On-line monitoring platform and method for multiple parameters of grinding and separation process in ore dressing plant

Abstract

This invention belongs to the field of mining automation and intelligent monitoring technology. It discloses a multi-parameter online monitoring platform and method for the grinding and beneficiation process in a mineral processing plant, including: collecting equipment operating parameters and material flow data; combining this with ore physical property detection values ​​to calculate real-time load index and capacity margin; dynamically dividing the crushing ratios of the coarse, medium, and fine crushing stages to determine the target discharge particle size range and generate a crushing ratio allocation vector; identifying pre-diversion nodes, determining pre-screening separation points and dry waste disposal trigger conditions to obtain material diversion path identifiers; performing coordinated adjustment to generate a set of equipment coordinated control parameters; distributing these parameters to each crushing device to monitor the oversize return ratio in real time; and recalculating the crushing ratio allocation vector and updating the equipment coordinated control parameter set when the return ratio exceeds a preset threshold. This significantly improves the overall efficiency and energy-saving level of the crushing system.

Description

Technical Field

[0001] This invention relates to the field of mining automation and intelligent monitoring technology, and more specifically, to a multi-parameter online monitoring platform and method for grinding and beneficiation processes in mineral processing plants. Background Technology

[0003] While traditional crushing and screening processes are technically mature, long-term production practice has revealed inefficiencies, high energy consumption, insufficient automation, and poor production stability. Unscientific equipment selection and capacity matching between different crushing stages lead to an unbalanced production process, with some equipment overloaded while others are idle. The overall system capacity fails to reach its design maximum, resulting in an unreasonable crushing ratio distribution and an imbalance between coarse, medium, and fine crushing tasks. This leads to uneven product particle size, low pass rates, and increased load and cost for subsequent grinding processes. Crushing is a high-energy-consuming stage in mining production, and the large amount of ineffective crushing further exacerbates energy waste. Furthermore, existing systems struggle to optimize for fluctuations in ore properties, resulting in unstable production efficiency and product quality.

[0004] In view of this, the present invention proposes an online monitoring platform and method for multiple parameters of the grinding and beneficiation process in mineral processing plants to solve the above problems. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a method for online monitoring of multiple parameters in the grinding and beneficiation process of a mineral processing plant, comprising:

[0006] Step 1: Collect the operating parameters and material flow data of each section of the crushing production line, and combine them with the test values ​​of the physical properties of the ore to calculate the real-time load index and capacity margin of each crushing section.

[0007] Step 2: Based on the real-time load index and capacity margin, dynamically divide the crushing ratio of the coarse crushing section, medium crushing section, and fine crushing section, determine the target discharge particle size range for each section, and generate a crushing ratio allocation vector.

[0008] Step 3: Based on the crushing ratio distribution vector and the particle size distribution characteristics of the material, identify the pre-diversion node, determine the pre-screening separation point and the dry waste disposal triggering condition, and obtain the material diversion path identifier;

[0009] Step 4: Based on the material diversion path identification and equipment operating parameters, coordinate the feeding speed and discharge port size of each crushing device to generate a set of equipment coordinated control parameters;

[0010] Step 5: Distribute the equipment collaborative control parameter set to each crushing device, monitor the oversize return ratio in the closed-loop cycle in real time, and when the return ratio exceeds the preset threshold, recalculate the crushing ratio allocation vector and update the equipment collaborative control parameter set.

[0011] An online monitoring platform for multiple parameters of the grinding and beneficiation process in a mineral processing plant, including:

[0012] Data acquisition module: Collects operating parameters and material flow data of equipment in each section of the crushing production line, and calculates the real-time load index and capacity margin of each crushing section by combining the test values ​​of ore physical properties.

[0013] Dynamic partitioning module: Based on the real-time load index and capacity margin, the crushing ratio of coarse crushing, medium crushing and fine crushing is dynamically partitioned, the target discharge particle size range of each section is determined, and a crushing ratio allocation vector is generated.

[0014] Diversion Identification Module: Based on the crushing ratio distribution vector and material particle size distribution characteristics, it identifies the upstream diversion node, determines the pre-screening separation point and the dry waste disposal triggering condition, and obtains the material diversion path identification;

[0015] Parameter determination module: Based on the material diversion path identifier and equipment operating parameters, the feeding speed and discharge port size of each crushing equipment are coordinated and adjusted to generate a set of equipment coordinated control parameters;

[0016] Control and monitoring module: Distributes the set of equipment collaborative control parameters to each crushing device, monitors the proportion of material returned to the screen in the closed loop in real time, and recalculates the crushing ratio allocation vector and updates the set of equipment collaborative control parameters when the proportion of material returned exceeds the preset threshold.

[0017] The technical effects and advantages of the online monitoring method for multiple parameters in the grinding and beneficiation process of the present invention are as follows:

[0018] This invention dynamically divides the crushing ratios of coarse, medium, and fine crushing stages based on real-time load indices and capacity margins, generating a crushing ratio allocation vector. This allows for adaptive allocation of crushing tasks to each stage based on the actual load capacity of the equipment, avoiding overload and idleness issues caused by fixed crushing ratios, thus achieving a balanced production process. Based on the crushing ratio allocation vector and material particle size distribution characteristics, it identifies pre-diversion nodes, determines pre-screening separation points and dry waste disposal trigger conditions, enabling early separation of materials that have reached the required particle size and timely removal of worthless waste rock, reducing ineffective crushing operations and effectively lowering energy consumption in the crushing process. Furthermore, it adjusts the feeding speed and discharge rate of each crushing device according to material diversion path identification and equipment operating parameters. The feed inlet size is adjusted in a coordinated manner to achieve linkage control between upstream and downstream equipment, ensuring matching of equipment capacity in each section and improving the overall capacity utilization and operating efficiency of the system. By monitoring the oversize return ratio in the closed-loop cycle in real time, when the return ratio exceeds the preset threshold, the crushing ratio allocation vector is recalculated and the equipment collaborative control parameter set is updated, realizing dynamic response and closed-loop feedback control to ore property fluctuations, ensuring product particle size uniformity and stable pass rate, and reducing the load and cost of subsequent grinding processes. This invention solves the problems of insufficient automation and poor production stability in traditional crushing and screening processes through multi-parameter online monitoring and dynamic collaborative control mechanisms, significantly improving the overall efficiency and energy saving level of the crushing system. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the online monitoring method for multiple parameters in the grinding and beneficiation process of a mineral processing plant according to the present invention;

