Coal conveying equipment fault monitoring system and fault monitoring method thereof

Abstract

The invention belongs to the technical field of monitoring, and particularly relates to a coal conveying equipment fault monitoring system and method, and the system comprises a data collection module which is used for collecting all parameter data of coal conveying equipment; the data transmission module is used for transmitting the data acquired by the data acquisition module; the data processing and analyzing module is used for processing and analyzing the data transmitted by the data transmission module so as to analyze whether the coal conveying equipment has a fault or not; and the intelligent alarm optimization module is used for grading the fault of the coal conveying equipment and then giving an alarm when the data processing and analysis module analyzes that the coal conveying equipment has the fault. The running state of the coal conveying equipment is monitored in real time, equipment faults are predicted in advance, measures are taken in time for processing, and production interruption caused by sudden equipment faults is avoided. Therefore, the reliability and availability of the equipment are improved, the production continuity is guaranteed, and the economic loss caused by equipment faults is reduced.

Description

Technical Field

[0001] The present invention relates to the field of monitoring technology, and in particular to a coal conveying equipment fault monitoring system and a fault monitoring method thereof. Background Art

[0002] Coal handling equipment refers to the various types of machinery used for transporting and processing coal, primarily including belt conveyors, coal feeders, bucket elevators, screening equipment, hammer crushers, and slag removal equipment. These devices together form a complete coal handling system, ensuring efficient operation of every link in the coal process, from mining to processing, storage, and transportation.

[0003] In industries such as power and chemical engineering, coal conveying systems are a crucial component of material transportation, and their stable operation is crucial to the entire production process. Coal conveying equipment is often exposed to harsh operating environments, such as high dust levels, high humidity, and heavy loads, making it prone to failures, leading to production interruptions, economic losses, and safety hazards. Traditional equipment maintenance relies primarily on manual inspections, which are subject to high subjectivity, long inspection cycles, and delayed fault detection. Therefore, a coal conveying equipment fault monitoring system and method are proposed. Summary of the Invention

[0004] To solve the above technical problems, according to one aspect of the present invention, the present invention provides the following technical solutions:

[0005] A coal handling equipment fault monitoring system, comprising:

[0006] Data acquisition module, used to collect various parameter data of coal handling equipment;

[0007] A data transmission module, used for transmitting the data collected by the data acquisition module;

[0008] The data processing and analysis module is used to process and analyze the data transmitted by the data transmission module to analyze whether there is a fault in the coal conveying equipment;

[0009] The intelligent alarm optimization module is used to classify the coal handling equipment failure and then issue an alarm when the data processing and analysis module analyzes that the coal handling equipment has a failure;

[0010] The equipment life prediction module is used to organize the data analyzed by the data processing and analysis module so as to predict the life of the coal handling equipment based on the organized data;

[0011] Energy management module, used to optimize the operating parameters of coal handling equipment according to its energy consumption;

[0012] The intelligent alarm optimization module includes:

[0013] The classification module is used to classify the alarm information according to the severity of the equipment failure, the frequency of the failure, and the impact on production when the data processing and analysis module analyzes that there is a failure in the coal handling equipment;

[0014] Priority alarm module, used to issue high-priority alarms for emergency failures that seriously affect production and notify personnel in a timely manner;

[0015] The low-priority alarm module is used to issue low-priority alarms for minor faults or potential hidden dangers, and conduct centralized display and statistical analysis to facilitate unified processing by maintenance personnel.

[0016] As a preferred solution of the coal handling equipment fault monitoring system of the present invention, the data acquisition module includes:

[0017] The vibration sensor module is used to collect real-time vibration signals from coal handling equipment during operation. The vibration signal is an important parameter reflecting the operating status of the equipment. By analyzing the vibration amplitude and frequency characteristics, it can be determined whether the equipment has imbalance, wear, or loose faults.

[0018] Temperature sensor module, used to monitor the temperature of coal handling equipment during operation;

[0019] The current sensor module is used to measure the current of the coal conveying equipment during operation.

