, sulfur content, and arsenic content detection values ​​of the copper concentrate currently being conveyed by the enclosed belt conveyor, matches these values ​​with the ranges of copper grade, sulfur content, and arsenic content values ​​in each corresponding relationship, determines the target corresponding relationship that simultaneously meets the matching conditions, and determines the silo number of the target batching silo based on the target corresponding relationship. The control system then feeds the currently conveyed copper concentrate into the target batching silo.

[0008] Preferably, in step S5, the control system controls each batching bin to simultaneously unload material into the metering belt conveyor according to preset smelting process parameters. The metering belt conveyor measures the discharge amount of each batching bin in real time and adjusts the discharge speed of each batching bin according to the measurement results, so that the discharge amount of each type of copper concentrate reaches the preset ratio. Specifically: The control system obtains the bin number of each batching bin and the target proportion percentage of the corresponding copper concentrate, and calculates the target instantaneous discharge amount of each batching bin based on the target proportion percentage and the total conveying capacity of each metering belt conveyor. Each batching bin is equipped with a metering belt conveyor. Each metering belt conveyor is equipped with a weighing sensor and a speed sensor. The weighing sensor measures the instantaneous weight of the material on the corresponding metering belt conveyor, and the speed sensor measures the belt running speed of the corresponding metering belt conveyor. The control system calculates the actual instantaneous discharge amount of the corresponding batching bin based on the instantaneous weight value of the material and the belt running speed value of each metering belt conveyor. It performs moving average processing on the time series data of the actual instantaneous discharge amount with a preset time window length to obtain the moving average discharge amount. It compares each moving average discharge amount with the corresponding target instantaneous discharge amount. Based on the comparison results, it independently adjusts the operating frequency of the discharge valve of each batching bin through the frequency converter so that each moving average discharge amount approaches the corresponding target instantaneous discharge amount. During the simultaneous unloading process of multiple compartments, when the deviation between the sliding average discharge amount and the target instantaneous discharge amount of any batching compartment exceeds the preset deviation threshold, the control system keeps the operating frequency of the unloading valves of other batching compartments unchanged and only adjusts the operating frequency of the unloading valve whose deviation exceeds the preset deviation threshold.

[0009] Preferably, in step S5, during the simultaneous unloading process of multiple compartments, the control system also performs the following operations: The control system records the time series data of the actual instantaneous discharge volume of each batching bin in real time, and performs a moving average processing on the time series data of the actual instantaneous discharge volume of each batching bin with a preset time window length to obtain the moving average discharge volume of each batching bin. The control system calculates the sum of the sliding average discharge amounts of all batching silos unloading at the same time to obtain the measured value of the total instantaneous discharge amount of the system; the control system obtains the sum of the total conveying capacity values ​​of each metering belt conveyor to obtain the nominal value of the total conveying capacity of the system; the control system compares the measured value of the total instantaneous discharge amount of the system with the nominal value of the total conveying capacity of the system to obtain the deviation value of the total discharge amount of the system. When the absolute value of the total system feed deviation is greater than the preset total system deviation allowable threshold, the control system determines that there is an overall metering deviation in the current batching system, triggers a system metering anomaly warning, and suspends the independent adjustment operation of the unloading speed of each batching bin except for the bin that has been triggered for independent adjustment in step S5, and maintains the current operating frequency of each unloading valve unchanged. When the absolute value of the total system feed deviation is less than or equal to the preset total system deviation allowable threshold, and the deviation between the sliding average feed of any batching bin and the target instantaneous feed exceeds the preset deviation threshold, the control system marks the batching bin as a suspected deviation bin and obtains the ratio of the sliding average feed of the suspected deviation bin to the target instantaneous feed as the relative deviation coefficient of the suspected deviation bin. The control system acquires the historical relative deviation coefficient records of the suspected deviation silo and calculates the standard deviation of the relative deviation coefficient of the suspected deviation silo within N consecutive time windows before the current time point. When the standard deviation is less than the preset stability threshold, the control system determines that the deviation of the suspected deviation silo is a systematic measurement deviation rather than a random fluctuation deviation, and uses the relative deviation coefficient of the suspected deviation silo to correct the target instantaneous feeding quantity of the batching silo stored in the control system online. The corrected target instantaneous feeding quantity replaces the original target instantaneous feeding quantity and is used for comparison with the moving average feeding quantity of the batching silo. After completing the above online correction, the control system restarts the independent adjustment operation of the unloading speed of each batching bin in step S5.

[0010] Preferably, in step S5, after the control system completes the online correction of the target instantaneous feed amount of any batching bin, it also performs the following operations: The control system records the correction history of the target instantaneous feeding amount of the batching silo. The correction history includes at least the timestamp of each correction, the target instantaneous feeding amount before the correction, the target instantaneous feeding amount after the correction, and the relative deviation coefficient that triggered the correction. The control system uses the current time as a reference to obtain all correction records of the batching silo within a preset historical backtracking period, and calculates the cumulative correction magnitude and number of corrections of the target instantaneous feeding quantity of the batching silo within the historical backtracking period; when the cumulative correction magnitude exceeds the preset cumulative correction magnitude threshold and the number of corrections exceeds the preset number of corrections threshold, the control system determines that the metering belt conveyor of the batching silo has a continuously deteriorating metering drift trend, triggering a metering system maintenance warning. After triggering a maintenance warning for the metering system, the control system acquires the moving average discharge rate sequence of the batching silo over M consecutive time windows prior to the warning trigger time. Linear regression analysis is performed on this moving average discharge rate sequence to obtain the slope value of the discharge rate change trend of the batching silo. When the absolute value of this slope value is greater than a preset slope threshold, the control system calculates a trend prediction compensation value for the target instantaneous discharge rate of the batching silo based on this slope value. This trend prediction compensation value is then used to perform a secondary correction on the target instantaneous discharge rate of the batching silo, obtaining the secondary corrected target instantaneous discharge rate. The control system replaces the online corrected target instantaneous discharge rate with the secondary corrected target instantaneous discharge rate for comparison with the moving average discharge rate of the batching silo.

[0011] Preferably, in step S7, the control system adjusts the humidification water volume of the spray device based on the detected moisture content of the material and the current production capacity, specifically as follows: An online moisture detector is installed at the inlet of the humidifying mixer. The online moisture detector measures the actual moisture content of the material before it enters the humidifying mixer and sends it to the control system. The control system acquires the current production capacity value, calculates the baseline humidification water volume value based on the current production capacity value and the preset humidification coefficient, corrects the baseline humidification water volume value based on the difference between the preset baseline moisture content value and the measured moisture content value, and obtains the target humidification water volume value; the control system controls the opening of the flow regulating valve of the water spraying device according to the target humidification water volume value, so that the actual humidification water volume value of the water spraying device reaches the target humidification water volume value. The preset humidification coefficient is the amount of water required per ton of material to increase the material's moisture content from the preset baseline moisture content to the preset target moisture content. The preset baseline moisture content is the nominal value of the incoming material's moisture content, which, under calibration conditions, is equal to the preset target moisture content value minus the product of the preset humidification coefficient and the amount of material per ton.

[0012] Preferably, in step S7, a second online moisture detector is installed at the outlet of the humidifying mixer. The second online moisture detector measures the measured value of the moisture content of the humidified material discharged from the humidifying mixer and sends it to the control system. The control system has a preset allowable range of humidification deviation. The control system compares the measured value of the moisture content of the humidified material measured by the second online moisture detector with the preset target moisture content value to obtain the moisture deviation value after humidification. When the moisture deviation value after humidification exceeds the allowable range of humidification deviation, the control system corrects the preset humidification coefficient based on the moisture deviation value after humidification, obtains the corrected humidification coefficient, and replaces the preset humidification coefficient with the corrected humidification coefficient for the calculation of the reference humidification water volume value.

[0013] Preferably, in step S7, the control system corrects the preset humidification coefficient based on the moisture deviation value after humidification to obtain the corrected humidification coefficient, specifically as follows: The control system has a preset upper limit for the single correction amplitude; The control system calculates the initial correction amount based on the moisture deviation value after humidification. The initial correction amount is the correction increment to the preset humidification coefficient. The control system compares the absolute value of the initial correction with the upper limit of the single correction amplitude; When the absolute value of the initial correction amount is less than or equal to the upper limit of the single correction amplitude, the control system uses the initial correction amount as the final correction amount to correct the preset humidification coefficient and obtain the corrected humidification coefficient. When the absolute value of the initial correction is greater than the upper limit of the single correction amplitude, the control system uses the upper limit of the single correction amplitude as the absolute value of the final correction and uses the sign of the initial correction as the sign of the final correction to obtain the final correction. The preset humidification coefficient is then corrected using the final correction to obtain the corrected humidification coefficient.

[0014] Preferably, in step S7, the control system calculates an initial correction amount based on the moisture deviation value after humidification. The initial correction amount is the correction increment for the preset humidification coefficient, specifically: The control system records the moisture deviation values ​​after humidification acquired in the last two times, and subtracts the moisture deviation value after humidification from the moisture deviation value after humidification at the current moment to obtain the moisture deviation change rate. The control system has a pre-stored dynamic calculation model for the initial correction amount. The initial correction amount dynamic calculation model takes the moisture deviation value and the rate of change of moisture deviation after humidification as inputs and the correction increment of the preset humidification coefficient as output. This correction increment is used as the aforementioned initial correction amount for comparison with the upper limit of the single correction amplitude. The dynamic calculation model for the initial correction amount is configured as follows: The dynamic adjustment start threshold is less than or equal to the allowable range of humidification deviation; when the absolute value of the moisture deviation value after humidification is greater than the preset dynamic adjustment start threshold, and the rate of change of moisture deviation has the same sign as the moisture deviation value after humidification, the absolute value of the output correction increment is greater than the absolute value of the reference ratio correction amount. The absolute value of the reference ratio correction amount is the value obtained by multiplying the absolute value of the moisture deviation value after humidification by the preset reference ratio coefficient. When the absolute value of the moisture deviation after humidification is greater than the preset dynamic adjustment start threshold, and the rate of change of moisture deviation has the opposite sign to the moisture deviation after humidification, the absolute value of the output correction increment is less than the absolute value of the reference proportional correction.

[0015] Preferably, in step S7, the dynamic calculation model for the initial correction amount is further configured as follows: When the absolute value of the moisture deviation after humidification is less than or equal to the preset dynamic adjustment start threshold, and the absolute value of the moisture deviation change rate is greater than the preset deviation change rate warning threshold, it is determined that the current state is in a critical pre-adjustment state where the deviation direction is about to reverse. Under critical pre-adjustment conditions, the correction increment output by the dynamic calculation model of the initial correction amount is the reverse pre-adjustment correction amount. The sign of the reverse pre-adjustment correction amount is opposite to the sign of the moisture deviation change rate. The absolute value of the reverse pre-adjustment correction amount is the absolute value of the preset benchmark ratio correction amount multiplied by the preset pre-adjustment attenuation coefficient. The preset pre-adjustment attenuation coefficient is a constant greater than 0 and less than 1.

[0016] Preferably, in step S7, under the critical pre-adjustment state, the absolute value of the reference proportional correction used for calculating the absolute value of the reverse pre-adjustment correction is obtained by the control system replacing the absolute value of the moisture deviation value after humidification at the current moment with a preset dynamic adjustment start threshold, and then multiplying it by a preset reference proportional coefficient.

[0017] Preferably, spray dust suppression devices are installed above the enclosed belt conveyor, at the inlet and outlet of the raw material silo, at the inlet and outlet of each batching silo, at the inlet of the mixer, at the inlet of the humidifying mixer, and at the inlet of the finished product silo; the start and stop of each spray dust suppression device are independently controlled by the control system. The control system has a pre-stored correspondence between the location numbers of each spray dust suppression device and the numbers of each process step; When the control system executes step S1, it activates the spray dust suppression device located above the enclosed belt conveyor. When the control system executes step S2, it activates the spray dust suppression device located at the feed inlet of the raw material silo. When the control system executes step S3, it activates the spray dust suppression device located at the discharge port of the raw material silo. When the control system executes step S4, it activates the spray dust suppression device located at the feed inlet of each batching bin. When the control system executes step S5, it activates the spray dust suppression device located at the discharge port of each batching bin. When the control system executes step S6, it activates the spray dust suppression device located at the feed inlet of the mixer; When the control system executes step S7, it activates the spray dust suppression device located at the feed inlet of the humidifying mixer; When the control system executes step S8, it activates the spray dust suppression device located at the feed inlet of the finished product silo; when the control system stops executing the corresponding step, it shuts down the spray dust suppression device corresponding to that step.

[0018] Preferably, after step S5 and before step S6, during the conveying process of the mixture into the mixer via the belt conveyor, a metal detector is installed on the belt conveyor to detect metal foreign objects in the mixture on the belt conveyor; the control system acquires the detection signal from the metal detector, and when the detection signal indicates the presence of metal foreign objects in the mixture, the control system records the detection time point of the metal foreign object detected by the metal detector; the control system calculates the arrival time point of the metal foreign object at the mixer inlet based on the detection time point, the running speed value of the belt conveyor, and the distance along the material conveying path from the metal detector to the mixer inlet; the control system controls the belt conveyor to stop running based on the arrival time point, and issues an alarm signal after the belt conveyor stops running.