[0020] Figure 2 This is a schematic diagram of the online monitoring platform for multiple parameters of the grinding and beneficiation process in a mineral processing plant according to the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example 1

[0023] Please see Figure 1 As shown in this embodiment, the online monitoring method for multiple parameters of the grinding and beneficiation process in a mineral processing plant includes:

[0024] Step S1: Collect the operating parameters and material flow data of each section of the crushing production line, and combine them with the physical property test values ​​of the ore to calculate the real-time load index and capacity margin of each crushing section.

[0025] Mineral resource crushing is a crucial step in mineral processing. Crushing production lines typically consist of three main stages: coarse crushing, medium crushing, and fine crushing. These stages are interconnected by conveying equipment to form a continuous material handling process. Traditional crushing and screening processes have revealed problems of low system efficiency and high energy consumption in long-term production practice. The main reason is the unscientific matching of equipment selection and capacity between different crushing stages, leading to overloaded equipment and idle equipment. Therefore, it is necessary to collect real-time operating status data of equipment in each crushing stage to accurately assess the load level and capacity margin of each stage, providing a data foundation for subsequent dynamic allocation of crushing ratios.

[0026] In this embodiment, the physical properties of the ore are measured as follows: ore hardness grade, moisture content, raw ore particle size distribution range, and magnetic strength classification. The ore hardness grade is determined using the Protodyakonov hardness coefficient f, and is divided into four grades: soft rock (f<4), medium-hard rock (4≤f<8), hard rock (8≤f<12), and extremely hard rock (f≥12). Moisture content is measured in real-time at the feed end using an infrared moisture analyzer with an accuracy of ±0.5%. The raw ore particle size distribution range is obtained using a laser particle size analyzer installed at the feed inlet, with a detection range of 0mm to 800mm. Magnetic strength classification is determined using a magnetic separator, and is divided into four grades: strong magnetic, medium magnetic, weak magnetic, and non-magnetic.

[0027] Operating parameters include: equipment operating current, spindle speed, discharge port opening, and equipment temperature. The operating current is collected by a current transformer installed in the motor control cabinet, with a sampling frequency of 10Hz. The spindle speed is detected by a rotary encoder installed at the end of the spindle. The discharge port opening is measured by a displacement sensor installed on the discharge port adjustment mechanism, with a measurement accuracy of ±0.1mm. The equipment temperature is detected by thermocouple sensors installed in the bearing housing and lubrication oil tank, with a detection accuracy of ±0.5℃.

[0028] It should be noted that this embodiment uses an industrial data acquisition gateway to uniformly collect the aforementioned sensor data, with an acquisition cycle set to 1 second to ensure data real-time performance and synchronization. In other embodiments, a PLC controller or a distributed control system (DCS) can also be used for data acquisition; the implementer can choose an appropriate data acquisition method based on the actual site conditions.

[0029] Preferably, in some possible implementations of the embodiments of the present invention, the methods for obtaining the real-time load index and capacity margin include:

[0030] Read the instantaneous operating current and rated current of each crushing section's equipment, and calculate the ratio between the two as the current load factor. The current load factor reflects the power consumption level of the equipment; the closer the current load factor is to 1, the closer the equipment is to full-load operation.

[0031] Simultaneously, the vibration amplitude of the equipment is read and compared with the preset safe vibration threshold to calculate the vibration occupancy rate. The vibration occupancy rate is equal to the ratio of the measured vibration amplitude to the safe vibration threshold. Equipment vibration is an important indicator reflecting the health and load status of the equipment. When the material hardness is high or the feeding is uneven, the equipment vibration amplitude will increase significantly. In this embodiment, the safe vibration threshold for the jaw crusher is set to 8 mm / s, and the safe vibration threshold for the cone crusher is set to 6 mm / s. These thresholds are determined according to the technical specifications provided by the equipment manufacturer. For example, if the measured vibration amplitude of a certain medium-sized cone crusher is 4.2 mm / s, then the vibration occupancy rate is 4.2 / 6 = 0.7.

[0032] The current load rate and vibration occupancy rate are weighted and combined to obtain the real-time load index for each fracture section. In this embodiment of the invention, the formula for calculating the real-time load index is: In the formula, For the first Real-time load index of each broken section; For the first Instantaneous operating current of each crushing section equipment; The rated current of the equipment; For the first The measured vibration amplitude of each crushing section equipment; The safe vibration threshold; and These are the weighting coefficients, and the sum of the weighting coefficients satisfies the condition that is 1.

[0033] The weighting coefficients are preset according to the equipment type: for jaw crushers, due to their working characteristics, the current fluctuation is relatively large, so the weighting coefficients are set accordingly. It is 0.6. The value is 0.4; for cone crushers, because their vibration characteristics are more sensitive to load response, the setting is... It is 0.5. The value is 0.5; for high-pressure roller mills, the value is set to 0.5. It is 0.7. The weighting factor is 0.3. This weighting factor is set based on the differences in the sensitivity of various crushing equipment to changes in current and vibration under different load conditions.