[0020] As a preferred solution of the coal handling equipment fault monitoring system of the present invention, the data acquisition module further includes:

[0021] The belt deviation sensor module is used to detect whether the belt is deviating. If the belt deviates, it will cause increased belt wear, material spillage, and even cause belt tearing in severe cases.

[0022] The coal flow sensor module is used to detect whether there is coal flow on the belt and the size of the coal flow. By monitoring the coal flow, it can be determined whether the coal conveying system is operating normally, avoiding equipment failure caused by interruption or excessive coal flow.

[0023] As a preferred solution of the coal handling equipment fault monitoring system of the present invention, the data processing and analysis module includes:

[0024] The data preprocessing module is used to preprocess the data transmitted by the data transmission module, including data cleaning, denoising, and normalization operations to improve the quality and availability of the data;

[0025] The feature extraction module is used to extract feature parameters reflecting the operating status of the equipment from the preprocessed data performed by the data preprocessing module.

[0026] As a preferred solution of the coal handling equipment fault monitoring system of the present invention, the data processing and analysis module further includes:

[0027] The data analysis and modeling module is used to conduct in-depth analysis of the characteristic parameters extracted by the feature extraction module, so as to be able to evaluate and predict the operating status of the equipment by establishing an equipment failure prediction model;

[0028] The fault diagnosis module is used to determine the fault type and location by comparing the current operating data of the equipment with the data characteristics in the fault mode library when the data analyzed by the data analysis and modeling module indicates the existence of a fault.

[0029] As a preferred solution of the coal handling equipment fault monitoring system of the present invention, the equipment life prediction module includes:

[0030] A data acquisition module is used to acquire the data analyzed by the data processing and analysis module;

[0031] The data storage module is used to store the data acquired by the data acquisition module.

[0032] As a preferred solution of the coal handling equipment fault monitoring system of the present invention, the equipment life prediction module further includes:

[0033] Data statistics module, used to classify and organize the data in the data storage module;

[0034] The data evaluation module is used to establish a component life model based on the data collected by the data statistics module, comprehensively considering the equipment's usage time, operating conditions, and maintenance records, and predict the probability of equipment failure in the future and the remaining service life of the components.

[0035] As a preferred solution of the coal handling equipment fault monitoring system of the present invention, the energy management module includes:

[0036] Energy consumption data monitoring module, used to monitor the energy consumption data of coal handling equipment in real time;

[0037] Energy consumption data analysis module, used to analyze energy consumption data to identify peak energy consumption periods and inefficient operation links;

[0038] The optimization module is used to optimize the operating parameters of the equipment in accordance with the operating requirements of the equipment to achieve energy-saving operation of the equipment.

[0039] A method for monitoring coal conveying equipment faults includes the following specific steps:

[0040] Step 1: Use the vibration sensor module to collect the vibration signal of the coal conveyor during operation in real time, use the temperature sensor module to monitor the temperature of the coal conveyor during operation, use the current sensor module to measure the current of the coal conveyor during operation, use the belt deviation sensor module to detect whether the belt is deviating, and use the coal flow sensor module to detect whether there is coal flow on the belt and the amount of coal flow;

[0041] Step 2: Transmitting the data collected by the data acquisition module through the data transmission module;

[0042] Step 3: The data transmitted by the data transmission module is preprocessed by the data preprocessing module. After preprocessing, the feature extraction module can extract the feature parameters reflecting the operating status of the equipment from the preprocessed data performed by the data preprocessing module. After extraction, the feature parameters extracted by the feature extraction module are deeply analyzed by the data analysis and modeling module, so as to be able to evaluate and predict the operating status of the equipment by establishing an equipment fault prediction model. Afterwards, when the data analyzed by the data analysis and modeling module indicates that there is a fault, the fault diagnosis module can determine the fault type and fault location by comparing the current operating data of the equipment with the data features in the fault mode library;