[0019] Preferably, the control system calculates the arrival time of the metal foreign object at the mixer inlet based on the detection time point, the operating speed of the belt conveyor, and the distance along the material conveying path from the metal detector to the mixer inlet. Specifically: The control system acquires the operating speed value of the belt conveyor; The control system acquires the first distance value between the installation position of the metal detector on the belt conveyor and the unloading end of the belt conveyor; The control system calculates the first conveying time value based on the first distance value and the running speed value; The control system calculates the first arrival time of the metallic foreign object at the unloading end based on the detection time point and the first conveying time value. The control system acquires a second distance value between the discharge end of the belt conveyor and the feed inlet of the mixer. The second distance value is the path length along the material conveying path between the discharge end of the belt conveyor and the feed inlet of the mixer. The control system calculates the second conveying time value based on the second distance value and the running speed value; The control system calculates the arrival time of the metal foreign object at the mixer inlet based on the first arrival time and the second conveying time value.

[0020] The present invention has at least the following beneficial effects: First, this invention integrates all processes—unloading, conveying, stacking and homogenizing, intelligent material handling, material distribution, batching, mixing, humidification, finished product distribution, and loading—into a centralized management system. This enables automatic connection between processes, eliminating the disconnects caused by manual coordination in traditional segmented operations, thereby improving the continuity and automation level of copper concentrate blending production. Because each process operates collaboratively under a unified control logic, any change in the state of any process can be promptly detected and adjusted by the system. This reduces waiting time and delays caused by independent process operation, allowing the entire production process to proceed continuously and stably, thus improving production efficiency and equipment utilization.

[0021] Secondly, this invention utilizes an automated stacker to automatically partition and stack materials in layers according to a preset process, employing a multi-layered, flat, and cross-laid intelligent stacking mode to uniformly stack different batches of raw materials, achieving homogeneous stacking. An automated retrieving machine, linked with the stacking and batching systems, uses a reciprocating scraper to uniformly cut the material pile, automatically adjusting the retrieving speed and travel frequency based on the real-time load of the production line to ensure continuous, stable, and uniform output flow. This solution automates the raw material stacking and retrieving processes, eliminating raw material composition deviations at the source, ensuring stable material composition and moisture content entering the batching system, reducing subsequent batching adjustment pressure, and providing a homogeneous and stable material foundation for precise multi-bin batching.

[0022] Third, this invention uses copper grade, sulfur content, and arsenic content as a joint matching benchmark. Material distribution is only executed when all three measured values ​​of the incoming material simultaneously meet the pre-stored parameter range for a specific bin. This avoids the problems of incorrect or mixed bins caused by information errors or operational mistakes during manual identification of ore types. This solution takes the core requirements of copper smelting for these three key indicators as its starting point and introduces the logic of multi-parameter joint matching into the binning process. This ensures that various types of copper concentrate are accurately fed into the batching bins that match their composition, providing an accurate material basis for subsequent multi-bin collaborative batching, thereby reducing the risk of fluctuations in batching indicators caused by chaotic raw material zoning.

[0023] Fourth, this invention independently configures weighing and speed sensors for each batching bin, acquiring the actual instantaneous discharge volume of each bin in real time and comparing it with its respective target instantaneous discharge volume. When the deviation exceeds a threshold, only the bin with the deviation is adjusted independently, while keeping the operating frequency of other bins unchanged. This achieves dynamic and precise batching during the simultaneous unloading process of multiple bins. This scheme calculates independent batching targets based on the target batching percentage and total conveying capacity of each bin, avoiding the problems of long adjustment cycles and accumulated deviations when manually adjusting the volume one by one. At the same time, the strategy of independent correction for each bin avoids system oscillations that may be caused by mutual adjustment between multiple bins, ensuring that the actual discharge volume of each type of copper concentrate can continuously approach the preset batching requirements.

[0024] Fifth, this invention uses a mixer to forcibly mix the proportioned materials, ensuring that the various types of copper concentrate undergo sufficient homogenization before entering the subsequent humidification process. This approach introduces an independent mixing process after the batching stage, effectively reducing the compositional differences between different materials through mechanical mixing. This improves the overall microscopic uniformity of the materials, providing a more consistent material basis for the humidification process, thus facilitating stable control of the subsequent humidification process and ensuring consistent quality of the finished product.

[0025] Sixth, this invention uses the production capacity value as a feedforward input to calculate the baseline humidification amount, and then corrects the baseline humidification amount based on the deviation between the measured moisture content of the incoming material and the preset baseline moisture content. This forms a humidification control method that couples production capacity and moisture content, allowing the humidification amount to dynamically adapt to changes in production capacity and fluctuations in incoming material moisture content. This solution overcomes the problems of manual water spraying humidification, which relies on experience-based judgment, has a lagging adjustment, and cannot be quantified. By using a flow regulating valve to control the actual humidification amount in a closed loop, it brings the humidification amount close to the target value. This avoids dust problems caused by insufficient humidification and also prevents material agglomeration and adhesion to the walls caused by excessive humidification, ensuring that the moisture content of the humidified finished material remains stable within the suitable range required by the smelting process.

[0026] Seventh, this invention adds a second online moisture detector at the outlet of the humidifying mixer. The deviation between the measured moisture content at the outlet and the target moisture content is used as a feedback signal to dynamically correct the preset humidification coefficient in the feedforward channel, thus forming an adaptive control structure that combines feedforward calculation and feedback correction. This scheme enables the humidification control model to self-tune its parameters in response to systematic deviations caused by long-term factors such as equipment wear and changes in material characteristics. It overcomes the problem that cumulative deviations caused by detection lag and material flow fluctuations cannot be eliminated autonomously when relying solely on inlet moisture detection. This allows the humidification control system to maintain its adaptability to changes in operating conditions during continuous production, thereby continuously ensuring the stability of the finished product's moisture content.

[0027] Eighth, this invention sets an upper limit for the single correction amplitude in the preset correction logic. This forces the initial correction amount calculated based on the outlet moisture deviation to be limited to this upper limit if it exceeds it, thus transforming the humidification coefficient correction process from a single large jump to multiple small, gradual adjustments. This scheme avoids sudden changes in humidification amount and violent fluctuations in the finished material moisture content caused by excessively abrupt single corrections. It allows the humidification coefficient correction process to gradually approach the target value in a smoother manner, ensuring a stable transition of the control system during the adaptive correction process and reducing the risk of moisture overshoot caused by excessive correction amplitude.

[0028] Ninth, this invention introduces the rate of change of moisture deviation as a dynamic adjustment factor in the calculation of the initial correction amount. When the deviation is large and the rate of change has the same sign as the deviation, the correction amount amplitude is actively increased; when the deviation is large but the rate of change has a different sign than the deviation, the correction amount amplitude is actively decreased. This ensures that the correction intensity matches the dynamic trend of the deviation. This solution solves the problem of insufficient correction speed and excessively long recovery time during the continuous deterioration stage of deviation when calculating the correction amount solely based on the deviation value according to a fixed relationship. It also avoids reverse overshoot caused by an excessively large correction amount when the deviation has entered the self-healing stage. The correction within the amplitude-limited framework can adaptively adjust the step size according to the direction of deviation change, thereby improving the efficiency and stability of deviation convergence.

[0029] Tenth, this invention adds an independent monitoring channel for the rate of change of moisture deviation after the deviation enters the near-zero region. When the rate of change exceeds the warning threshold, it is determined that the material moisture is crossing the target value at a relatively fast speed, and a reverse pre-adjustment correction amount opposite to the drift direction is applied in advance. This suppresses the crossing trend before the deviation expands. This solution solves the problem that the dynamic adjustment function is silent when the deviation amplitude is too small, and that relying solely on micro-correction cannot timely curb the rapid drift trend. It enables the control system to intervene in advance when the deviation direction is about to reverse, thereby reducing the possibility of repeated moisture crossing of the target value causing oscillations in the humidification amount. This helps to maintain the moisture content of the finished material relatively stably near the target value.

[0030] Eleventh, this invention severs the direct correlation between the reverse pre-adjustment correction amount and the current small deviation value under critical pre-adjustment conditions. Instead, it uses a preset constant, such as a dynamically adjusted start-up threshold, as a virtual deviation in the calculation, thereby matching the amplitude of the reverse pre-adjustment correction amount with the drift intensity represented by the deviation change rate. This solution solves the problem in the near-zero region where the correction amplitude is mismatched with the drift trend due to the small deviation value, resulting in insufficient correction strength to effectively curb the rapid crossing trend. By replacing the small deviation value with a threshold in the calculation, the reverse pre-adjustment correction amount is reasonably amplified, thereby improving the near-zero region suppression gain without changing the overall structure of the control model, further ensuring the effective blocking of the water crossing trend.

[0031] Twelfth, this invention establishes independent spray dust suppression devices at multiple dust-generating points in the copper concentrate blending process. The control system activates only the spray devices corresponding to the currently executing process step number, allowing the dust suppression range to dynamically shift as production progresses. This solution addresses the high energy consumption and significant water waste associated with continuous spray dust removal across the entire area, ensuring effective dust removal at each point while avoiding ineffective spraying in areas without dust generation. Because the spray activation and deactivation are linked to the process execution status, the dust suppression devices can precisely cover the actual time and location of dust generation, thus reducing water and electricity consumption while meeting environmental dust removal requirements. Simultaneously, the dust removal system is integrated with all dust-generating equipment. The dust removal system starts synchronously when the equipment starts and shuts down after a delay, automatically performing pulse cleaning and timed ash unloading. The collected dust is uniformly recycled back to the batching system, achieving both compliant dust control and improved recycling rates of valuable metal materials.

[0032] Thirteenth, this invention involves installing a metal detector on the belt conveyor between the batching stage and the mixer inlet. When a metal foreign object is detected, the detection time is recorded. Combined with the belt speed and conveying distance, the precise time when the foreign object reaches the mixer inlet is calculated. The machine automatically stops just before the foreign object enters, keeping the section containing the metal foreign object on the belt conveyor. This solution solves the problem of metal foreign objects damaging the blades and drive mechanism of the mixer, while avoiding the inconvenience of operators having to search for the foreign object along a long belt line when stopping immediately. Because the stopping time is related to the actual location of the foreign object, the location of the foreign object is relatively clear, facilitating quick manual location and removal, thus protecting the equipment while reducing the impact on production efficiency.

[0033] Fourteenth, this invention divides the conveying path from the metal detector installation location to the mixer inlet into two independent sections: from the detector to the unloading end and from the unloading end to the inlet. A corresponding distance value is assigned to each section, and the conveying time is calculated independently and then accumulated. This allows the arrival time calculation to adapt to situations where there are different segment structures in the conveying path, such as unloading drop and transfer points. This solution solves the arrival time deviation problem caused by simply dividing the distance by the speed when treating the entire path as a single conveying segment, which fails to consider the characteristics of path segments. By timing each segment separately, the calculation of the time when foreign objects arrive at the mixer inlet is more accurate, thus providing a more reliable time basis for precise shutdown.

[0034] Fifteenth, this invention utilizes a closed belt conveyor for the enclosed transport of unloaded copper concentrate. Spray dust suppression devices are installed above the closed belt conveyor, at the inlet and outlet of the raw material silo, at the inlet and outlet of each batching silo, at the inlet of the mixer, at the inlet of the humidifying mixer, and at the inlet of the finished product silo. This ensures that dust generated during the unloading, transfer, siloing, mixing, humidification, and storage of the copper concentrate is suppressed at its source, reducing dust dispersion into the workshop environment and atmosphere, improving air quality in the workplace, and mitigating the occupational health impact of dust on operators. Simultaneously, the moisture content of the material after precise humidification is maintained within a suitable range, preventing dust pollution during transfer and loading due to excessively dry material. These measures collectively achieve effective control of dust pollution throughout the entire blending process, ensuring that the production process meets clean production and environmental emission requirements.

[0035] Sixteenth, this invention independently adjusts the operating frequency of the unloading valves in each batching silo using a frequency converter, ensuring that the operating power of the unloading valves precisely matches the actual material discharge requirements. This avoids the energy waste caused by excessive feeding and ineffective operation under traditional fixed-frequency operation. The control system accurately calculates the target humidification water volume based on the measured material moisture content and current production capacity, and controls the actual humidification water volume in a closed-loop manner through a flow regulating valve, avoiding water waste caused by excessive water addition during manual humidification. Each spray dust suppression device is activated and deactivated only during the corresponding process, avoiding the ineffective consumption of electricity and water resources caused by continuous spraying. Therefore, this invention significantly reduces energy and material consumption in copper concentrate blending production from the perspectives of electricity and water resources, demonstrating excellent energy-saving and consumption-reducing effects.