[0034] The design capacity and current actual throughput of each crushing section are read, and the difference between the design capacity and the actual throughput is calculated. The ratio of this difference to the design capacity is used as the capacity margin. The capacity margin ranges from [0,1]. When the capacity margin is close to 0, it indicates that the equipment is operating at near full capacity with almost no capacity reserve. When the capacity margin is close to 1, it indicates that the equipment has a large capacity reserve. For example, if the design capacity of a cone crusher in a medium-sized crushing section is 600 tons per hour, and the current actual throughput is 420 tons per hour, then the capacity margin is (600-420) / 600=0.3, indicating that the equipment still has 30% capacity reserve available for allocation.

[0035] It should be noted that when the capacity margin is negative, it indicates that the actual processing volume has exceeded the designed capacity, and the equipment is in an overload state. In this case, measures such as reducing the feeding speed should be taken immediately to protect the equipment. In this embodiment, the lower limit of the capacity margin is set to -0.1. When the capacity margin is less than -0.1, the overload protection mechanism is triggered.

[0036] Step S2: Based on the real-time load index and capacity margin, dynamically divide the crushing ratios of the coarse crushing section, medium crushing section, and fine crushing section, determine the target discharge particle size range for each section, and generate a crushing ratio allocation vector.

[0037] Traditional crushing processes employ fixed crushing ratio allocation schemes, which cannot be optimized and adjusted according to fluctuations in ore properties and changes in equipment operating conditions. This leads to unreasonable crushing ratio allocation and an imbalance in coarse, medium, and fine crushing tasks. When a certain crushing section is overloaded, it can easily cause equipment overload damage and energy waste; conversely, when a certain crushing section is underloaded, it will result in wasted production capacity. Therefore, it is necessary to dynamically adjust the crushing ratio of each section based on the real-time load index and capacity margin of each section to ensure that the overall system operates in an optimal state.

[0038] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the breakage ratio allocation vector includes:

[0039] First, based on the ore hardness grade, consult the preset crushing ratio benchmark table to obtain the benchmark crushing ratios for coarse, medium, and fine crushing stages. The crushing ratio benchmark table is preset based on the ore hardness and the process characteristics of the crushing equipment, as shown in the table below:

[0040] Ore hardness grade Coarse crushing section benchmark crushing ratio medium-sized crushing ratio Fine segment benchmark crushing ratio Soft rock (f<4) 5.0 4.0 3.0 Medium-hard rock (4 ≤ f < 8) 4.5 4.5 3.5 Hard rock (8≤f<12) 4.0 5.0 4.0 Extremely hard rock (f≥12) 3.5 5.5 4.5

[0041] The above-mentioned benchmark crushing ratio is set based on rock hardness. For ores with lower hardness, the coarse crushing stage equipment has higher crushing efficiency and can handle a larger crushing ratio. For ores with higher hardness, more crushing tasks need to be allocated to the medium and fine crushing stages to avoid overloading the coarse crushing equipment.

[0042] Secondly, the real-time load index of each crushing section is read, and the crushing ratio is dynamically adjusted according to the load status. In this embodiment, the preset upper limit of load is set to 0.85, and the preset lower limit of load is set to 0.5. The basis for setting this value range is: when the load index exceeds 0.85, the equipment is close to full load operation, and further increasing the load will lead to the risk of equipment overload; when the load index is below 0.5, the equipment has a large amount of wasted capacity.

[0043] When the real-time load index of the coarse crushing stage exceeds the preset load limit of 0.85, it indicates that the coarse crushing stage equipment is overloaded. In this case, the crushing ratio of the coarse crushing stage should be reduced, and the crushing ratio of the medium crushing stage should be increased accordingly. The adjustment range is calculated according to the following formula: In the formula, This is the adjustment amount for the crushing ratio; This represents the real-time load index for the coarse-grained segment; The adjustment factor is taken as an empirical value of 2.0. For example, when the real-time load index of the coarse-grained segment is 0.92, the adjustment amount is... If the value is 0.14, then the crushing ratio of the coarse crushing section decreases by 0.14, and the crushing ratio of the medium crushing section increases by 0.14.

[0044] When the real-time load index of the coarse crushing stage is less than or equal to the preset upper load limit of 0.85 and greater than the preset lower load limit of 0.5, the benchmark crushing ratio between the coarse and medium crushing stages remains unchanged, and the system is in normal operation.

[0045] When the real-time load index of the coarse crushing stage is less than or equal to the preset lower load limit of 0.5, it indicates that the coarse crushing stage equipment is under light load, resulting in wasted capacity. In this case, the crushing ratio of the coarse crushing stage should be increased, and the crushing ratio of the medium crushing stage should be decreased accordingly. The adjustment range is calculated according to the following formula: ;in, For example, when the real-time load index of the coarse crushing section is 0.35, the adjustment amount is... If the value is 0.3, then the crushing ratio of the coarse crushing section increases by 0.3, and the crushing ratio of the medium crushing section decreases by 0.3.

[0046] It should be noted that the same adjustment logic is used for the medium crushing section and the fine crushing section. When the medium crushing section is overloaded, some crushing tasks are transferred to the fine crushing section. When the fine crushing section is overloaded, the feeding speed needs to be reduced or the crushing ratio of the upstream crushing section needs to be adjusted.

[0047] Then, the target discharge particle size range is calculated based on the adjusted crushing ratios for each stage. The formula for calculating the target discharge particle size range is: and In the formula, and These are the lower and upper limits of the target discharge particle size range, respectively; and These are the upper and lower limits of the feed particle size, respectively; The crushing ratio after adjustment of the crushing section; The particle size fluctuation coefficient is taken as an empirical value of 1.2.

