A method of monitoring coal bunker wall sticking

Abstract

The present application relates to the technical field of coal storage monitoring, in particular to a method for monitoring coal bunker sticky wall, the existing coal bunker sticky wall monitoring method cannot be quantified, has low safety, poor real-time performance and is difficult to adapt to digital operation demand; the method obtains the coal accumulation and the coal discharge accumulation under the empty state of the coal bunker, calculates the difference to obtain the sticky wall amount, compares the sticky wall amount with the preset threshold and combines the sticky wall rate analysis to realize the sticky wall diagnosis and early warning; at the same time, the data can be updated by regular calibration to ensure the calculation accuracy; the present application is a non-invasive online real-time monitoring, fully utilizes the existing measurement data, realizes the accurate quantification of the sticky wall amount, can complete the historical tracking and trend analysis, can be integrated with the existing management system, provides data support for the preventive maintenance of the coal bunker, and effectively improves the safety and intelligent level of the coal bunker operation.

Description

Technical Field

[0001] This invention relates to the field of coal storage monitoring technology, and in particular to a method for monitoring coal bunker wall adhesion. Background Technology

[0002] In the coal mining, processing, and storage and transportation processes, coal bunkers (including silos and storage bins) serve as core storage and buffer facilities, and their normal operation is crucial for production continuity. However, the problem of coal adhering to the walls has been a long-standing issue, bringing many negative impacts to coal storage operations: First, coal adhering to the walls occupies effective storage capacity, significantly reducing the storage and buffering capacity of the coal bunker and affecting production scheduling; second, coal adhering to the walls for a long time is prone to oxidation and spontaneous combustion, and the material adhering to the walls may suddenly collapse when it accumulates to a certain extent, causing impact damage to equipment and even safety accidents, posing serious safety hazards; third, adhering to the walls disrupts the "first-in, last-out" storage principle for coal, leading to the mixing of different batches of coal, affecting the accuracy of coal blending and coal quality control, and at the same time, the material adhering to the walls causes serious distortion in coal warehouse inventory measurement, making it impossible to accurately grasp the actual inventory.

[0003] Currently, the industry mainly relies on three methods to monitor coal bunker wall adhesion: First, manual inspection, where staff check through observation holes or enter the bunker during cleaning. This method is not only inefficient but also poses a high safety risk due to manual entry. Furthermore, it cannot provide real-time information on wall adhesion or quantify the amount of adhesion. Second, video surveillance, which involves installing cameras inside the bunker for visual observation. However, the high dust levels, poor lighting, and limited camera angles inside the bunker make it difficult to comprehensively observe wall adhesion at various points, and it is impossible to quantify the thickness and weight of the adhesion. Third, wall vibration / impact analysis, which indirectly determines wall adhesion by collecting and analyzing vibration signals. This method is susceptible to vibration interference from other operations in the plant area, has low monitoring accuracy, and cannot convert vibration signals into specific wall adhesion weight, making it difficult to meet the quantitative requirements of actual production.

[0004] In summary, existing methods for monitoring coal bunker wall adhesion all have significant shortcomings. There is a lack of a safe, efficient, and quantifiable online monitoring method. Existing technologies either cannot accurately quantify the amount of adhesion or require shutdown or even manual intervention for monitoring, making them unsuitable for the continuous, intelligent, and safe operation requirements of modern digital coal bunkers. Therefore, a new method for monitoring coal bunker wall adhesion is urgently needed to solve these problems. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies by providing a method for monitoring coal bunker wall adhesion. Under the premise of stable coal bunker structure, the difference between the coal output and coal input in the empty bunker state mainly comes from the influence of materials adhering to the bunker wall. By calibrating and calculating this difference, the amount of wall adhesion can be accurately determined. Combined with threshold comparison and rate analysis, wall adhesion diagnosis and early warning can be achieved, effectively solving the problems mentioned in the background technology.