[0036] Seventeenth, this invention installs a metal detector on the belt conveyor that transports the batched materials to the mixer. When a metal foreign object is detected, the system automatically calculates the precise time it will reach the mixer's feed inlet and automatically stops the belt conveyor before the foreign object enters the mixer. This avoids equipment failures, forced shutdowns, or even secondary accidents caused by metal foreign objects damaging the blades and drive mechanism after entering the mixer, thus ensuring the safety of equipment and production operations. At the same time, all processes, including unloading, conveying, stacking and homogenizing, intelligent material handling, material distribution, batching, mixing, humidification, and loading, are centrally and automatically controlled by the control system. Operators do not need to perform frequent manual operations on the production site, reducing direct contact with operating machinery and dusty environments, and lowering the risk of personnel injury from machinery and dust hazards. Therefore, this invention comprehensively improves the safety of copper concentrate blending production from both equipment and personnel safety perspectives. In addition, the belt conveyor adopts automated interlock control and implements forward start and reverse stop operation logic. It is equipped with sensors for detection of deviation, material blockage, tearing, and overload. In case of abnormality, the entire line will be linked and shut down. The batching silo has automatic material level monitoring, automatic arch breaking, anti-blockage and pressure stabilization functions to prevent abnormalities such as bridging, silo blockage, and material interruption. The mixer has automatic interlock protection functions for overload, material blockage, and idling. The control system monitors parameters such as equipment current, temperature, pressure, flow rate, and material level in real time, realizes fault self-diagnosis and automatic alarm, effectively avoids equipment operation with defects and material accumulation accidents, and further improves the safety and reliability of the production line operation.

[0037] Other advantages, objectives and features of the present invention will become apparent in part from the following description, and in part from those skilled in the art through study and practice of the invention. Attached Figure Description

[0038] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0039] The present invention will now be described in further detail so that those skilled in the art can implement it based on the description.

[0040] In existing technologies, copper concentrate blending operations typically employ a segmented, independent operation method. For example, multiple types of copper concentrate are tested separately, manually fed according to a set ratio, and then mixed in an independent mixer. The processes rely on manual coordination, lacking unified automatic control, resulting in insufficient production continuity and automation, making it difficult to achieve fully integrated operations. Taking publicly available blending processes as an example, the batching and mixing stages still rely on on-site coordination by operators. The start / stop of belt conveyors and the operating frequency of each piece of equipment need to be manually set separately, making it impossible to achieve overall automation from unloading to finished product loading.

[0041] To address the aforementioned problems, this embodiment provides a fully automated production method for blending copper concentrate. The entire production line includes an unloading device, a closed belt conveyor, an automatic stacker, an automatic reclaimer, raw material silos, multi-compartment batching silos, distribution trolleys, metering belt conveyors, mixers, humidifying mixers, a water spraying device, finished product silos, reversible distribution belt conveyors, unloading chutes, and a dust removal system. All equipment is centrally managed by a programmable control system, with interlocking control between devices based on forward start / reverse stop logic. Operators pre-set process parameters in the control system, such as silo allocation, target blending percentage, total conveying capacity, and target moisture content for each grade of copper concentrate. At the start of production, copper concentrate of various grades is centrally unloaded into the unloading pit by grab buckets or dump trucks. The unloading hoppers utilize buffer and anti-clogging structures such as silo wall vibrators and air cannons to ensure uniform material feeding. The material is then conveyed at a constant speed to the top of the raw material silo via a closed belt conveyor. During the conveying process, the entire belt conveyor system operates on a forward start / reverse stop logic, with each belt equipped with sensors for deviation, blockage, tearing, and overload detection. In case of any abnormality, the entire line is interlocked to shut down and trigger an alarm. An automatic stacker is installed at the top of the raw material silo. After being connected to the central control system, it automatically divides and stacks materials according to a preset process program, employing a multi-layered, flat, and cross-laid intelligent stacking mode to evenly stack different batches of raw materials, achieving homogeneous stockpiling. An automatic retrieving machine is linked with the stacking and batching systems, using a reciprocating scraper process to uniformly cut the material from the pile. It automatically adjusts the retrieving speed and travel frequency based on the real-time load of the production line to ensure continuous, stable, and uniform output flow. The control system automatically controls the movement of the material distribution trolley based on the online detection values ​​of copper grade, sulfur content, and arsenic content of the material after feeding, accurately unloading the current material into the batching bins that match the range of these three parameters. Each batching bin has a corresponding metering belt conveyor below its discharge port, and each conveyor is equipped with a weighing sensor and a speed sensor. When the control system starts the batching program, each batching bin simultaneously feeds material to its respective metering belt conveyor via a frequency converter-controlled discharge valve. Taking a total conveying capacity of 120 t / h and target batching ratios of 30%, 30%, and 40% for the three batching bins as an example, the control system automatically calculates the target instantaneous discharge rate of the first batching bin as 36 t / h, the second batching bin as 36 t / h, and the third batching bin as 48 t / h.The metering belt conveyor collects the instantaneous weight of the material and the belt speed in real time, calculates the actual instantaneous discharge amount, and performs a sliding average processing to obtain the sliding average discharge amount. Taking the preset batching deviation threshold of 2 t / h as an example, if the sliding average discharge amount of the first batching bin is 33 t / h, which is lower than the target value of 36 t / h and the deviation exceeds the preset deviation threshold, the control system increases the operating frequency of its discharge valve through the frequency converter until the sliding average discharge amount approaches 36 t / h. The sliding average discharge amount of the second batching bin is 35 t / h, and the sliding average discharge amount of the third batching bin is 47 t / h. The deviations of both from their respective target values ​​do not exceed the preset deviation thresholds, and the control system keeps the operating frequency of these two discharge valves unchanged. The adjustment of each batching bin is carried out independently and does not compensate for each other. During the conveying process of the mixed material after batching into the mixer via the belt conveyor, the belt conveyor is equipped with a metal detector to detect metal foreign objects in the mixed material. The control system acquires the detection signal from the metal detector. When the detection signal indicates the presence of a metal foreign object, the control system records the detection time of the metal foreign object. Based on the running speed of the belt conveyor and the distance along the material conveying path from the metal detector to the mixer inlet, the control system calculates the arrival time of the metal foreign object at the mixer inlet. At the arrival time when the metal foreign object is about to reach the mixer inlet, the control system controls the belt conveyor to stop running and issues an alarm signal, so that the material segment carrying the metal foreign object stops on the belt conveyor, preventing the metal foreign object from entering the mixer. Specifically, the control system acquires a first distance value between the installation position of the metal detector on the belt conveyor and the discharge end of the belt conveyor. Based on the first distance value and the operating speed value, it calculates a first conveying time value. Then, based on the detection time point and the first conveying time value, it calculates the first arrival time point of the metal foreign object at the discharge end. The control system also acquires a second distance value between the discharge end of the belt conveyor and the feed inlet of the mixer. This second distance value is the path length along the material conveying path. Based on the second distance value and the operating speed value, it calculates a second conveying time value. Finally, based on the first arrival time point and the second conveying time value, it calculates the arrival time point of the metal foreign object at the feed inlet of the mixer. The proportioned mixture is then fed into a horizontal twin-shaft mixer via a collecting belt conveyor. The mixer is intelligently linked with the front-end batching and conveying system, automatically adapting the mixing speed and material residence time according to the total incoming material flow to forcefully mix the materials. The control system monitors the mixer's operating load and material status in real time, and has automatic interlocking protection functions for overload, blockage, and idling.The mixed material is conveyed by a belt conveyor to the inlet of the humidifying mixer. An online moisture meter is installed at this inlet, measuring the moisture content of the material entering the humidifying mixer to be 5.5%. The control system, considering the current production capacity of 120 t / h and the preset humidification coefficient, calculates the baseline humidification water volume. It then corrects for the difference between the measured moisture content and the preset baseline moisture content of 6.0%, obtaining the target humidification water volume. The flow control valve of the water spray device inside the humidifying mixer is adjusted to ensure the actual water volume reaches this target value. The humidifying mixer continuously adds water while mixing the material, maintaining the outlet material moisture content at approximately 8.5%. After humidification, the material is conveyed by a belt conveyor to the top of the finished product silo. A reversible spreading belt conveyor evenly distributes the finished material into the silo. The bottom of the finished product silo is equipped with a hydraulic gate and a discharge chute. During loading, the control system automatically opens the gate, and the material is directly loaded into the transport vehicle via the discharge chute. In all the above steps, the start and stop of the belt conveyor and the operation of each process equipment are automatically executed by the control system according to a preset logical sequence, requiring no manual intervention.

[0042] In the above production process, spray dust suppression devices are installed above the enclosed belt conveyor, at the inlet of the raw material silo, at the outlet of the raw material silo, at the inlet of each batching silo, at the outlet of each batching silo, at the inlet of the mixer, at the inlet of the humidifying mixer, and at the inlet of the finished product silo. The start and stop of each spray dust suppression device are independently controlled by the control system. The control system pre-stores the correspondence between the location numbers of each spray dust suppression device and the step numbers of each process. When executing step S1, the spray dust suppression device located above the enclosed belt conveyor is activated; when executing step S2, the spray dust suppression device located at the raw material silo inlet is activated; when executing step S3, the spray dust suppression device located at the raw material silo outlet is activated; when executing step S4, the spray dust suppression devices located at the inlets of each batching silo are activated; when executing step S5, the spray dust suppression devices located at the discharge outlets of each batching silo are activated; when executing step S6, the spray dust suppression device located at the mixer inlet is activated; when executing step S7, the spray dust suppression device located at the humidifying mixer inlet is activated; and when executing step S8, the spray dust suppression device located at the finished product silo inlet is activated. When the control system stops executing a corresponding step, it shuts down the spray dust suppression device corresponding to that step.

[0043] This solution enables centralized, automated control of the entire copper concentrate blending process, from unloading, homogenization, intelligent material handling, compartmentalized material distribution, automatic batching, mixing, humidification, to finished product loading. In actual production, operators only need to monitor the sliding average discharge rate displayed on each metering conveyor via the control system interface to directly confirm whether the copper concentrate discharge ratio has reached the preset value. For example, if the sliding average discharge rate of the first batching bin is stable between 35.5 and 36.5 t / h, the second batching bin between 35.5 and 36.5 t / h, and the third batching bin between 47.5 and 48.5 t / h, it indicates that the proportions meet the accuracy requirements. Simultaneously, the moisture content of the material at the outlet of the humidifying mixer can also be read in real-time on the operating interface, remaining near the target value. The entire production line is coordinated by the control system, eliminating manual waiting and adjustment between processes, effectively improving production continuity and automation.

[0044] In existing technologies, the distribution of copper concentrate in different batching bins is typically determined by operators based on incoming material inspection reports or visual experience. They then manually switch the discharge positions of the distribution equipment to unload different grades of copper concentrate into their respective batching bins. Due to the intervention of manual identification and operation, errors in information identification or operation frequently occur, leading to copper concentrate being incorrectly placed into inappropriate batching bins. This causes mixing of materials in the bins, resulting in deviations from the expected material composition during subsequent batching, leading to fluctuations in the proportioning indicators and affecting the stability of the smelting process.

[0045] To address the issues of misclassification and mixing of materials in manual batching, this implementation method further controls the material distribution by jointly matching the grade and impurity parameters of the copper concentrate on a centrally controlled automated production line. The control system pre-establishes a correspondence between the bin number and the ranges of copper grade, sulfur content, and arsenic content in the host computer database. For example, bin number 1 corresponds to copper concentrate with a copper grade of 22%–24%, a sulfur content of 28%–32%, and an arsenic content of less than 0.1%; bin number 2 corresponds to copper concentrate with a copper grade of 18%–20%, a sulfur content of 25%–28%, and an arsenic content of less than 0.2%; and bin number 3 corresponds to copper concentrate with a copper grade of 15%–17%, a sulfur content of 30%–33%, and an arsenic content of less than 0.5%. An online X-ray fluorescence analyzer is installed above the unloading area at the front end of the enclosed belt conveyor, enabling real-time component detection of each batch of copper concentrate during transport. When a batch of copper concentrate enters the conveyor belt, the analyzer sends signals to the control system indicating the measured copper grade (19%), sulfur content (26%), and arsenic content (0.1%). The control system then iterates through the parameter ranges of the three batching bins in its database for matching: the copper grade of 19% is compared to the 22%–24% range of batching bin 1 (not satisfied); it is compared to the 18%–20% range of batching bin 2 (satisfied); and it is compared to the 15%–17% range of batching bin 3 (not satisfied). The sulfur content of 26% is then compared to the 25%–28% range of batching bin 2 (satisfied). Finally, the arsenic content of 0.1% is compared to the less than 0.2% range of batching bin 2 (also satisfied). The control system only designates a batching bin as the target bin when all three measured parameters simultaneously meet the predetermined ranges. In this example, the control system identifies batching bin number two as the target bin and then issues a command to move the distribution trolley along the track to a position directly above the feed inlet of batching bin number two. Previously, the belt conveyor had already delivered this batch of copper concentrate to the top of the bin, and the material accurately falls into batching bin number two as the discharge baffle opens. After matching, the control system determines the bin number of the target batching bin based on the target correspondence and drives the distribution trolley along the track to a position directly above the feed inlet of that bin, ensuring that the currently conveyed copper concentrate accurately falls into the target bin. Operators can view the incoming material detection values ​​in real time on the monitoring interface and compare them with the target bin number matched by the control system, and manually verify the data by comparing it with the pre-stored bin parameter range in the database.