[0048] The lower limit of the target discharge particle size range of the coarse crushing stage is used as the upper limit of the feed particle size of the medium crushing stage, and the lower limit of the target discharge particle size range of the medium crushing stage is used as the upper limit of the feed particle size of the fine crushing stage, so as to ensure that the particle size connection between each crushing stage is reasonable. Finally, the adjusted crushing ratio of each stage is combined and packaged with the corresponding target discharge particle size range to generate a crushing ratio allocation vector.

[0049] Step S3: Based on the crushing ratio distribution vector and the particle size distribution characteristics of the material, identify the pre-diversion node, determine the pre-screening separation point and the dry waste disposal triggering condition, and obtain the material diversion path identifier.

[0050] In traditional crushing processes, all materials must undergo processing through all crushing stages, resulting in the repeated crushing of a large amount of material that has already met the particle size requirements, leading to energy waste and increased equipment wear. Simultaneously, waste rock containing a large amount of gangue minerals also enters the entire process, increasing the load on subsequent mineral processing steps. Therefore, it is necessary to set up a pre-diversion node in the crushing process to separate qualified materials from the crushing process in advance and discard low-grade waste rock in a timely manner, thereby improving crushing efficiency, reducing energy consumption, and improving product quality.

[0051] Preferably, in some possible implementations of the embodiments of the present invention, the specific method for identifying the pre-diversion node, determining the pre-screening separation point and the dry waste disposal triggering condition, and obtaining the material diversion path identifier includes:

[0052] First, the particle size distribution range of the raw ore is detected at the feed end of the coarse crushing section. A laser particle size analyzer installed above the feed conveyor belt scans the material surface in real time to obtain particle size distribution data. The proportion of material smaller than the lower limit of the target discharge particle size range of the coarse crushing section is compared with a preset qualified particle size threshold.

[0053] In this embodiment, the preset qualified particle size threshold is set to 15%. The basis for this setting is that when the proportion of fine particles exceeds 15%, this part of the material will not only fail to be effectively crushed after entering the coarse crushing equipment, but will also be repeatedly squeezed along with the coarse particles, increasing the over-crushing rate. Therefore, it is necessary to separate them in advance.

[0054] When the proportion of this material exceeds the preset qualified particle size threshold by 15%, the feed end of the coarse crushing section is marked as a pre-screening separation point. After the pre-screening separation point is set, the system controls the diversion gate to divert materials smaller than the lower limit of the target discharge particle size range of the coarse crushing section to the bypass conveyor belt, which directly transports them to the medium or fine crushing section for processing. For example, if it is detected that the proportion of materials with a particle size smaller than 143mm in the raw ore is 22%, which is greater than the qualified particle size threshold of 15%, then a pre-screening separation point is set at the feed end of the coarse crushing section, and these 22% of fine particles are directly diverted to the medium crushing section.

[0055] When the proportion of material is less than or equal to 15% of the preset qualified particle size threshold, no pre-screening separation point is set, and all material enters the coarse crushing stage. At this time, the proportion of fine-grained material is small, and the economic benefits of pre-screening separation are insufficient to offset the cost of setting up diversion equipment.

[0056] Secondly, the magnetic strength of the material is assessed at the discharge end of the crushing section for classification. An online magnetic separator installed above the discharge conveyor belt is used to detect the magnetic characteristics of the material. For magnetic minerals such as magnetite, valuable minerals exhibit strong magnetism, while gangue minerals are typically non-magnetic or weakly magnetic. The proportion of material with magnetic strength below the preset lower limit for valuable minerals is compared with a preset waste disposal threshold.

[0057] In this embodiment, the lower limit of magnetic properties of valuable minerals is pre-calibrated according to the type of ore. For example, for magnetite, it is set to a specific magnetic susceptibility of 0.003. The preset waste disposal ratio threshold is set to 20%. The basis for setting this value is that when the proportion of low magnetic waste exceeds 20%, timely waste disposal can significantly reduce the load on the fine crushing stage and subsequent grinding and beneficiation processes.

[0058] When this proportion exceeds the preset waste disposal threshold of 20%, the discharge end of the medium-crushed section is marked as a dry waste disposal node. After the dry waste disposal node is set, the system starts the dry magnetic separator to separate the low-magnetic waste rock and transport it to the waste rock dump via a waste rock conveyor belt. For example, if it is detected that the proportion of material with magnetic strength lower than the lower limit of magnetic properties of valuable minerals in the medium-crushed section discharge is 28%, which is greater than the waste disposal threshold of 20%, then a dry waste disposal node is set at the discharge end of the medium-crushed section.

[0059] When this proportion is less than or equal to the preset waste disposal ratio threshold of 20%, no dry waste disposal node is set, and all materials continue to enter the fine crushing stage. At this time, the proportion of waste rock is low, and the benefits of dry waste disposal are not obvious.

[0060] Finally, based on the marking results of the pre-screening separation point and the dry waste disposal node, a material diversion path identifier is generated. The material diversion path identifier includes the location of the diversion node, the direction of the diverted material flow, and the subsequent processing section number of the diverted material. The data structure of the material diversion path identifier is as follows: ;in, Identify material distribution paths; The location of the pre-screening separation point is indicated by the number of the feed end of the coarse crushing section or a blank value. The value for the pre-screened and diverted material flow direction is either medium-sized or fine-sized. This is the number of the subsequent processing section for the material after pre-screening and diversion; The value represents the location of the dry waste disposal node, and can be either the discharge end number of the medium-sized crushing section or a blank value. The value is taken as the destination of the waste material; This is the number of the subsequent processing section for the remaining materials after waste disposal.