[0006] The technical solution adopted by the present invention to solve the above problems is as follows: A method for monitoring coal bunker wall adhesion includes the following steps; S1 determines the coal inlet and outlet quantities of the coal bunker: The coal inlet time is determined by a camera deployed on the inlet conveyor belt, and then the coal inlet quantity is determined by multiplying the coal inlet quantity per unit time of the measured conveyor belt, the coal inlet time, and the coal outlet quantity by statistically analyzing the loading and weighing data of the mine, i.e., the difference between the weighing of vehicles entering and leaving the factory. Dynamic calculation of wall adhesion during the operation of S2 coal bunker: Step 1: Data Acquisition. Collect the cumulative coal intake and output of the coal bunker in an empty state according to the set period. Step 2: Calculate the amount of coal adhering to the wall. The amount of coal adhering to the wall (empty bin state) is calculated using the formula: Amount of coal adhering to the wall (empty bin state) = Cumulative amount of coal fed in - Cumulative amount of coal discharged out. S3 Adhesion Diagnosis and Early Warning: The calculated amount of adhesion is compared with preset multi-level thresholds, and the rate of change of the amount of adhesion over time is tracked. When the amount of adhesion is greater than the first threshold (early warning threshold), a mild adhesion warning is issued. When the amount of adhesion is greater than the second threshold (action threshold), a severe adhesion alarm is issued, and the alarm signal can be interlocked to the production management system.

[0007] In S1, the monitoring data of coal input and output are collected continuously in real time, and the collection cycle can be adjusted according to the working conditions of the coal bunker.

[0008] The empty warehouse state refers to the state in which the coal storage in the coal warehouse is at a preset benchmark value, which can be calibrated according to the structure, specifications and actual usage requirements of the coal warehouse.

[0009] It also includes a model self-calibration step: after each coal bunker cleanup, the coal inlet and outlet determination operation of S1 is re-executed to update the data and correct the calculation deviation caused by equipment wear and changes in coal characteristics, so as to ensure the long-term accuracy of the wall adhesion calculation.

[0010] When the rate of change of the amount of material adhering to the wall increases abnormally over time, the system issues an early warning signal. The abnormality judgment criteria for the rate of change are set based on the historical operating data of the coal bunker and the characteristics of the coal type.

[0011] After the severe wall adhesion alarm is issued, the production management system generates a clearing plan suggestion or coal type adjustment suggestion based on the interlocking signal to avoid the continuous entry of easily wall-adhesive coal types into the warehouse.

[0012] This method can be integrated as a software module into existing digital coal bunker management platforms to achieve historical tracking and trend analysis of wall adhesion amount and wall adhesion rate.

[0013] Compared with the prior art, the present invention has the following advantages: 1. Quantitative diagnosis with higher accuracy: Breaking through the limitations of existing fuzzy judgment technology, it directly calculates and outputs the "tonnage of wall adhesion" through the difference between the amount of coal entering and leaving the wall, realizing the precise quantification of wall adhesion and providing specific and reliable data basis for production decision-making; 2. Non-invasive monitoring with high safety: No manual entry into the coal bunker or machine shutdown is required throughout the entire process. Real-time online monitoring can be achieved 24 / 7 during normal operation of the coal bunker, completely eliminating the safety risks of manual inspection and ensuring the continuity of production. 3. Low cost and wide applicability: It makes full use of existing data acquisition facilities such as cameras and weighing equipment in coal bunkers, without the need for additional expensive special sensors, which greatly reduces the construction cost of the monitoring system and can be adapted to different specifications of coal bunkers in various coal mines and coal chemical enterprises. 4. Model self-calibration and long-term stability: By periodically calibrating and updating data after the cleanup, the calculation deviation caused by equipment wear, changes in coal characteristics, etc. are automatically corrected to ensure the long-term accuracy of the wall adhesion calculation and avoid monitoring failure due to changes in equipment or operating conditions. 5. Intelligent early warning and proactive prevention: A multi-level early warning mechanism is established, which combines the comparison of wall adhesion threshold and the analysis of wall adhesion rate to achieve dual early warning. Moreover, the early warning / alarm signal can be linked to the production management system to realize intelligent suggestions for cleaning and coal type adjustment, effectively preventing safety hazards and production problems caused by wall adhesion. 6. Easy to integrate and adapt to digital needs: It can be easily integrated into the existing digital coal bunker management platform as a software module, realizing historical tracking, trend analysis and visualization of wall-adhesive data, perfectly adapting to the intelligent operation needs of modern digital coal bunkers and improving the overall management level of coal bunkers. Detailed Implementation

[0014] The following are specific embodiments of the present invention, and the technical solutions of the present invention will be further described in conjunction with the accompanying drawings. However, the present invention is not limited to these embodiments.