[0046] Through the above scheme, operators can intuitively verify the accuracy of the batch material distribution on the monitoring interface of the control system. The monitoring interface displays in real time the online detection values ​​of copper grade, sulfur content, and arsenic content of the current batch of copper concentrate in a list format, as well as the target bin number selected by the control system after matching. For example, if the interface shows detection values ​​of 19% copper grade, 26% sulfur content, and 0.1% arsenic content, and the corresponding target bin number is No. 2, the operator can manually verify the values ​​by comparing them with the parameter range of No. 2 bin pre-entered in the database to confirm that the three detection values ​​do indeed fall within the three parameter ranges of that bin. Since the entire matching and material distribution process is automatically completed by the control system based on the three-parameter joint matching logic, the manual identification of ore type and manual switching of material distribution points are eliminated. Therefore, in actual operation, there will be no mis-bin or mixed bin situations caused by human error in reading information or manual mistakes. Meanwhile, the detection values ​​of each batch of materials and their corresponding warehouse locations are automatically recorded and saved by the control system, which facilitates subsequent traceability and verification. This ensures the accuracy of the material composition in each batching warehouse from the source and provides a reliable material basis for subsequent multi-warehouse collaborative automatic batching.

[0047] In existing technologies, copper concentrate batching typically involves manually calculating the discharge volume of each bin and then manually setting a fixed operating frequency for the discharge valves of each bin. When fluctuations in material moisture content, changes in particle size, or equipment wear cause the actual discharge volume to deviate from the set value, operators can only detect the deviation through intermittent weighing checks and then manually adjust the frequency. This adjustment cycle is long, and the deviations from each bin are cumulative in the total material flow, making it difficult to achieve dynamic and accurate batching when multiple bins discharge simultaneously.

[0048] To address the issue of inaccurate batching ratios during simultaneous unloading from multiple silos, this implementation incorporates automatic material level monitoring, automatic arch breaking, and anti-blocking pressure stabilization functions in the batching silos, ensuring continuous and stable material feeding and preventing abnormal situations such as bridging, silo blockage, and material interruption. Each of the three batching silos is independently equipped with a metering belt conveyor. Each metering belt conveyor has four weighing sensors installed on its load-bearing beam and a speed sensor installed at the drive roller end. The control system pre-stores the target copper concentrate percentage for each batching silo and the total conveying capacity of the metering belt conveyors. Taking a total conveying capacity of 120 t / h and target batching ratios of 30%, 30%, and 40% for the three silos as an example, the control system automatically calculates the target instantaneous discharge rate as follows: 36 t / h for batching silo 1, 36 t / h for batching silo 2, and 48 t / h for batching silo 3. After batching begins, the hydraulic unloading valves of the three batching silos open simultaneously, and the material falls onto their respective metering belt conveyors. The weighing sensor measures the instantaneous weight of the material on the conveyor belt at a sampling frequency of 10 times per second, while the speed sensor simultaneously measures the belt speed. The control system multiplies the instantaneous weight value by the belt speed value to obtain the actual instantaneous discharge rate of each batching bin, and then performs a moving average processing to obtain the moving average discharge rate of each batching bin. If the moving average discharge rate of batching bin No. 1 is displayed as 33 t / h, which is lower than the target value of 36 t / h, the deviation reaches 3 t / h, exceeding the preset deviation threshold of 2 t / h. The control system then uses the frequency converter to increase the frequency of the drive motor of the discharge valve of batching bin No. 1 from the preset 35 Hz to 38 Hz, so that the discharge rate gradually recovers. Meanwhile, the sliding average discharge rate of batching silo No. 2 was 35 t / h and that of batching silo No. 3 was 47 t / h. Both fluctuated near their respective target values ​​and did not trigger the deviation threshold. Therefore, the control system maintained the operating frequency of these two discharge valves unchanged and did not make any compensatory adjustments to other silos due to the discharge rate deviation of batching silo No. 1. Once the sliding average discharge rate of batching silo No. 1 returned to the range of 35.5~36.5 t / h and the deviation narrowed below the threshold, the control system stopped adjusting and continued to operate at the current frequency. If the sliding average discharge rate of a certain batching bin exceeds the target value and the deviation exceeds the limit, for example, the measured sliding average discharge rate is 39 t / h, which exceeds the target value of 36 t / h and the deviation of 3 t / h exceeds the preset deviation threshold of 2 t / h, the control system will reduce the frequency of the drive motor of the discharge valve of that batching bin from the preset 35 Hz to 32 Hz through the frequency converter, so that the discharge rate gradually decreases. Other bins will not be adjusted in the same way.

[0049] Through this scheme, operators can simultaneously observe three sets of real-time data on the control system monitoring interface: For batching bin No. 1, the target is 36 t / h, with the moving average discharge rate fluctuating between 35.7 and 36.3 t / h; for batching bin No. 2, the target is 36 t / h, with the moving average discharge rate fluctuating between 35.5 and 36.2 t / h; and for batching bin No. 3, the target is 48 t / h, with the moving average discharge rate fluctuating between 47.5 and 48.5 t / h. The moving average discharge rate of each bin continuously approaches its target value. When a batching bin exceeds the tolerance, the value for that bin on the interface turns yellow, while the values ​​for other bins remain green and normal. Operators can directly see that only the bin with the deviation is automatically adjusting, while the other bins maintain a stable operating mode. This scheme transforms the open-loop control method of manually setting a fixed frequency into a closed-loop control method where each compartment is independently measured and adjusted. It also eliminates the problem of accumulated deviations in each compartment when manually adjusting the quantity one by one, by using a strategy of independently correcting deviations in a single compartment without linking adjustments to other compartments. This ensures that multiple types of copper concentrate are consistently fed according to the preset ratio during the simultaneous unloading process.

[0050] In existing automated batching production of copper concentrate, each batching bin is typically equipped with an independent metering belt conveyor. Each conveyor measures its discharge rate in real time using load cells and speed sensors. The control system compares the actual instantaneous discharge rate of each bin with the target instantaneous discharge rate and then independently adjusts the operating frequency of the discharge valve of each bin via a frequency converter, so that the actual discharge rate of each bin approaches its target value. However, this batching method with independent closed-loop regulation of each bin has a long-overlooked problem: during operation, the metering belt conveyors can produce metering errors due to factors such as material adhesion, zero-point drift of the load cells, and belt wear. When a positive error occurs in the metering belt conveyor of a bin, the control system may mistakenly interpret it as a high discharge rate and reduce its discharge frequency; conversely, a negative error may be mistakenly interpreted as a low discharge rate and its discharge frequency increased. Since the adjustment of each bin is carried out independently, this adjustment driven by measurement error will not trigger any alarms. Each bin continues to deviate from the true ratio under the drive of error, and the operator cannot identify the existence of measurement error by simply judging whether the actual material feeding of each bin is close to the target value - because from the feedback of the control system, the actual material feeding of each bin is "up to standard".

[0051] To address this issue, this implementation method, based on multi-bin independent closed-loop batching, adds an online diagnostic and compensation mechanism for metering deviation based on system total flow verification. The control system performs a moving average processing on the time series data of the actual instantaneous discharge volume of each batching silo for a preset time window length, obtaining the moving average discharge volume of each silo to filter out instantaneous fluctuation noise. Subsequently, the control system calculates the sum of the moving average discharge volumes of all batching silos unloading at the same time to obtain the measured value of the system's total instantaneous discharge volume; simultaneously, it obtains the sum of the total conveying capacity values ​​of each metering belt conveyor as the nominal value of the system's total conveying capacity. The measured value of the system's total instantaneous discharge volume is compared with the nominal value of the system's total conveying capacity to obtain the deviation value of the system's total discharge volume. When the absolute value of this deviation value exceeds the preset allowable threshold for system total deviation, the control system determines that there is an overall metering deviation in the current batching system, immediately triggers a system metering anomaly warning, and suspends the independent adjustment operation of the unloading speed of each batching silo except for those that have already triggered independent adjustment, maintaining the current operating frequency of each unloading valve unchanged, awaiting operator confirmation and handling. The basis of this logic is that, under steady-state production conditions where multiple compartments unload material simultaneously, the sum of the sliding average discharge amounts of each compartment should theoretically be equal to the sum of the target instantaneous discharge amounts of each compartment, and the sum of the target instantaneous discharge amounts of each compartment is equal to the nominal value of the total conveying capacity of the system. When this mathematical constraint is violated, it necessarily means that at least one metering belt conveyor has a metering error.

[0052] When the absolute value of the total system feed deviation is less than or equal to the preset system total deviation allowable threshold, it indicates that there is no significant metering deviation in the batching system as a whole. At this time, the control system continues to perform independent adjustment of each bin. If, during this process, the deviation between the moving average feed rate and the target instantaneous feed rate of a certain batching bin exceeds the preset deviation threshold, the control system marks the batching bin as a suspected deviation bin and obtains the ratio of the moving average feed rate to the target instantaneous feed rate of the suspected deviation bin as the relative deviation coefficient of the suspected deviation bin. Subsequently, the control system retrieves the relative deviation coefficient records of the suspected deviation bin within N consecutive time windows before the current time point and calculates the standard deviation of these relative deviation coefficients. When the standard deviation is less than the preset stability threshold, it indicates that the deviation of the bin remains stable over multiple consecutive time windows and does not alternate between positive and negative over time. Based on this, the control system determines that the deviation is a systematic measurement deviation rather than a random fluctuation deviation, and uses the relative deviation coefficient to perform online correction on the target instantaneous discharge quantity of the batching bin stored in the control system—multiplying the original target instantaneous discharge quantity by the relative deviation coefficient, and using the corrected target instantaneous discharge quantity to replace the original target instantaneous discharge quantity for subsequent comparison and adjustment. After correction, the control system restarts the independent adjustment operation of the unloading speed of each batching bin. The principle of this scheme is to use the standard deviation to distinguish the nature of the deviation: random fluctuation deviations fluctuate around 1.0 in relative deviation coefficients over multiple time windows, with a large standard deviation; while systematic measurement deviations exhibit continuous, unidirectional shifts, with the relative deviation coefficient remaining stable over multiple time windows and a small standard deviation.

[0053] Compared with existing technologies, this implementation method has significant differences. In existing multi-compartment batching control systems, each metering belt conveyor acts as an independent measuring element, providing its own feed rate data to the control system. The control system only focuses on whether the feed rate of a single compartment reaches its target value, never verifying the measurements of all compartments as a whole. When a metering belt conveyor experiences a metering error, the existing system mistakenly interprets it as a true feed rate deviation and adjusts accordingly, causing a systematic shift in the batching ratio driven by the error. In contrast, this implementation method verifies the overall system flow rate, first determining whether a metering deviation exists at a global level. After confirming that the overall metering is correct, it then uses standard deviation analysis of the relative deviation coefficient to distinguish whether the deviation of a single compartment is a systematic metering deviation or a random fluctuation deviation, only compensating for systematic deviations online. This mechanism enables the batching system to have self-diagnostic capabilities for metering errors, fundamentally solving the problem of systematic drift in the batching ratio caused by the inherent errors of the metering devices in closed-loop batching systems. In actual operation, operators can directly observe the real-time reading of the total system feed deviation value through the control system monitoring interface. When the value remains stable within the preset total system deviation allowable threshold, it indicates that the overall metering status of each metering belt conveyor is normal. When a certain bin is marked as a suspected deviation bin and online correction is completed, operators can view the relative deviation coefficient of the bin and the target instantaneous feed value before and after correction in the correction history. After correction, the fluctuation range of the sliding average feed of the bin is not significantly different from that before correction, but the total system feed deviation value is improved compared with that before correction. This comparison can directly verify the effectiveness of the correction.

[0054] In existing automated copper concentrate batching systems, when a systematic metering deviation occurs in the metering belt conveyor of a batching bin, the control system compensates by multiplying the target instantaneous discharge quantity of that bin by a relative deviation coefficient through online correction. However, this online correction mechanism harbors a more subtle and difficult-to-detect problem: the metering error of the metering belt conveyor is not always constant. In actual production, belt wear gradually reduces belt thickness, fatigue of the weighing sensor slowly decreases sensitivity, and dust accumulation on the belt and idlers causes a continuous increase in tare weight measurements—all these factors lead to a unidirectional, slow, and continuous change in metering error over time, the so-called "trend drift." When the drift rate is slow enough, the relative deviation coefficient observed in each time window still satisfies the characteristic of a small standard deviation, and is therefore judged as a systematic deviation and corrected by the aforementioned mechanism. However, as the drift continues to worsen, a new deviation reappears after each correction and is corrected again, resulting in repeated corrections and continuous unidirectional accumulation of the target instantaneous discharge quantity of that bin. Even more seriously, when operators only observed from the monitoring interface, the actual material feeding of each compartment steadily approached its respective target value, and the batching system appeared to be operating perfectly normally—no one realized that the target value itself had already deviated significantly under the drive of error, and the actual batching ratio had long deviated from the preset process requirements.