[0061] It should be noted that the pre-screening separation point and the dry waste disposal node are set independently of each other; they can be set simultaneously or only one of them can be set, depending on the particle size distribution and magnetic characteristics of the material. In other embodiments, the pre-screening separation point can also be set at the discharge end of the coarse crushing section, or the dry waste disposal node can be set at the discharge end of the fine crushing section. The implementer can adjust it according to the specific process flow.

[0062] Step S4: Based on the material diversion path identifier and equipment operating parameters, coordinate the feeding speed and discharge port size of each crushing device to generate a set of equipment coordinated control parameters.

[0063] The operating parameters of each crushing unit are interconnected. Adjusting the parameters of a single unit may lead to material accumulation or supply interruption in upstream and downstream units. Therefore, it is necessary to coordinate the adjustment of all equipment in the production line based on the material diversion path and the operating status of each unit to ensure the continuity and balance of material flow and achieve optimal overall system efficiency.

[0064] Preferably, in some possible implementations of the embodiments of the present invention, the process of generating the device cooperative control parameter set includes the following sub-steps:

[0065] Step S41: Read the current feeding speed and discharge port opening of each crushing device, and calculate the target discharge port opening by combining the target discharge particle size range of the corresponding segment in the crushing ratio allocation vector.

[0066] The discharge opening is a key parameter determining the particle size of the crushed product. A smaller opening results in finer output particles, but also increases equipment energy consumption and wear. The formula for calculating the target discharge opening is: In the formula, The target discharge port opening; The upper limit of the target discharge particle size range; This is the discharge opening coefficient, with a value of 0.85 for jaw crushers, 0.75 for cone crushers, and 0.90 for high-pressure roller mills. This coefficient is determined based on the statistical relationship between the discharge particle size and the discharge opening of various crushing equipment.

[0067] Step S42: Compare the target discharge port opening with the current discharge port opening and calculate the opening adjustment amount.

[0068] The difference between the target discharge port opening and the current discharge port opening is used as the opening adjustment amount. A positive value indicates that the opening needs to be increased, and a negative value indicates that the opening needs to be decreased. When the absolute value of the opening adjustment amount is greater than the preset single adjustment limit, the adjustment amount is limited to the preset single adjustment limit. In this embodiment, the preset single adjustment limit is set to 10mm. The basis for setting this value is that a large change in the discharge port opening will cause drastic fluctuations in the discharge particle size, affecting the stable operation of downstream equipment. Therefore, if the calculated opening adjustment amount is 15mm, the actual adjustment amount is limited to 10mm, and the remaining 5mm of adjustment is completed in the next adjustment cycle.

[0069] When the absolute value of the opening adjustment amount is less than or equal to the preset single adjustment limit of 10mm, the calculated opening adjustment amount is used directly.

[0070] Step S43: Read the direction of material flow at each diversion node according to the material diversion path identifier, estimate the amount of material entering the downstream crushing section after diversion, and calculate the target feeding speed in combination with the capacity margin of the downstream crushing section.

[0071] Because material diversion changes the actual feed rate in each crushing section, the target feed rate for each section needs to be recalculated based on the diversion situation. The process of determining the target feed rate includes:

[0072] First, read the current discharge flow rate of the upstream crushing section and the diversion ratio of the diversion node, and calculate the actual material flow rate entering the current crushing section after diversion as the expected feed flow rate. The formula for calculating the expected feed flow rate is: In the formula, This represents the expected feed flow rate. This represents the current discharge flow rate of the upstream crushing section; The diversion ratio is set to 0 if there is no diversion node. Next, the capacity margin and real-time load index of the current crushing section are read, and the target feeding speed is determined based on the equipment status. In this embodiment, the preset capacity margin threshold is set to 0.2, and the preset median load is set to 0.7.

[0073] When the capacity margin is greater than the preset sufficient threshold of 0.2 and the real-time load index is less than the preset load median of 0.7, it indicates that the equipment is operating well and has sufficient capacity margin, and the expected feed flow rate is directly used as the target feed speed.

[0074] When the capacity margin is less than or equal to the preset sufficient threshold of 0.2, or the real-time load index is greater than or equal to the preset load median of 0.7, it indicates that the equipment load is too heavy or the capacity margin is insufficient, and the expected feed flow rate needs to be reduced. The reduction factor is the ratio of the current crushing section's capacity margin to the preset sufficient threshold. The product of the reduction factor and the expected feed flow rate is used as the reduced flow rate and the target feed rate.

[0075] Finally, the target feeding speed is compared with the maximum allowable feeding speed of the equipment. When the target feeding speed is greater than the maximum feeding speed, the maximum feeding speed is used as the final target feeding speed to prevent equipment overload. When the target feeding speed is less than or equal to the maximum feeding speed, the calculated target feeding speed is directly used as the final target feeding speed.

[0076] Step S44: Summarize the target discharge port opening, opening adjustment amount, and target feeding speed of each crushing equipment to generate a set of equipment collaborative control parameters.

[0077] The set of parameters for equipment collaborative control includes the number of the crushing equipment, the target discharge port opening of the equipment, the opening adjustment amount of the equipment, the target feeding speed of the equipment, and the total number of crushing equipment.

[0078] Step S5: Distribute the set of equipment collaborative control parameters to each crushing device, monitor the proportion of material returned from the screen in the closed loop in real time, and when the proportion of material returned exceeds the preset threshold, recalculate the crushing ratio allocation vector and update the set of equipment collaborative control parameters.

[0079] After the set of equipment collaborative control parameters is generated, it needs to be distributed to each piece of equipment in a reasonable order for execution, and the execution effect needs to be monitored in real time. The oversize return ratio in the closed-loop cycle is an important indicator reflecting the crushing effect. If the return ratio is too high, it means that the particle size of the crushed product does not meet the requirements, and the equipment parameters need to be adjusted in time.