[0015] This invention provides a method for monitoring coal bunker wall adhesion, comprising the following steps; S1 determines the coal inlet and outlet quantities of the coal bunker: The coal inlet time is determined by a camera deployed on the inlet conveyor belt, and then the coal inlet quantity is determined by multiplying the coal inlet quantity per unit time of the measured conveyor belt, the coal inlet time, and the coal outlet quantity by statistically analyzing the loading and weighing data of the mine, i.e., the difference between the weighing of vehicles entering and leaving the factory. Dynamic calculation of wall adhesion during the operation of S2 coal bunker: Step 1: Data Acquisition. Collect the cumulative coal intake and output of the coal bunker in an empty state according to the set period. Step 2: Calculate the amount of coal adhering to the wall. The amount of coal adhering to the wall (empty bin state) is calculated using the formula: Amount of coal adhering to the wall (empty bin state) = Cumulative amount of coal fed in - Cumulative amount of coal discharged out. S3 Adhesion Diagnosis and Early Warning: The calculated amount of adhesion is compared with preset multi-level thresholds, and the rate of change of the amount of adhesion over time is tracked. When the amount of adhesion is greater than the first threshold, i.e. the early warning threshold, a mild adhesion warning is issued. When the amount of adhesion is greater than the second threshold, i.e. the action threshold, a severe adhesion alarm is issued, and the alarm signal can be interlocked to the production management system.

[0016] Determine the coal output and coal input rates; The amount of coal fed onto the conveyor belt per unit time is fixed. The amount of coal entering the coal bunker is calculated based on the time difference, and then the volume or size of the coal is estimated. The amount of coal output is determined by statistically analyzing the loading and weighing data of the mine. Specifically, the weighing values ​​of the transport vehicles entering the factory empty and leaving the factory loaded are recorded, the difference between the two is calculated and statistically analyzed to obtain the actual amount of coal output from the coal bunker. Dynamic calculation of wall adhesion during operation; During the normal cyclical operation of coal feeding, storage, and discharging in the coal bunker, the amount of coal adhering to the wall is dynamically calculated according to the following logic: Step 1: Data Acquisition. Continuously collect the cumulative coal intake and discharge volumes of the coal bunker in an empty state according to the set cycle. The empty state is defined as the coal inventory in the bunker reaching a preset benchmark value. The benchmark value can be flexibly determined according to the structure, specifications, actual operating conditions, and usage requirements of the coal bunker. The collection cycle can be adjusted according to production needs to achieve dynamic real-time monitoring. Step 2: Calculate the amount of coal adhering to the wall. The actual amount of coal adhering to the wall in the coal bunker is calculated using the core formula: amount of coal adhering to the wall in empty bunker = cumulative amount of coal fed in - cumulative amount of coal discharged out. The amount of coal adhering to the wall is directly output as a tonnage, thus achieving accurate quantification of the amount of coal adhering to the wall. Adhesion wall diagnosis and early warning; Based on the structural parameters, safety operation standards, production process requirements, and historical operating data of the coal bunker, two levels of thresholds for wall adhesion are pre-set: a first threshold, a warning threshold, a second threshold, and an action threshold. The real-time calculated wall adhesion amount is compared with the pre-set thresholds at each level, while continuously tracking the rate of change of wall adhesion amount over time to achieve wall adhesion diagnosis and graded early warning. When the amount of coal adhering to the wall exceeds the first threshold, the system automatically issues a mild wall adhering warning, prompting staff to pay attention to the coal bunker wall adhering situation and increase the monitoring frequency; When the amount of coal adhering to the wall exceeds the second threshold, the system automatically issues a severe wall-adhering alarm and can interlock the alarm signal to the production management system, which will then generate a clearing plan suggestion or a coal type adjustment suggestion to prevent the continuous entry of coal types that are prone to wall adhesion into the warehouse. If the rate of change of the amount of coal adhering to the wall over time increases abnormally, i.e. the abnormal judgment criteria are set according to the historical data of the coal bunker and the characteristics of the coal type, the system will issue an early warning signal in advance to achieve proactive prevention and control. Furthermore, the present invention also includes a model self-calibration step: after each coal bunker cleaning operation is completed, the coal feed and coal discharge determination operation in step 1 above is re-executed to update the baseline parameters of data acquisition, correct the calculation deviation caused by factors such as equipment wear, changes in coal type characteristics, and working condition adjustments, and ensure the long-term accuracy of the wall adhesion calculation. Meanwhile, the monitoring method of the present invention can be easily integrated into the existing digital coal bunker management platform as an independent software module. Through the platform, historical data tracking, trend analysis and visualization of the amount and rate of coal adhering to the wall can be realized, providing comprehensive and accurate data support for the long-term operation management and preventive maintenance of the coal bunker.