[0055] To address this issue, this implementation adds a trend drift identification and proactive compensation mechanism to the aforementioned system total flow verification and online correction mechanism. After completing the online correction of the target instantaneous discharge volume for any batching silo, the control system does not simply write the correction result and forget it. Instead, it records all relevant information for each correction—including the correction timestamp, the target instantaneous discharge volume before correction, the target instantaneous discharge volume after correction, and the relative deviation coefficient that triggered the correction—in the correction history of that silo. Using the current moment as a reference, the control system acquires all correction records for that batching silo within a preset historical backtracking period, and calculates the cumulative correction magnitude and number of corrections for the target instantaneous discharge volume of that batching silo within that historical backtracking period. The physical meaning of the cumulative correction magnitude is: the algebraic sum of all single correction magnitudes for that silo within the historical backtracking period; the physical meaning of the number of corrections is: the total number of times that the silo triggers online correction and completes compensation within the historical backtracking period. When the cumulative correction magnitude exceeds the preset cumulative correction magnitude threshold and the number of corrections exceeds the preset correction number threshold, the control system determines that the metering belt conveyor of the batching silo has a continuously deteriorating metering drift trend, triggering a metering system maintenance warning. The basis for this judgment logic is that if the deviation is a constant offset, the target value will match the actual physical state after one or a few corrections, and subsequent corrections will not be repeatedly triggered; however, if the deviation is a trend drift, corrections will occur repeatedly and the correction amount will continue to accumulate in one direction—the simultaneous exceeding of the limits of both the cumulative correction magnitude and the number of corrections is a direct quantitative representation of the phenomenon of "repeated corrections and continuous accumulation".

[0056] Upon triggering a maintenance warning, the control system does not immediately shut down for maintenance. Instead, it initiates a more refined predictive compensation operation. The control system acquires the moving average discharge rate sequence of the batching silo over M consecutive time windows prior to the warning trigger. Linear regression analysis is performed on this sequence to obtain the slope value of the discharge rate trend. The sign of this slope value reflects the direction of drift—a positive value indicates that the measured value is higher over time, and a negative value indicates that the measured value is lower over time; the absolute value of the slope value reflects the rate of drift—the larger the absolute value, the faster the drift. When the absolute value of the trend slope value is greater than a preset trend slope threshold, it indicates that the drift rate has reached a level worthy of compensation. The control system calculates the trend prediction compensation value of the target instantaneous discharge rate of the batching silo based on this trend slope value, and then uses this trend prediction compensation value to perform a secondary correction on the target instantaneous discharge rate of the batching silo, obtaining the secondary corrected target instantaneous discharge rate, which is then compared with the moving average discharge rate of the batching silo. The principle of this compensation operation is as follows: by performing linear regression on the moving average feed rate sequence to extract the drift trend slope, the amount of measurement drift that will continue to change over a period of time after the current moment can be estimated. Thus, the advance compensation is completed before the drift accumulates to trigger the next correction, so that the correction of the target value is transformed from retrospective compensation to ex-ante prediction.

[0057] Compared with existing technologies, this implementation method has significant differences. Existing technologies for improving the metering accuracy of belt scales, such as by installing weighing level gauges in the batching silos, using the ratio of the silo weight difference to the cumulative value of the batching scale as a correction factor to compensate for the batching scale accuracy, or by adjusting and compensating the proportions among multiple belt scales to detect abnormalities online, all focus on single, independent error detection and compensation. They do not consider the trend characteristics of continuous changes in metering errors over time, nor do they establish a long-term monitoring and trend analysis mechanism for correction behavior. In contrast, this implementation method establishes a correction history record, jointly determines the cumulative correction magnitude and the number of corrections, and uses linear regression analysis on the moving average feed rate sequence to extract the slope of the drift trend and implement advance compensation, forming a complete closed loop from "identifying trend drift" to "predicting and compensating for future drift". In actual operation, operators can view the correction records of any bin through the correction history query page of the control system. When the correction record of a bin shows that multiple corrections in the same direction have occurred within several consecutive hours and the cumulative correction magnitude continues to increase, the system will automatically trigger a maintenance warning. Operators can then arrange for the corresponding metering belt conveyor to be cleaned or calibrated. After the warning is triggered, the correction frequency of the bin that has undergone secondary correction will be significantly reduced in subsequent operation. This change can be directly observed from the correction history record, indicating that the advance compensation has effectively slowed down the accumulation rate of drift.

[0058] In existing technologies, copper concentrate humidification is typically achieved by operators visually assessing the moisture content of the incoming material and manually opening the water spray valve. The humidification amount is judged solely by experience, lacking a quantitative correlation with the actual moisture content of the incoming material and the current production capacity. When the moisture content of the incoming material fluctuates or production capacity is adjusted, manual adjustments are often delayed, causing the moisture content of the humidified material to deviate from the suitable range for smelting and furnace feeding. This results in either material being too dry, causing dust generation, or too wet, leading to material agglomeration, sticking to the walls, and clogging subsequent equipment.

[0059] To address the issue of the inability to accurately adjust the humidification amount in real time based on changes in incoming material moisture content and production capacity, this embodiment installs an online microwave moisture detector above the inlet belt conveyor of the humidifying mixer, specifically the online moisture detector described in step S7, to measure the moisture content of the material before it enters the humidification process. The control system has three preset key parameters: a preset baseline moisture content of 6.0%, a preset target moisture content of 8.5%, and a preset humidification coefficient of 0.025 tons of water per ton of material. This coefficient means that, under calibrated conditions, 0.025 tons of water are needed to increase the moisture content of each ton of material from 6.0% to 8.5%.

[0060] During production, the mixed materials are discharged from the mixer and conveyed to the inlet of the humidifying mixer via a belt conveyor. An online microwave moisture detector continuously scans the material flow to measure the current moisture content of the incoming material, assuming it to be 5.5%, and sends this signal to the control system in real time. Simultaneously, the control system obtains the production capacity value from the currently running batching program, assuming it to be 120 t / h. The control system first calculates the baseline humidification water volume based on the current capacity and the preset humidification coefficient: Baseline humidification water volume = Current capacity × Preset humidification coefficient; Substitute the values: The baseline humidification water volume = 120 t / h × 0.025 t water / t material = 3.0 t water / h; The preset humidification coefficient of 0.025 is in tons of water per ton of material, which means the amount of water required to be added per ton of material. The current capacity value is used to convert the amount of water added per unit of material into the total amount of water added per unit time.

[0061] Next, the control system calculates the incoming material moisture content deviation: incoming material moisture content deviation = preset baseline moisture content value - measured moisture content value; incoming material moisture content deviation = 6.0% - 5.5% = 0.5%. The system uses this difference to correct the baseline humidification water volume according to a preset correction algorithm (for example, linear correction based on a ratio of 0.8 t water / h for every 1% deviation). The larger the deviation, the larger the correction. In this example operating condition, the incoming material is 0.5% drier, and after calculation by the algorithm, an additional 0.4 t water / h of humidification water is required. The calculated target humidification water volume is 3.4 t water / h.

[0062] The control system then sends the target value to the electric flow regulating valve of the water spray device. The valve opening automatically adjusts from the current opening to the position required for a flow rate of 3.4 tons of water per hour. The electromagnetic flow meter on the downstream pipeline feeds back the actual flow rate of 3.38 tons of water per hour to the control system. The control system compares this with the actual flow rate and fine-tunes the valve opening until the actual humidification water volume stabilizes around 3.4 tons of water per hour. The double-helix mixing shaft inside the humidifying mixer simultaneously forces the mixing of materials and water, ensuring uniform water penetration. A second online moisture detector is installed at the outlet of the humidifying mixer. This detector measures the actual moisture content of the humidified material discharged from the mixer and sends it to the control system. The control system has a preset allowable range for humidification deviation. It compares the measured moisture content of the humidified material measured by the second online moisture detector with the preset target moisture content value of 8.5% to obtain the moisture deviation value after humidification. When the moisture content deviation after humidification exceeds the allowable range, the control system corrects the preset humidification coefficient based on the deviation and replaces the original preset humidification coefficient with the corrected coefficient for subsequent calculation of the baseline humidification volume. The allowable range for humidification deviation can be preset according to actual process requirements, for example, set to ±0.3%.

[0063] When correcting the preset humidification coefficient based on the moisture deviation value after humidification, the control system has a preset upper limit value for the single correction amplitude. The control system calculates the initial correction amount based on the moisture deviation value after humidification and compares the absolute value of the initial correction amount with the upper limit value for the single correction amplitude. When the absolute value of the initial correction amount is less than or equal to the upper limit value for the single correction amplitude, the initial correction amount is used as the final correction amount. When the absolute value of the initial correction amount is greater than the upper limit value for the single correction amplitude, the upper limit value for the single correction amplitude is used as the absolute value of the final correction amount, while maintaining the positive or negative sign of the initial correction amount. The preset humidification coefficient is corrected using this final correction amount.

[0064] In this system, when calculating the initial correction amount based on the moisture deviation value after humidification, the control system first calculates the correction increment for the preset humidification coefficient using the initial correction amount dynamic calculation model. Then, it compares the output correction increment with the aforementioned single correction amplitude upper limit to determine the final correction amount. Specifically, the control system records the moisture deviation values ​​acquired most recently after humidification, subtracts the deviation value from the previous time value from the current time value to obtain the moisture deviation change rate. The control system has a pre-stored initial correction amount dynamic calculation model, which takes the moisture deviation value and the moisture deviation change rate as inputs and the correction increment for the preset humidification coefficient as output. This model is configured as follows: when the absolute value of the moisture deviation value after humidification is greater than the preset dynamic adjustment start threshold, and the moisture deviation change rate has the same sign as the moisture deviation value after humidification, the absolute value of the output correction increment is greater than the absolute value of the reference proportional correction amount, which is the absolute value of the deviation multiplied by the preset reference proportional coefficient; when the absolute value of the deviation is greater than the dynamic adjustment start threshold, and the change rate has a different sign than the deviation, the absolute value of the output correction increment is less than the absolute value of the reference proportional correction amount. The model is also configured as follows: as an optional further optimization technique of the present invention, when the absolute value of the deviation is less than or equal to the dynamic adjustment start threshold and the absolute value of the rate of change is greater than the preset deviation rate of change warning threshold, it is determined to be a critical pre-adjustment state. At this time, the output correction increment is the reverse pre-adjustment correction amount, the sign of which is opposite to the sign of the rate of change, and the absolute value is the absolute value of the benchmark proportional correction amount multiplied by the preset pre-adjustment attenuation coefficient. The preset pre-adjustment attenuation coefficient is a constant greater than 0 and less than 1. In the critical pre-adjustment state, the absolute value of the benchmark proportional correction amount is calculated by the control system using the dynamic adjustment start threshold instead of the absolute value of the deviation at the current moment.

[0065] This solution allows operators to directly observe a continuous set of real-time data on the control system's monitoring interface: the inlet moisture detector displays a current incoming material moisture content of 5.5%, the current production capacity is 120 t / h, the control system calculates a baseline humidification water volume of 3.0 tons of water per hour, the target humidification water volume is 3.4 tons of water per hour, and the actual humidification water volume fed back by the electromagnetic flowmeter remains stable between 3.35 and 3.45 tons of water per hour. When the incoming material moisture content fluctuates, for example, rising from 5.5% to 6.2%, the operator can see the inlet moisture detection value change to 6.2%, the target humidification water volume automatically decreases to approximately 2.8 tons of water per hour, and the actual humidification water volume decreases accordingly. This solution incorporates the measured incoming material moisture content and production capacity as two independent variables into the quantitative calculation model for humidification volume, overcoming the shortcomings of manual watering which relies solely on experience and lacks quantitative basis. This ensures that the moisture content of the humidified finished material remains stable within the preset target range, avoiding both dust generation and wall adhesion.

[0066] In existing technologies, when the humidified and stirred finished copper concentrate is sent into the finished product silo, a fixed discharge point is often used for unloading. The material falls vertically continuously from a single discharge port, naturally accumulating into a cone-shaped pile within the silo. Due to the different angles of repose, coarse and fine particles segregate, with coarse particles rolling to the bottom periphery of the cone and fine particles remaining at the top center. This results in differences in material composition and moisture content at different locations within the silo, leading to inconsistent quality of copper concentrate in different parts of the same transport vehicle after loading.