[0080] Preferably, in some possible implementations of the embodiments of the present invention, the process of issuing and executing the device collaborative control parameter set includes:

[0081] The set of equipment collaborative control parameters is split according to equipment number to generate independent control instructions for each crushing device. Each independent control instruction includes four fields: equipment number, target discharge port opening, opening adjustment amount, and target feed rate.

[0082] Independent control commands are issued sequentially according to the preset equipment response priority order. In this embodiment, the fine crushing equipment takes priority over the medium crushing equipment, and the medium crushing equipment takes priority over the coarse crushing equipment. This priority order is set based on the principle that adjusting from downstream to upstream can make room for material processing and avoid material accumulation in intermediate stages. For example, the discharge opening of the fine crushing cone crusher is adjusted first, then the medium crushing cone crusher is adjusted, and finally the feeding speed of the coarse crushing jaw crusher is adjusted.

[0083] The system monitors the response status of each device after receiving control commands. When a device completes parameter adjustment within a preset response time limit, the adjustment completion status is recorded, and monitoring continues for the next device. In this embodiment, the preset response time limit is set to 30 seconds, a value determined based on the response characteristics of the discharge port hydraulic adjustment mechanism and the feeder's frequency conversion speed regulation.

[0084] If the equipment fails to complete parameter adjustment within the preset response time limit of 30 seconds, the equipment number is recorded and the abnormal handling procedure is triggered. The abnormal handling procedure includes pausing the feeding of the equipment and sending a deceleration command to the upstream equipment to prevent material accumulation and equipment blockage. At the same time, the system generates an abnormal alarm message and pushes it to the operator in the central control room for manual intervention.

[0085] Preferably, in some possible implementations of the embodiments of the present invention, the monitoring and processing process of the over-screen return ratio in the closed-loop cycle includes:

[0086] The flow rates of oversize and undersize materials are collected at the screening equipment at the fine crushing section discharge end. Electronic belt scales installed on the oversize and undersize material conveyor belts monitor the flow rates of both materials in real time. The formula for calculating the oversize return ratio is: ;in, The proportion of material returned from the screen; This refers to the flow rate of material over the screen. This represents the flow rate of material passing through the screen.

[0087] The proportion of material returned from the screen is compared with the preset upper limit of the return proportion. In this embodiment, the preset upper limit of the return proportion is set to 35%. The basis for setting this value is that when the return proportion exceeds 35%, the effective production capacity of fine fragments will decrease significantly, and the equipment parameters need to be adjusted in time.

[0088] When the proportion of material returned to the screen is less than or equal to the preset upper limit of 35%, the current set of equipment collaborative control parameters remains unchanged and routine monitoring continues. At this time, the crushing effect meets the requirements, and the system is in normal operation.

[0089] When the proportion of material returned from the screen exceeds the preset upper limit of 35%, different adjustment strategies need to be selected based on the load status of the fine crushing equipment:

[0090] When the real-time load index of the fine crushing equipment is less than the preset upper load limit of 0.85, it indicates that the equipment still has a load margin. At this time, the discharge port opening of the fine crushing equipment should be reduced to decrease the discharge particle size. The amount of reduction in the discharge port opening is calculated according to the following formula: In the formula, The amount by which the discharge port opening is reduced; This represents the current percentage of material returned from the screen. To adjust the coefficient, an empirical value of 0.1 is used; The current discharge port opening. When the real-time load index of the fine crushing equipment is greater than or equal to the preset load limit of 0.85, it indicates that the equipment is close to full load. At this time, the feeding speed of the fine crushing section should be reduced to alleviate the load on the equipment. The reduction in feeding speed is calculated according to the following formula: In the formula, To reduce the amount of material fed at a lower speed; This represents the current feeding speed. Simultaneously, a speed reduction command is sent to the upstream intermediate crushing equipment to maintain the coordination of material flow.

[0091] Based on the above adjustments, the crushing ratio allocation vector is recalculated, and the equipment collaborative control parameter set is updated before being issued for execution. The updated parameter set needs to be re-executed according to the issuance process in step S5 to form closed-loop control.

[0092] It should be noted that the monitoring cycle in this embodiment is set to 5 seconds, meaning that the oversize return ratio data is collected every 5 seconds for judgment. In other embodiments, the monitoring cycle can be adjusted according to the response characteristics of the production line, generally ranging from 3 seconds to 10 seconds.

[0093] This embodiment solves the technical problems of unreasonable crushing ratio distribution, uneven equipment load, and high energy consumption in traditional crushing processes by real-time load monitoring and capacity margin analysis of each section of the crushing production line, identifying material diversion nodes to achieve pre-screening separation and dry waste disposal, coordinating equipment parameters and monitoring the return material ratio in a closed loop. It realizes intelligent operation and overall efficiency optimization of the crushing system, improves the product particle size qualification rate, and reduces the load and cost of subsequent grinding processes.

[0094] Example 2

[0095] Please see Figure 2 As shown, for parts not described in detail in this embodiment, please refer to the description in Embodiment 1. A multi-parameter online monitoring platform for the grinding and beneficiation process in a mineral processing plant is provided, including:

[0096] Data acquisition module: Collects operating parameters and material flow data of equipment in each section of the crushing production line, and calculates the real-time load index and capacity margin of each crushing section by combining the test values ​​of ore physical properties.

[0097] Dynamic partitioning module: Based on the real-time load index and capacity margin, the crushing ratio of coarse crushing, medium crushing and fine crushing is dynamically partitioned, the target discharge particle size range of each section is determined, and a crushing ratio allocation vector is generated.