[0017] In S1, the monitoring data of coal input and output are collected continuously in real time, and the collection cycle can be adjusted according to the working conditions of the coal bunker.

[0018] The empty warehouse state refers to the state in which the coal storage in the coal warehouse is at a preset benchmark value, which can be calibrated according to the structure, specifications and actual usage requirements of the coal warehouse.

[0019] It also includes a model self-calibration step: after each coal bunker cleanup, the coal inlet and outlet determination operation of S1 is re-executed to update the data and correct the calculation deviation caused by equipment wear and changes in coal characteristics, so as to ensure the long-term accuracy of the wall adhesion calculation.

[0020] When the rate of change of the amount of material adhering to the wall increases abnormally over time, the system issues an early warning signal. The abnormality judgment criteria for the rate of change are set based on the historical operating data of the coal bunker and the characteristics of the coal type.

[0021] After the severe wall adhesion alarm is issued, the production management system generates a clearing plan suggestion or coal type adjustment suggestion based on the interlocking signal to avoid the continuous entry of easily wall-adhesive coal types into the warehouse.

[0022] This method can be integrated as a software module into existing digital coal bunker management platforms to achieve historical tracking and trend analysis of wall adhesion amount and wall adhesion rate.

[0023] This embodiment uses a cylindrical coal bunker with a diameter of 15m and a height of 30m in a coal mine as an example to illustrate the method for monitoring coal bunker wall adhesion. In use, this invention deploys a high-definition camera at the coal bunker's inlet conveyor belt to monitor the conveyor belt's coal transport speed and volume in real time, enabling continuous collection of coal input data. A weighbridge is set up in the coal mine's loading area to record the empty weight of each transport vehicle entering the plant and the loaded weight of each vehicle leaving the plant. The coal transport volume of a single vehicle is calculated and accumulated to obtain the actual coal output of the coal bunker. The collection cycle for coal input and output data is set to 5 minutes per time. First, the empty state of the coal bunker is defined as follows: the coal bunker is considered empty when the coal inventory is ≤50 tons. During normal coal feeding, storage, and discharging operations, the cumulative coal feeding and discharging amounts are collected every 5 minutes in the empty state. The amount of coal adhering to the wall (empty state) is calculated using the formula: Cumulative coal feeding amount - Cumulative coal discharging amount. For example, if the cumulative coal feeding amount in the empty state is 800 tons and the cumulative coal discharging amount is 765 tons in a certain statistical period, then the amount of coal adhering to the wall in that period is 35 tons. Based on the structural parameters, safety operation standards, and historical operation data of the coal bunker, the first threshold for wall adhesion is set at 50 tons, and the second threshold is set at 100 tons; at the same time, the abnormal standard for wall adhesion rate is set as: the wall adhesion amount increases by ≥20 tons within 24 hours.