[0067] To address the issue of uneven quality caused by material segregation within the finished product silo, this embodiment installs a reversible material distribution belt conveyor on top of the silo. This conveyor is driven by a bidirectional electric roller, and the belt can rotate in both directions. The control system pre-stores the total longitudinal length of the rectangular opening of the finished product silo, assumed to be 15 m, and sets travel coordinates from 0.0 to 15.0 m along the longitudinal centerline, with one edge of the opening as the origin. The reversible material distribution belt conveyor is mounted on rails laid on both sides of the silo opening via wheels on its drive frame, and is driven by a variable frequency drive motor to move back and forth along the rails. Before unloading begins, the control system sets the initial position of the reversible material distribution belt conveyor at a travel coordinate of 2.5 m. When the finished material discharged from the humidifying mixer is conveyed to the reversible material distribution belt conveyor on top of the silo via the belt conveyor, the control system initiates the material distribution program. The reversible fabric conveyor belt initially moves towards the other end of the hopper at a low speed of 5 m / min using the variable frequency drive motor. Simultaneously, the reversible belt rotates forward, evenly spreading material from the vehicle's discharge port into the hopper. When the conveyor belt reaches a travel coordinate of 12.5 m, it triggers a limit switch at that location. This signal is transmitted back to the control system, which then instructs the drive motor to reverse, causing the conveyor belt to reverse direction while maintaining a travel speed of 5 m / min. Simultaneously, the reversible belt automatically switches to reverse direction, ensuring that the material discharge from the discharge port always faces the already-spread area within the hopper. When the conveyor belt reverses to a travel coordinate of 2.5 m, it triggers the limit switch again, causing the drive motor to reverse once more. This cycle of spreading material continues. A continuous level gauge measures the material accumulation height with the hopper bottom as the zero point. The control system continuously receives signals from the continuous level gauge at the top of the finished product silo. When the continuous level gauge detects that the material accumulation height has reached the preset maximum allowable stacking height of 12 m, the control system stops the reversible material conveyor belt from feeding material and simultaneously sends a silo full warning signal to the operation interface. At this time, the operator can arrange loading operations. After the material in the silo is transported out and the material level drops to below the reset level of 8 m, the control system automatically resumes the reversible material conveyor belt from reversing to feed material.

[0068] This solution allows operators to visually verify the uniformity of the material distribution process on the control system's monitoring interface. The right side of the interface displays the current travel direction of the reversible material distribution belt conveyor (forward or backward), with the current travel coordinate cycling between 2.5 and 12.5 m, and the current travel speed set at 5 m / min. The left side of the interface displays the current material level in the finished product hopper as a progress bar. When the material level gradually rises from 8 m to 12 m and reaches the limit, the progress bar changes from green to red, and the reversible material distribution belt conveyor stops. Operators can also climb onto the inspection platform at the top of the hopper and observe through the hopper opening window that the material surface is roughly flat, rather than forming a cone-shaped pile due to single-point material drop. This solution, combining the reversible material distribution belt conveyor's reciprocating movement along the entire longitudinal length of the hopper opening with forward and reverse belt rotation, achieves uniform layer-by-layer material distribution, eliminating the segregation of coarse and fine particles caused by fixed drop points, and ensuring that materials loaded at different locations and at different times within the same finished product hopper are more consistent in composition and moisture content.

[0069] In existing technologies, the loading process of finished product silos typically involves operators manually controlling the opening and closing of hydraulic gates below the silo, relying on visual judgment to determine the fullness of the truck bed before closing the gates. Because the timing of manual operation varies from person to person, the weight of finished copper concentrate loaded into the same batch of transport vehicles can differ. Insufficient loading leads to inefficient transport, while excessive loading results in material spillage, causing both losses and site contamination. Furthermore, when the gates open, the free-falling material impacts the truck bed floor, instantly filling the loading area with dust.

[0070] To address the challenges of accurately controlling the loading volume of finished products and the spread of dust during unloading, this embodiment connects a hydraulic gate and an unloading chute sequentially to the bottom of the conical discharge port of the finished product silo. The hydraulic gate is the same as the unloading gate described in step S9. The unloading chute is a fully enclosed rectangular steel structure with a flexible telescopic pipe at its end, made of wear-resistant rubber canvas. Its lower outlet can be adjusted to the bottom of the truck bed or the top surface of the material pile depending on the loading height. The opening of the hydraulic gate is continuously adjusted by the control system via a hydraulic proportional valve. A radar level gauge is installed on the side wall of the unloading chute to monitor the flow of material entering the chute in real time. The control system simultaneously receives vehicle tare weight signals and target load signals from the loading weighbridge. Before loading begins, the empty truck undergoes tare weight weighing in the loading channel under the finished product silo. The weighbridge system sends the empty truck weight and the preset target load value to the control system. After calculating the target total weight, the control system inputs the unloading program. After the operator presses the loading start button, the control system first lowers the lower outlet of the flexible telescopic chute to a height of approximately 0.3 meters above the truck bed. Then, the hydraulic gate is pre-opened at a small 20% opening, allowing material to flow at a low velocity through the unloading chute and flexible telescopic chute into the bottom of the truck bed. Once the radar level gauge detects a stable material level established by the material flow in the chute, the control system gradually increases the hydraulic gate opening to the normal unloading opening of 80%, accelerating the unloading of material into the truck bed. Simultaneously, the loading weighbridge continuously weighs the vehicle dynamically, updating the real-time weight value every 0.5 seconds and sending it to the control system. When the real-time total weight of the vehicle displayed on the weighbridge reaches 95% of the target total weight, the control system issues a pre-closing command, rapidly reducing the hydraulic gate opening from 80% to 20%, and simultaneously decreasing the material flow rate. When the total weight on the weighbridge reaches 100% of the target weight, the control system immediately issues a closing command. The hydraulic gate closes completely for a preset configurable closing time, which is 2 seconds in this example. The remaining material in the chute continues to fall, and the loading is completed. Subsequently, the lower outlet of the flexible telescopic chute automatically rises and retracts to a position flush with the end of the unloading chute, completing one loading cycle.

[0071] This system allows operators to monitor the entire loading process on the control system's monitoring interface. The interface displays the current vehicle tare weight, target total weight, real-time total weight on the weighbridge, and the current percentage opening of the hydraulic gate. Operators can observe that the real-time total weight gradually increases from the tare weight, with the gate opening maintaining a corresponding percentage throughout. When the real-time total weight reaches 95% of the target total weight, the gate opening rapidly decreases from approximately 80% to approximately 20%, visually indicating a significant reduction in material flow rate. When the real-time total weight further increases to 100% of the target total weight, the gate opening returns to zero, and loading stops. The weight difference before and after loading for each vehicle is the actual loading amount, automatically recorded by the weighbridge system. After ten consecutive loading cycles, operators can view the deviation between the actual loading amount and the target value for each cycle. The distribution range of these deviations directly reflects the quantitative accuracy of the loading process. Furthermore, the lower outlet of the flexible telescopic chute is flush with the floor of the truck bed or the material surface for unloading. Combined with a fully enclosed unloading chute and gate speed control, operators can clearly observe almost no dust overflowing around the vehicle at the loading site. This solution replaces the traditional manual visual gate opening and closing method with an automatic closed-loop loading method driven by real-time weighing feedback from the weighbridge, enabling precise control of the finished product loading quantity while effectively suppressing dust diffusion during the unloading process.

[0072] In existing technologies, after finished copper concentrate is loaded onto trucks, the surface of the material inside the truck bed is exposed. During transportation, fine-grained mineral powder is easily scattered and lost from the top of the truck bed due to wind and road bumps, causing material loss and dust pollution to the road surface and environment along the transportation route. The usual solution is to have personnel manually spray the surface of the truck bed with a water hose after loading. However, the uniformity and completeness of the spraying depend entirely on the operator's experience, making it difficult to guarantee that every truck will consistently achieve the effect of suppressing dust.

[0073] To address the issue of material scattering from the top of the truck bed during finished product transportation, this embodiment incorporates an automatic surface curing spray system above the loading aisle of the finished product silo. This spray system consists of a spray pipe spanning the loading aisle, multiple atomizing fan-shaped nozzles mounted on the spray pipe, an electric diaphragm metering pump, a curing agent storage tank, and a clean water inlet. The curing agent storage tank is pre-filled with a liquid, environmentally friendly crusting agent, the active ingredient of which is a water-soluble polymer. This agent is mixed online with clean water at a 1:100 volume ratio before use. The control system automatically triggers the surface spraying process after the loading procedure is completed, the hydraulic gate is fully closed, and a loading completion signal is received from the weighbridge.

[0074] When the spraying program starts, the metering pump simultaneously extracts the crusting agent concentrate and water at a set ratio. The mixed diluted solution is then sprayed downwards from the atomizing fan-shaped nozzles through the spray pipes. The nozzle installation spacing and spray angle are pre-arranged so that when the vehicle stops at the designated position in the loading aisle, the spray coverage width extends approximately 0.1 m beyond the two sides of the inner wall of the truck bed. The longitudinal coverage length is controlled by the spraying time. The control system pre-stores spraying schedules corresponding to common truck bed lengths; for example, a 9.6 m long truck bed corresponds to a spraying time of 25 s, and a 13 m long truck bed corresponds to a spraying time of 35 s. Operators select the corresponding truck bed length setting through the control system interface when the vehicle enters the site, or the control system automatically matches a typical truck bed length based on the vehicle's tare weight data when linked with the loading weighbridge. During the spraying process, each atomizing nozzle evenly sprays the diluted solution, forming a continuous thin liquid film on the material surface. The metering pump automatically stops after running for the preset spraying time, completing a single spraying cycle.

[0075] This method allows operators to verify the surface curing effect through simple observation. After spraying, operators can climb onto the viewing platform or use the observation platform set up on the side of the loading lane to directly observe that the surface of the material inside the truck bed is uniformly moistened. The surface color changes from the dry light yellowish-brown before spraying to a moist dark brown, and the moist layer continuously covers the entire material surface, with no obvious dry spots missing at the corners of the truck bed. After the vehicle stops briefly in the loading area for about 3-5 minutes, some of the moisture in the surface liquid film permeates and evaporates, and the effective components of the crusting agent form an interlocking mesh film between the material surface particles. At this time, a light touch of the material surface with a fingertip can feel a distinct stickiness between the material particles, which are about 0.5-1 cm thick, and are no longer in a loose, flowing state. During subsequent transportation, even at speeds of 40-60 km / h, no significant dust is observed rising from the top of the truck bed from following vehicles or roadside observation points. This solution uses the loading completion signal as a trigger condition to automatically complete a quantitative surface spraying and curing operation, eliminating the randomness and uneven coverage problems of manual spraying, and effectively reducing material scattering losses and dust spillage during transportation.

[0076] In existing technologies, each dust-generating point in a copper concentrate blending production line typically has an independent dust collector. The collected dust is discharged separately or bagged and transported off-site, lacking a unified dust recycling path. This collected dust still contains valuable metal components comparable to the raw materials. Direct discharge or low-cost disposal results in resource waste, while simply returning it to the raw material silo may interfere with the proportioning accuracy due to the incompatibility of dust composition with the current batch.

[0077] To address the issue of ineffective dust collection and recycling, this implementation method incorporates an integrated dust collection system and a centralized dust collection and return system. The dust collection system is integrated with all dust-generating equipment along the entire production line. When unloading, conveying, stacking, retrieving, batching, and mixing equipment starts, the dust collection system automatically starts synchronously. After equipment shutdown, the dust collection system shuts down after a delay to thoroughly remove residual dust. The system monitors pipeline negative pressure and equipment differential pressure in real time, automatically performing pulse cleaning and timed dust unloading operations, and adaptively adjusting the dust collection airflow based on dust generation. The system consists of multiple star-shaped dust discharge valves at the bottom of the dust collectors, a closed pneumatic conveying pipeline, a dust collection hopper, a dust metering screw conveyor, and a return conveyor belt. Each component is connected to the control system for unified management, and the collected dust is uniformly returned to the batching system for recycling. All dust collectors are distributed along the production line at dust-prone locations such as the top conveyor belt drop point of the raw material silo, the mixer inlet, the humidifying mixer inlet, and the top distribution conveyor belt drop point of the finished product silo. Its placement complements the spray dust suppression device, each undertaking different functions: dust collection and dust suppression. The rotary valves at the bottom of each dust collector open sequentially at time intervals set by the control system, preventing simultaneous opening of multiple valves and potential blockage of the pneumatic conveying pipeline. Each rotary valve opens for approximately 15 seconds, discharging the dust accumulated in the dust collector hopper into the pneumatic conveying pipeline. A Roots blower provides negative pressure airflow within the pipeline, transporting the dust in a suspended state to the top of the dust collection hopper. After being separated by filter bags within the hopper, the dust falls to the bottom. A level gauge is installed at the bottom of the dust collection hopper. When the level rises to the preset high level of 2.5 m, the level gauge signal triggers the control system to start the dust metering screw conveyor. The driving end of the metering screw conveyor is equipped with a speed sensor and a weighing module. Its outlet leads to a short-distance return belt conveyor. The discharge point of the return belt conveyor is located above the collecting belt conveyor, which is a conveyor that receives the material discharged from each metering belt conveyor and sends it to the mixer.