[0098] Diversion Identification Module: Based on the crushing ratio distribution vector and material particle size distribution characteristics, it identifies the upstream diversion node, determines the pre-screening separation point and the dry waste disposal triggering condition, and obtains the material diversion path identification;

[0099] Parameter determination module: Based on the material diversion path identifier and equipment operating parameters, the feeding speed and discharge port size of each crushing equipment are coordinated and adjusted to generate a set of equipment coordinated control parameters;

[0100] Control and monitoring module: Distributes the set of equipment collaborative control parameters to each crushing device, monitors the proportion of material returned to the screen in the closed loop in real time, and recalculates the crushing ratio allocation vector and updates the set of equipment collaborative control parameters when the proportion of material returned exceeds the preset threshold.

[0101] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for online monitoring of multiple parameters in the grinding and beneficiation process of a mineral processing plant, characterized in that, include: Step 1: Collect the operating parameters and material flow data of each section of the crushing production line, and combine them with the test values ​​of the physical properties of the ore to calculate the real-time load index and capacity margin of each crushing section. Step 2: Based on the real-time load index and capacity margin, dynamically divide the crushing ratio of the coarse crushing section, medium crushing section, and fine crushing section, determine the target discharge particle size range for each section, and generate a crushing ratio allocation vector. Step 3: Based on the crushing ratio distribution vector and the particle size distribution characteristics of the material, identify the pre-diversion node, determine the pre-screening separation point and the dry waste disposal triggering condition, and obtain the material diversion path identifier; Step 4: Based on the material diversion path identification and equipment operating parameters, coordinate the feeding speed and discharge port size of each crushing device to generate a set of equipment coordinated control parameters; Step 5: Distribute the equipment collaborative control parameter set to each crushing device, monitor the oversize return ratio in the closed-loop cycle in real time, and when the return ratio exceeds the preset threshold, recalculate the crushing ratio allocation vector and update the equipment collaborative control parameter set.

2. The online monitoring method for multiple parameters of the grinding and beneficiation process in a mineral processing plant according to claim 1, characterized in that, The physical properties of the ore include: ore hardness grade, moisture content, raw ore particle size distribution range, and magnetic strength grading. Operating parameters include: equipment operating current, spindle speed, discharge port opening, and equipment temperature.

3. The online monitoring method for multiple parameters of the grinding and beneficiation process in a mineral processing plant according to claim 1, characterized in that, The methods for obtaining real-time load index and capacity margin include: Read the instantaneous operating current and rated current of each crushing section equipment, calculate the ratio of the two as the current load rate, and simultaneously read the equipment vibration amplitude and preset safe vibration threshold to calculate the vibration occupancy rate; weight the current load rate and vibration occupancy rate to obtain the real-time load index of each crushing section, where the weighting coefficient is preset according to the equipment type; read the design capacity and current actual processing volume of each crushing section, calculate the difference between the design capacity and the actual processing volume, and use the ratio of the difference to the design capacity as the capacity margin.

4. The online monitoring method for multiple parameters of the grinding and beneficiation process in a mineral processing plant according to claim 1, characterized in that, The methods for obtaining the breakage ratio allocation vector include: Based on the ore hardness grade, consult the preset crushing ratio benchmark table to obtain the benchmark crushing ratios for coarse, medium, and fine crushing stages; Read the real-time load index of each crushing section. When the real-time load index of the coarse crushing section is greater than the preset load upper limit, reduce the crushing ratio of the coarse crushing section and increase the crushing ratio of the medium crushing section accordingly. When the real-time load index of the coarse crushing section is less than or equal to the preset load upper limit and greater than the preset load lower limit, maintain the benchmark crushing ratio of the coarse and medium crushing sections unchanged. When the real-time load index of the coarse crushing section is less than or equal to the preset load lower limit, increase the crushing ratio of the coarse crushing section and decrease the crushing ratio of the medium crushing section accordingly. Calculate the corresponding target discharge particle size range based on the adjusted crushing ratio of each stage. Take the lower limit of the target discharge particle size range of the coarse crushing stage as the upper limit of the feed particle size of the medium crushing stage, and take the lower limit of the target discharge particle size range of the medium crushing stage as the upper limit of the feed particle size of the fine crushing stage. The adjusted crushing ratios of each segment are combined and packaged with the corresponding target output particle size ranges to generate a crushing ratio allocation vector.

5. The online monitoring method for multiple parameters of the grinding and beneficiation process in a mineral processing plant according to claim 1, characterized in that, Identify the pre-diversion node, determine the pre-screening separation point and the dry waste disposal triggering condition, and obtain the material diversion path identifier, including: The particle size distribution range of the raw ore is detected at the feed end of the coarse crushing section. The proportion of material smaller than the lower limit of the target discharge particle size range of the coarse crushing section is compared with the preset qualified particle size threshold. When the proportion of the material is greater than the preset qualified particle size threshold, the feed end of the coarse crushing section is marked as a pre-screening separation point. When the proportion of the material is less than or equal to the preset qualified particle size threshold, no pre-screening separation point is set and all the material enters the coarse crushing section. The magnetic strength of the material is detected and classified at the discharge end of the medium crushing section. The proportion of material with magnetic strength lower than the preset lower limit of magnetic strength of valuable minerals is compared with the preset waste disposal ratio threshold. When the proportion is greater than the preset waste disposal ratio threshold, the discharge end of the medium crushing section is marked as a dry waste disposal node. When the proportion is less than or equal to the preset waste disposal ratio threshold, no dry waste disposal node is set and all material continues to enter the fine crushing section. Based on the marking results of the pre-screening separation point and the dry waste disposal node, a material diversion path identifier is generated. The material diversion path identifier includes the location of the diversion node, the direction of the diverted material flow, and the subsequent processing section number of the diverted material.