[0024] When the amount of coal adhering to the wall reaches 52 tons, which is greater than the first threshold, the system will automatically issue a mild wall adhering warning to remind staff to strengthen the monitoring of coal bunker wall adhering. When the amount of coal adhering to the wall reaches 105 tons, which is greater than the second threshold, the system issues a severe wall-adhering alarm and transmits the alarm signal to the coal mine production management system. The system automatically generates a cleanup plan suggestion and prompts to suspend the entry of high-moisture coal types that are prone to wall adhesion. If the amount of coal adhering to the wall of the coal bunker increases from 40 tons to 62 tons within a 24-hour period, an increase of 22 tons, which is an abnormal rate, the system will issue an early warning signal in advance, and the staff will take preventive measures such as adjusting the coal type and blowing the bunker wall in a timely manner. After the coal bunker is cleaned, the coal intake and output data are collected again using the belt conveyor camera and loading weighbridge. The data collection benchmark is updated to correct calculation deviations caused by belt scale wear and recent changes in the moisture content of the coal entering the bunker, ensuring the accuracy of subsequent wall adhesion calculations. At the same time, the monitoring method of this invention is encapsulated as a software module and integrated into the coal mine's digital coal bunker management platform. The platform enables real-time display of wall adhesion amount and rate, historical data query, and trend analysis. Based on the wall adhesion trend, the platform automatically generates monthly and quarterly maintenance suggestions, providing data support for the intelligent operation of the coal bunker.

Claims

1. A method for monitoring coal bunker wall adhesion, characterized in that: Includes the following steps; S1 determines the coal inlet and outlet quantities of the coal bunker: The coal inlet time is determined by a camera deployed on the inlet conveyor belt, and then the coal inlet quantity is determined by multiplying the coal inlet quantity per unit time of the measured conveyor belt, the coal inlet time, and the coal outlet quantity by statistically analyzing the loading and weighing data of the mine, i.e., the difference between the weighing of vehicles entering and leaving the factory. Dynamic calculation of wall adhesion during the operation of S2 coal bunker: Step 1: Data acquisition. Collect the cumulative amount of coal entering and exiting the coal bunker in an empty state according to the set period. Step 2: Calculate the amount of coal adhering to the wall. The amount of coal adhering to the wall (empty bin state) is calculated using the formula: Amount of coal adhering to the wall (empty bin state) = Cumulative amount of coal fed in - Cumulative amount of coal discharged out. S3 Adhesion Diagnosis and Early Warning: The calculated amount of adhesion is compared with preset multi-level thresholds, and the rate of change of the amount of adhesion over time is tracked. When the amount of adhesion is greater than the first threshold (early warning threshold), a mild adhesion warning is issued. When the amount of adhesion is greater than the second threshold (action threshold), a severe adhesion alarm is issued, and the alarm signal can be interlocked to the production management system.

2. The method for monitoring coal bunker wall adhesion as described in claim 1, characterized in that: In S1, the monitoring data of coal input and output are collected continuously in real time, and the collection cycle can be adjusted according to the working conditions of the coal bunker.

3. The method for monitoring coal bunker wall adhesion as described in claim 1, characterized in that: The empty warehouse state refers to the state in which the coal storage in the coal warehouse is at a preset benchmark value, which can be calibrated according to the structure, specifications and actual usage requirements of the coal warehouse.

4. The method for monitoring coal bunker wall adhesion as described in claim 1, characterized in that: It also includes a model self-calibration step: after each coal bunker cleanup, the coal inlet and outlet determination operation of S1 is re-executed to update the data and correct the calculation deviation caused by equipment wear and changes in coal characteristics, so as to ensure the long-term accuracy of the wall adhesion calculation.

5. The method for monitoring coal bunker wall adhesion as described in claim 1, characterized in that: When the rate of change of the amount of material adhering to the wall increases abnormally over time, the system issues an early warning signal. The abnormality judgment criteria for the rate of change are set based on the historical operating data of the coal bunker and the characteristics of the coal type.

6. The method for monitoring coal bunker wall adhesion as described in claim 1, characterized in that: After the severe wall adhesion alarm is issued, the production management system generates a clearing plan suggestion or coal type adjustment suggestion based on the interlocking signal to avoid the continuous entry of easily wall-adhesive coal types into the warehouse.

7. The method for monitoring coal bunker wall adhesion as described in claim 1, characterized in that: This method can be integrated as a software module into existing digital coal bunker management platforms to achieve historical tracking and trend analysis of wall adhesion amount and wall adhesion rate.