[0078] When the control system initiates the dust collector return program, the metering screw conveyor uniformly transports the dust collector ash from the collecting hopper at a speed of 15 rpm. The weighing module measures the instantaneous weight of the material in the screw tube in real time, and the speed sensor synchronously measures the screw shaft speed. The control system calculates the actual instantaneous return amount of the dust collector ash based on this. The return belt conveyor continuously scatters this dust collector ash onto the material layer of the collecting belt conveyor, where it merges with the proportioned mixture being delivered and then enters the subsequent mixer. During the return process, the control system acquires the total capacity of the current production line and the proportioning data of each batching bin in real time. When the dust collector ash collecting hopper level meets the discharge conditions, the instantaneous return amount of the metering screw conveyor is controlled within the range of 0.5% to 1% of the total capacity to ensure that the mixing ratio of dust collector ash is small and stable, and will not significantly change the overall composition of the current batch of materials. When the collecting hopper level is insufficient, the return process stops. When the material level in the dust collection hopper drops to the preset low level of 0.5m, the level gauge signal triggers the control system to stop the metering screw conveyor, the return process ends, and it waits for the material level to rise again before restarting.

[0079] This system allows operators to visually monitor the operational status of dust collector ash recycling on the control system's monitoring interface. The interface displays the current material level in the dust collector hopper. As the material level gradually rises from 0.5 m to 2.5 m, the rotary valve's operation record shows the sequential opening status of each valve, allowing operators to confirm that the ash discharge from each dust collector hopper is normal. When the material level reaches the 2.5 m high level, the interface displays that the metering screw conveyor has started, with an instantaneous return rate of approximately 0.6 t / h, which is about 0.5% of the total capacity of 120 t / h, within the set range. When the material level falls back to the 0.5 m low level, the metering screw conveyor stops operating. Operators can also inspect the surface of the material collected on the return conveyor belt below the material drop point during routine inspections. Using a sampling shovel, they can take a mixed sample at any point before the humidifier outlet, pass it through a 200-mesh sieve, and perform chemical analysis. Comparing the copper content of the individual dust sample with the mixed sample, if the difference is within the expected range, it indicates that the dust has been uniformly mixed into the mainstream material. This solution centrally transports, collects, and meters the dust collected from various dust-generating points on the production line, then uniformly returns it to the mainstream material in a small, stable manner. This achieves centralized and effective recovery of valuable dust without significantly affecting the original proportions, eliminating the waste of dust discharge.

[0080] In existing technologies, even if the production line implements sequential interlocking automatic control, operators still need to continuously monitor the equipment status in front of the screen in the central control room. If an operator temporarily leaves the workstation due to inspection, shift handover, or other matters, and a sudden equipment failure triggers an interlocking shutdown, the operator cannot immediately know the situation on site and can only investigate afterward by reviewing historical alarm records. The emergency response time is significantly delayed, especially when a single person is on duty at night.

[0081] To address the issues of operators being unable to leave the central control room and delays in obtaining abnormal information, this implementation adds a remote mobile monitoring function to the control system. The main controller of the control system adds an industrial Ethernet communication module, which connects to the factory's local area network switch via shielded twisted-pair cable, and then establishes an encrypted tunnel connection with the cloud message relay server through the enterprise firewall. Simultaneously, a monitoring application running on mobile terminals is developed. After operators log in with authorized accounts, the mobile terminal interface displays the real-time operating status of all production line equipment, instantaneous material feed of each metering belt, humidification water volume, and finished product silo level, using the same flowchart format as the central control room monitoring interface. When the current signal of any equipment on the production line triggers the fault shutdown interlock procedure, the control system immediately generates an alarm message while disconnecting the relevant equipment. The message includes the name of the faulty equipment, fault type, trigger time, and current interlock shutdown progress. This message is pushed to all online mobile terminals via the communication module within 2 seconds. Upon receiving the alarm, the mobile terminal emits continuous vibration and a dedicated alert sound. Operators can directly jump to the alarm details interface by clicking the push notification.

[0082] The operator also has a password-protected remote emergency stop button on the mobile terminal. When the operator observes a situation requiring an emergency stop through the mobile terminal, they can press and hold the button for more than 2 seconds. The terminal will send an encrypted emergency stop command to the control system. After receiving the command, the control system verifies the sender's identity. Once the command is confirmed to be legitimate, it automatically executes the entire material flow shutdown procedure, which is completely equivalent to pressing the emergency stop button on the control panel in the central control room.

[0083] The method for verifying the effectiveness of this scheme is simple and intuitive. An operator can carry a mobile terminal with a monitoring application installed to an office building approximately 300 meters from the control room. The real-time status of the production line observed on the mobile terminal is manually compared with the image on the fixed monitor in the control room every 30 seconds. This confirms that the colors, current values, and material level data of each device displayed are completely consistent. Subsequently, under safety supervision, the mixer overload protection is manually triggered on-site. The mobile terminal shows a vibration alarm approximately 1-2 seconds later, with the notification clearly indicating an overload fault in the mixer and a sequential shutdown of the entire line, matching the alarm list in the control room. In another simulation, after the operator presses and holds the emergency stop button on the mobile terminal, returning to the production line confirms that each device stops sequentially according to the preset material flow direction, with the loading hydraulic gate stopping unloading last. At the end of each shift, operators check the number of loadings, cumulative material discharge from each compartment, and total humidification water volume on the mobile terminal report page. These figures are then manually compared with the weighbridge slips and cumulative flow meter readings printed from the weighbridge. Any discrepancies between the three sets of data are within acceptable limits. This solution frees operators from being confined to a fixed control room, allowing them to be aware of abnormal situations immediately while on the move and providing remote emergency intervention capabilities, effectively shortening the time interval from fault occurrence to manual confirmation.

[0084] In existing technologies, the operation records of copper concentrate blending production lines are mostly filled out manually on paper forms or entered into computer spreadsheets afterward. The records include the set values ​​of the blending ratio for each time period, the amount of water added, and the number of trucks loaded. This recording method not only relies on the operator's sense of responsibility, but also has low time resolution. Once product quality fluctuations or customer feedback on quality issues occur, it is often difficult to accurately trace which specific link, time period, or truck's production data deviated from the record. Reliable data support is lacking for determining responsibility and improving the process.

[0085] To address the issues of inefficient production data recording and broken quality traceability chains, this implementation method establishes a complete automatic recording and traceability system for production process data within the control system. The control system's database server is equipped with a large-capacity hard disk array, which cyclically stores data from all online monitoring instruments and control actuators across the entire production line according to a preset cycle. This data specifically includes: copper grade, sulfur content, and arsenic content values ​​for each batch of incoming material measured by an online X-ray fluorescence analyzer, along with corresponding timestamps; target instantaneous discharge setpoints and continuous actual instantaneous discharge values ​​for each metering belt conveyor; moisture content of the material before humidification measured by an online microwave moisture analyzer; instantaneous actual humidification water volume feedback from the electromagnetic flowmeter; continuous level gauge height values ​​at the top of the finished product silo; tare weight, target total weight, and real-time total weight values ​​feedback from the loading weighbridge; the opening percentage curve of the hydraulic gate; and the operating current values ​​of the drive motors of each major piece of equipment. All data is tagged with real-time timestamps accurate to the second during storage.

[0086] Each time a transport vehicle completes loading, the hydraulic gate closes completely, and a loading completion signal is received from the weighbridge, the control system automatically generates a unique traceability batch number for that vehicle. The encoding rule for the traceability batch number is: year, month, and day plus the loading sequence number for that day. For example, 20260331001 represents the first vehicle on March 31, 2026. The control system packages all production process data for that vehicle under this traceability batch number. The packaged data includes the average instantaneous discharge rate of all batching bins during the loading period, the average moisture content of the material before humidification, the average actual humidification water volume, the final total loading weight, and the incoming material inspection values ​​for each batch of copper concentrate used. This data package is synchronously stored in a data table on the database server, establishing a retrieval structure indexed by the traceability batch number.

[0087] Operators can access the "Traceability Query" page on the control system's monitoring interface. Entering any traceability batch number in the search box will display a snapshot of the complete production data for that batch. For example, entering 20260331001 will show that the loading time for that batch was from 09:15 to 09:28 on March 31, 2026. During this period, the average actual material discharge from batch 1 was 36.1 t / h, batch 2 was 36.0 t / h, and batch 3 was 47.8 t / h. The average moisture content of the material before humidification was 5.6%, and the average actual humidification water volume was 3.3 t / h. The target total loading weight was 40.0 t, and the actual total loading weight was 40.02 t. The average copper grade of the batch used was 19.2%, the average sulfur content was 26.3%, and the average arsenic content was 0.09%. Operators can manually compare these data with the specifications on the shift's batching process card, which state that the batching capacity is 36 t / h for batching bin 1, 36 t / h for batching bin 2, 48 t / h for batching bin 3, the target moisture content is 8.5%, and the target loading volume is 40 t. The comparison results show that all deviations are within the allowable range. Simultaneously, operators can retrieve the opening curve of the hydraulic gate for this shipment, visually observing the complete process on the timeline from 20% pre-opening to 80% normal unloading, then decreasing to 20% at 95% total weight, and finally returning to zero.

[0088] This solution provides a simple and easy way to verify the effectiveness of the traceability function. After a week of continuous production, operators randomly select five vehicle license plate numbers from the weighbridge list printed at the weighbridge. They then enter the corresponding date and serial number on the traceability query page, verifying that the actual total weight displayed by the system matches the net weight on the weighbridge list. All five sets of data correspond correctly. Next, one vehicle is selected, and the average raw material ratio displayed by the system for that trip is compared with the target ratio set in the batching program for that shift. The discrepancy is immediately apparent. This solution uses second-level time stamps and vehicle-wide traceability batch numbers as the main thread, automatically linking, packaging, and storing multi-source heterogeneous online detection data and control execution data. This ensures that each finished product transport vehicle comes with a complete production process data archive, fundamentally changing the rudimentary management model of scattered manual records and lack of post-event traceability. It provides a reliable data foundation for accurate identification of quality problems and continuous process optimization.

[0089] In existing technologies, even with automatic data recording and traceability in copper concentrate blending production lines, the setting of process parameters still relies entirely on manual adjustments by technicians based on test reports and operational experience. For example, key parameters such as the batching ratio and humidification coefficient are often not updated for days or even weeks after being set, while the actual copper grade, sulfur content, and moisture content of the incoming material are constantly and slowly changing. This causes the various indicators of the finished product to gradually deviate from the optimal process window, and adjustments always lag behind changes in the incoming material, which is detrimental to the continuous stability of product quality.

[0090] To address the issues of lagging process parameter adjustments and inability to adapt to changes in incoming materials, this implementation adds a process parameter self-learning module to the control system's database server. This module automatically initiates a batch calculation task at the end of each shift, extracting all historical production data from the past seven consecutive natural days as analysis samples. The theoretical duration of seven natural days is 168 hours, with only data from the effective production periods being statistically analyzed. This data includes the actual instantaneous discharge records of the metering belt conveyors corresponding to each batching bin, the material moisture content before humidification measured by an online microwave moisture analyzer, the actual humidification water volume feedback from the electromagnetic flowmeter, and the finished product moisture content obtained from manual sampling and testing at the outlet of the humidifying mixer. The self-learning module first analyzes the proportioning deviation: it calculates the hourly average of the actual instantaneous discharge volume of each batching bin, then subtracts it from the corresponding hourly target discharge volume to obtain the hourly average deviation value. Finally, it calculates the arithmetic mean of the average deviation values ​​for all hours over the seven natural days to obtain the long-term deviation trend value for that batching bin. Assuming the long-term deviation trend of batching silo No. 1 is -0.5 t / h, indicating that the actual feed rate of this silo is consistently 0.5 t / h lower than the target value, the self-learning module automatically corrects the target feed rate of batching silo No. 1 to the original target value plus 0.5 t / h in its internal register and writes the correction value into the next shift's operating parameters in the formula parameter table. Similarly, the self-learning module adaptively optimizes the humidification coefficient by performing multiple linear regression on all measured material moisture content before humidification, actual humidification water volume, and finished product moisture content read from the database over seven natural days. It calculates the optimal humidification coefficient correction value that brings the average finished product moisture content close to the target value of 8.5% under the current fluctuating incoming material moisture content. This correction value is compared with the current preset humidification coefficient of 0.025 tons of water / ton of material. If the absolute value of the correction exceeds 0.002, i.e., the coefficient change exceeds 8%, the preset humidification coefficient is automatically updated to the correction value. The revised target feed amount and the new wet coefficient will take effect automatically when the next shift of production starts, without the need for manual intervention.