6. The online monitoring method for multiple parameters of the grinding and beneficiation process in a mineral processing plant according to claim 5, characterized in that, Step 4 specifically includes: Step 41: Read the current feeding speed and discharge port opening of each crushing device, and calculate the target discharge port opening by combining the target discharge particle size range of the corresponding segment in the crushing ratio allocation vector. Step 42: Compare the target discharge port opening with the current discharge port opening and calculate the opening adjustment amount. When the opening adjustment amount is greater than the preset single adjustment limit, limit the adjustment amount to the preset single adjustment limit. When the opening adjustment amount is less than or equal to the preset single adjustment limit, directly use the calculated opening adjustment amount. Step 43: Read the direction of material flow at each diversion node according to the material diversion path identifier, estimate the amount of material entering the downstream crushing section after diversion, and calculate the target feeding speed in combination with the capacity margin of the downstream crushing section. Step 44: Summarize the target discharge port opening, opening adjustment amount, and target feeding speed of each crushing device to generate a set of equipment collaborative control parameters.

7. The online monitoring method for multiple parameters of the grinding and beneficiation process in a mineral processing plant according to claim 1, characterized in that, The process of issuing and executing the equipment collaborative control parameter set includes: The set of equipment collaborative control parameters is split according to equipment number to generate independent control commands for each crushing equipment. Independent control commands are issued sequentially according to the preset equipment response priority, with fine crushing equipment taking priority over medium crushing equipment, and medium crushing equipment taking priority over coarse crushing equipment. The response status of each equipment after receiving the control command is monitored. When the equipment completes the parameter adjustment within the preset response time limit, the adjustment completion status is recorded and the monitoring of the next equipment continues. When the equipment fails to complete the parameter adjustment within the preset response time limit, the equipment number is recorded and an abnormal handling process is triggered. The abnormal handling process includes suspending the feeding of the equipment and sending a deceleration command to the upstream equipment.

8. The online monitoring method for multiple parameters of the grinding and beneficiation process in a mineral processing plant according to claim 1, characterized in that, The monitoring and handling process for the proportion of oversize return material in a closed-loop cycle includes: The flow rates of material on the screen and material under the screen are collected at the screening equipment at the discharge end of the fine crushing section. The ratio of the flow rate of material on the screen to the total flow rate is calculated as the proportion of material returned from the screen. The oversize return ratio is compared with the preset upper limit of the return ratio. When the oversize return ratio is less than or equal to the preset upper limit of the return ratio, the current set of equipment collaborative control parameters remains unchanged and routine monitoring continues. When the proportion of material returned from the screen is greater than the preset upper limit of the return proportion, the real-time load index of the fine crushing equipment is read. When the real-time load index of the fine crushing equipment is less than the preset upper limit of the load, the opening of the discharge port of the fine crushing equipment is reduced. When the real-time load index of the fine crushing equipment is greater than or equal to the preset upper limit of the load, the feeding speed of the fine crushing equipment is reduced. After adjusting and recalculating the crushing ratio allocation vector, updating the equipment collaborative control parameter set, and then issuing the command for execution.

9. The online monitoring method for multiple parameters of the grinding and beneficiation process in a mineral processing plant according to claim 6, characterized in that, The process of determining the target feed rate includes: Read the current discharge flow rate of the upstream crushing section and the diversion ratio of the diversion node, and calculate the actual material flow rate entering the current crushing section after diversion as the expected feed flow rate; The capacity margin and real-time load index of the current crushing section are read. When the capacity margin is greater than the preset sufficient threshold and the real-time load index is less than the preset load median, the expected feed flow rate is used as the target feed rate. When the capacity margin is less than or equal to the preset sufficient threshold or the real-time load index is greater than or equal to the preset load median, the expected feed flow rate is reduced according to the ratio of the capacity margin to the preset sufficient threshold, and the reduced flow rate is used as the target feed rate. The target feeding speed is compared with the maximum feeding speed allowed by the equipment. When the target feeding speed is greater than the maximum feeding speed, the maximum feeding speed is used as the final target feeding speed. When the target feeding speed is less than or equal to the maximum feeding speed, the calculated target feeding speed is directly used as the final target feeding speed.

10. A multi-parameter online monitoring platform for the grinding and beneficiation process in a mineral processing plant, used to implement the multi-parameter online monitoring method for the grinding and beneficiation process in a mineral processing plant as described in any one of claims 1 to 9, characterized in that, include: Data acquisition module: Collects operating parameters and material flow data of equipment in each section of the crushing production line, and calculates the real-time load index and capacity margin of each crushing section by combining the test values ​​of ore physical properties. Dynamic partitioning module: Based on the real-time load index and capacity margin, the crushing ratio of coarse crushing, medium crushing and fine crushing is dynamically partitioned, the target discharge particle size range of each section is determined, and a crushing ratio allocation vector is generated. Diversion Identification Module: Based on the crushing ratio distribution vector and material particle size distribution characteristics, it identifies the upstream diversion node, determines the pre-screening separation point and the dry waste disposal triggering condition, and obtains the material diversion path identification; Parameter determination module: Based on the material diversion path identifier and equipment operating parameters, the feeding speed and discharge port size of each crushing equipment are coordinated and adjusted to generate a set of equipment coordinated control parameters; Control and monitoring module: Distributes the set of equipment collaborative control parameters to each crushing device, monitors the proportion of material returned to the screen in the closed loop in real time, and recalculates the crushing ratio allocation vector and updates the set of equipment collaborative control parameters when the proportion of material returned exceeds the preset threshold.

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