[0091] This solution allows operators and process managers to verify the actual effectiveness of the self-learning adjustment using simple statistical methods. By accessing the "Parameter Trend" page on the control system monitoring interface, line graphs showing the hourly average deviation values ​​of batching bins 1, 2, and 3 over the past ten shifts can be retrieved. Operators can clearly see that in the shifts before the self-learning function was implemented, the hourly average deviation value of batching bin 1 was generally distributed in the range of -0.3 to -0.7 t / h, with the line graph fluctuating continuously in the negative region. After the self-learning module automatically corrected the target value at shift handover, the line graph showing the hourly average deviation value of batching bin 1 in subsequent shifts shifted upwards, narrowing the distribution range to -0.2 to +0.2 t / h. Similarly, on the humidification effect trend page, the shift average change curve of the finished product moisture sample value can be viewed. Before the self-learning adjustment, the curve fluctuated between 8.0% and 8.3%, and after the adjustment, it stabilized in the range of 8.4% to 8.6%, more closely approaching the target value of 8.5%. Furthermore, process management personnel can access the operation logs from the learning module at any time. These logs detail the time each correction is triggered, the original parameter values ​​before the correction, the calculated correction value, and the new parameter values ​​after the correction. For example, a log might show that "the humidification coefficient was corrected from 0.025 to 0.0228" on a specific day and time. This record can be manually verified. Driven by actual historical production data, this solution periodically and automatically adjusts the batching and humidification parameters, ensuring that process control parameters continuously adapt to changes in incoming materials. This eliminates the lag and deviation caused by relying solely on periodic adjustments based on manual experience, contributing to the long-term stability of various finished product indicators.

[0092] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details.

Claims

1. A fully automated production method for blending copper concentrate, characterized in that, Includes the following steps: S1: Multi-grade copper concentrate is centrally unloaded by the unloading device and transported to the raw material silo by a closed belt conveyor; the belt conveyor is interlocked for forward and reverse start and stop, and is equipped with detection for deviation, blockage, tearing and overload. In case of abnormality, the entire line will be linked to stop and alarm. S2: The automatic stacker stacks materials in zones and layers according to a preset program, and evenly stacks different batches of raw materials by laying multiple layers flat and cross-laying. S3: The automatic material handling machine is linked with the stacking and batching system, and uses a reciprocating scraper to pick up materials, adjusting the material picking speed and walking frequency according to the production load; S4: The control system controls the material distribution equipment to feed the copper concentrate into the corresponding batching bins according to the grade and impurity parameters of each type of copper concentrate. S5: The control system controls each batching bin to simultaneously unload material onto the metering belt conveyor according to preset smelting process parameters, measures the material discharge amount in real time and adjusts the discharge speed to the preset ratio; the batching bins have automatic material level monitoring, automatic arch breaking, anti-blocking and pressure stabilization functions. S6: After proportioning, the materials are fed into the mixer via a belt conveyor. The mixer is linked with the front-end batching system, and the mixing speed and residence time are adapted according to the total flow of incoming materials. It also has automatic interlock protection against overload, material blockage, and idling. S7: After mixing, the material is sent into the humidifying mixer. The control system adjusts the amount of humidifying water according to the material moisture detection value and the current production capacity. S8: After humidification, the finished material is sent to the finished material silo, and is evenly fed into the silo by the finished material distribution equipment; S9: The finished product silo is transported and loaded onto trucks via the unloading gate and unloading chute; The start and stop of each piece of equipment is centrally controlled by the control system; the dust removal system is linked with the dust-generating equipment, starting synchronously and stopping with a delay, and the dust is uniformly returned to the batching system for recycling; the control system monitors equipment parameters, automatically alarms and protects against shutdown in case of abnormality, and stores the proportion, output and operating parameters.

2. The fully automated copper concentrate blending production method according to claim 1, characterized in that, In step S4, the control system, based on the grade and impurity parameters of each type of copper concentrate, controls the silo distribution equipment to feed each type of copper concentrate into its corresponding batching silo. Specifically, the control system pre-stores the correspondence between the silo number of each batching silo and the ranges of copper grade, sulfur content, and arsenic content values ​​of each type of copper concentrate. The control system acquires the copper grade, sulfur content, and arsenic content detection values ​​of the copper concentrate currently being conveyed by the enclosed belt conveyor, matches these values ​​with the ranges of copper grade, sulfur content, and arsenic content values ​​in each corresponding relationship, determines the target corresponding relationship that simultaneously meets the matching conditions, and determines the silo number of the target batching silo based on the target corresponding relationship. The control system then feeds the currently conveyed copper concentrate into the target batching silo.

3. The fully automated copper concentrate blending production method according to claim 1, characterized in that, In step S5, the control system, based on preset smelting process parameters, controls each batching bin to simultaneously unload material into the metering belt conveyor. The metering belt conveyor measures the discharge amount from each batching bin in real time and adjusts the discharge speed of each batching bin according to the measurement results, so that the discharge amount of each type of copper concentrate reaches the preset ratio. Specifically: The control system obtains the bin number of each batching bin and the target proportion percentage of the corresponding copper concentrate, and calculates the target instantaneous discharge amount of each batching bin based on the target proportion percentage and the total conveying capacity of each metering belt conveyor. Each batching bin is equipped with a metering belt conveyor. Each metering belt conveyor is equipped with a weighing sensor and a speed sensor. The weighing sensor measures the instantaneous weight of the material on the corresponding metering belt conveyor, and the speed sensor measures the belt running speed of the corresponding metering belt conveyor. The control system calculates the actual instantaneous discharge amount of the corresponding batching bin based on the instantaneous weight value of the material and the belt running speed value of each metering belt conveyor. It performs moving average processing on the time series data of the actual instantaneous discharge amount with a preset time window length to obtain the moving average discharge amount. It compares each moving average discharge amount with the corresponding target instantaneous discharge amount. Based on the comparison results, it independently adjusts the operating frequency of the discharge valve of each batching bin through the frequency converter so that each moving average discharge amount approaches the corresponding target instantaneous discharge amount. During the simultaneous unloading process of multiple compartments, when the deviation between the sliding average discharge amount and the target instantaneous discharge amount of any batching compartment exceeds the preset deviation threshold, the control system keeps the operating frequency of the unloading valves of other batching compartments unchanged and only adjusts the operating frequency of the unloading valve whose deviation exceeds the preset deviation threshold.

4. The fully automated copper concentrate blending production method according to claim 1, characterized in that, In step S7, the control system adjusts the humidification water volume of the spray device based on the detected moisture content of the material and the current production capacity, specifically as follows: An online moisture detector is installed at the inlet of the humidifying mixer. The online moisture detector measures the actual moisture content of the material before it enters the humidifying mixer and sends it to the control system. The control system acquires the current production capacity value, calculates the baseline humidification water volume value based on the current production capacity value and the preset humidification coefficient, and corrects the baseline humidification water volume value based on the difference between the preset baseline moisture content value and the measured moisture content value to obtain the target humidification water volume value. The control system controls the opening of the flow regulating valve of the spray device according to the target humidification water volume value, so that the actual humidification water volume value of the spray device reaches the target humidification water volume value. The preset humidification coefficient is the amount of water required per ton of material to increase the material's moisture content from the preset baseline moisture content to the preset target moisture content. The preset baseline moisture content is the nominal value of the incoming material's moisture content, which, under calibration conditions, is equal to the preset target moisture content value minus the product of the preset humidification coefficient and the amount of material per ton.

5. The fully automated copper concentrate blending production method according to claim 4, characterized in that, In step S7, a second online moisture detector is installed at the outlet of the humidifying mixer. The second online moisture detector measures the measured value of the moisture content of the humidified material discharged from the humidifying mixer and sends it to the control system. The control system has a preset allowable range of humidification deviation. The control system compares the measured value of the moisture content of the humidified material measured by the second online moisture detector with the preset target moisture content value to obtain the moisture deviation value after humidification. When the moisture deviation value after humidification exceeds the allowable range of humidification deviation, the control system corrects the preset humidification coefficient based on the moisture deviation value after humidification, obtains the corrected humidification coefficient, and replaces the preset humidification coefficient with the corrected humidification coefficient for the calculation of the reference humidification water volume value.

6. The fully automated copper concentrate blending production method according to claim 5, characterized in that, In step S7, the control system corrects the preset humidification coefficient based on the moisture deviation value after humidification to obtain the corrected humidification coefficient, specifically as follows: The control system has a preset upper limit for the single correction amplitude; The control system calculates the initial correction amount based on the moisture deviation value after humidification. The initial correction amount is the correction increment to the preset humidification coefficient. The control system compares the absolute value of the initial correction with the upper limit of the single correction amplitude; When the absolute value of the initial correction amount is less than or equal to the upper limit of the single correction amplitude, the control system uses the initial correction amount as the final correction amount to correct the preset humidification coefficient and obtain the corrected humidification coefficient. When the absolute value of the initial correction is greater than the upper limit of the single correction amplitude, the control system uses the upper limit of the single correction amplitude as the absolute value of the final correction and uses the sign of the initial correction as the sign of the final correction to obtain the final correction. The preset humidification coefficient is then corrected using the final correction to obtain the corrected humidification coefficient.

7. The fully automated copper concentrate blending production method according to claim 6, characterized in that, In step S7, the control system calculates an initial correction amount based on the moisture deviation value after humidification. The initial correction amount is the correction increment for the preset humidification coefficient, specifically: The control system records the moisture deviation values ​​after humidification acquired in the last two times, and subtracts the moisture deviation value after humidification from the moisture deviation value after humidification at the current moment to obtain the moisture deviation change rate. The control system has a pre-stored dynamic calculation model for the initial correction amount. The initial correction amount dynamic calculation model takes the moisture deviation value and the rate of change of moisture deviation after humidification as inputs and the correction increment of the preset humidification coefficient as output. This correction increment is used as the aforementioned initial correction amount for comparison with the upper limit of the single correction amplitude. The dynamic calculation model for the initial correction amount is configured as follows: The dynamic adjustment start threshold is less than or equal to the allowable range of humidification deviation; when the absolute value of the moisture deviation value after humidification is greater than the preset dynamic adjustment start threshold, and the rate of change of moisture deviation has the same sign as the moisture deviation value after humidification, the absolute value of the output correction increment is greater than the absolute value of the reference ratio correction amount. The absolute value of the reference ratio correction amount is the value obtained by multiplying the absolute value of the moisture deviation value after humidification by the preset reference ratio coefficient. When the absolute value of the moisture deviation after humidification is greater than the preset dynamic adjustment start threshold, and the rate of change of moisture deviation is opposite in sign to the moisture deviation after humidification, the absolute value of the output correction increment is less than the absolute value of the reference proportional correction.

8. The fully automated copper concentrate blending production method according to claim 1, characterized in that, Spray dust suppression devices are installed above the enclosed belt conveyor, at the feed inlet and discharge outlet of the raw material silo, at the feed inlet and discharge outlet of each batching silo, at the feed inlet of the mixer, at the feed inlet of the humidifying mixer, and at the feed inlet of the finished product silo. The start and stop of each spray dust suppression device are independently controlled by the control system. The control system has a pre-stored correspondence between the location numbers of each spray dust suppression device and the numbers of each process step; When the control system executes step S1, it activates the spray dust suppression device located above the enclosed belt conveyor. When the control system executes step S2, it activates the spray dust suppression device located at the feed inlet of the raw material silo. When the control system executes step S3, it activates the spray dust suppression device located at the discharge port of the raw material silo. When the control system executes step S4, it activates the spray dust suppression device located at the feed inlet of each batching bin. When the control system executes step S5, it activates the spray dust suppression device located at the discharge port of each batching bin. When the control system executes step S6, it activates the spray dust suppression device located at the feed inlet of the mixer; When the control system executes step S7, it activates the spray dust suppression device located at the feed inlet of the humidifying mixer; When the control system executes step S8, it activates the spray dust suppression device located at the feed inlet of the finished product silo; when the control system stops executing the corresponding step, it shuts down the spray dust suppression device corresponding to that step.

9. The fully automated copper concentrate blending production method according to claim 1, characterized in that, After step S5 and before step S6, during the conveying process of the mixed material into the mixer via the belt conveyor, a metal detector is installed on the belt conveyor to detect metal foreign objects in the mixed material on the belt conveyor. The control system acquires the detection signal from the metal detector. When the detection signal indicates the presence of metal foreign objects in the mixed material, the control system records the detection time point of the metal foreign object detected by the metal detector. Based on the detection time point, the running speed of the belt conveyor, and the distance along the material conveying path from the metal detector to the mixer inlet, the control system calculates the arrival time point of the metal foreign object at the mixer inlet. Based on the arrival time point, the control system controls the belt conveyor to stop running and issues an alarm signal after the belt conveyor stops running.

10. The fully automated production method for blending copper concentrate according to claim 9, characterized in that, The control system calculates the arrival time of the metal foreign object at the mixer inlet based on the detection time, the operating speed of the belt conveyor, and the distance along the material conveying path from the metal detector to the mixer inlet. Specifically: The control system acquires the operating speed value of the belt conveyor; The control system acquires the first distance value between the installation position of the metal detector on the belt conveyor and the unloading end of the belt conveyor; The control system calculates the first conveying time value based on the first distance value and the running speed value; The control system calculates the first arrival time of the metallic foreign object at the unloading end based on the detection time point and the first conveying time value. The control system acquires a second distance value between the discharge end of the belt conveyor and the feed inlet of the mixer. The second distance value is the path length along the material conveying path between the discharge end of the belt conveyor and the feed inlet of the mixer. The control system calculates the second conveying time value based on the second distance value and the running speed value; The control system calculates the arrival time of the metal foreign object at the mixer inlet based on the first arrival time and the second conveying time value.

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