[0043] Step 4: When the data processing and analysis module analyzes that there is a fault in the coal handling equipment through the classification module, the alarm information can be graded according to the severity of the equipment fault, the frequency of the fault, and the impact on production. Among them, for emergency faults that seriously affect production, a high-priority alarm will be issued through the priority alarm module to notify personnel in time. For minor faults or potential hidden dangers, a low-priority alarm will be issued through the low-priority alarm module, and centralized display and statistical analysis will be carried out to facilitate unified processing by maintenance personnel;

[0044] Step 5: The data analyzed by the data processing and analysis module is acquired through the data acquisition module. After acquisition, the data acquired by the data acquisition module will be stored through the data storage module. After storage, the data in the data storage module will be classified and sorted through the data statistics module. After that, the component life model will be established based on the data collected by the data statistics module through the data evaluation module. Taking into account the equipment's usage time, operating conditions, and maintenance records, the probability of equipment failure in the future and the remaining service life of the components are predicted;

[0045] Step 6: The energy consumption data of the coal handling equipment is monitored in real time through the energy consumption data monitoring module. After monitoring, the energy consumption data will be analyzed through the energy consumption data analysis module to find out the peak periods of energy consumption and inefficient operation links. Afterwards, the optimization module will be used to optimize the equipment's operating parameters in combination with the equipment's operating requirements to achieve energy-saving operation of the equipment.

[0046] Compared with existing technologies:

[0047] 1. Improve equipment reliability and availability: By monitoring the operating status of coal handling equipment in real time, equipment failures can be predicted in advance and timely measures can be taken to address them, avoiding production interruptions caused by sudden equipment failures. This improves equipment reliability and availability, ensures production continuity, and reduces economic losses caused by equipment failures.

[0048] 2. Improved production efficiency: Because equipment failures are promptly and effectively controlled, downtime during production is significantly reduced, thereby improving production efficiency. At the same time, the system can monitor the operation of the coal handling system in real time, providing accurate data support for production scheduling, optimizing production processes, and further improving production efficiency.

[0049] 3. Ensure safe production: Failures in coal handling equipment can lead to accidents, such as belt ruptures causing spilled materials and equipment fires. This fault monitoring system can promptly detect hidden equipment failures and take appropriate measures to address them, preventing accidents and protecting the lives of employees and the property of the company.

[0050] 4. By setting up an equipment life prediction module, the company can know the remaining life of equipment components in advance. Enterprises can reasonably arrange equipment maintenance and replacement plans, avoid emergency repairs when the equipment is about to fail, and reduce the risk of production interruption caused by sudden equipment failure.

[0051] 5. By setting up the energy management module, it is possible to reduce unnecessary energy consumption and lower the energy costs of the enterprise by optimizing equipment operating parameters.

[0052] 6. By setting up an intelligent alarm optimization module, it is possible to process alarm information in a hierarchical manner to ensure that maintenance personnel can pay attention to the most urgent and important equipment failures at the first time, take timely measures to deal with them, and reduce the impact of equipment failures on production. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0054] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0055] The present invention provides a coal handling equipment fault monitoring system, please refer to Figure 1 ;

[0056] It includes: a data acquisition module for collecting various parameter data of the coal conveying equipment; a data transmission module for transmitting the data collected by the data acquisition module; a data processing and analysis module for processing and analyzing the data transmitted by the data transmission module to analyze whether there is a fault in the coal conveying equipment; an intelligent alarm optimization module for first classifying the fault of the coal conveying equipment and then issuing an alarm when the data processing and analysis module analyzes that there is a fault in the coal conveying equipment; an equipment life prediction module for collating the data analyzed by the data processing and analysis module to predict the life of the coal conveying equipment based on the sorted data; an energy management module for optimizing the operating parameters of the coal conveying equipment according to the energy consumption of the coal conveying equipment;

[0057] The intelligent alarm optimization module includes: a grading module, which is used to grade the alarm information according to the severity of the equipment failure, the frequency of the failure and the impact on production when the data processing and analysis module analyzes that there is a failure in the coal handling equipment; a priority alarm module, which is used to issue a high-priority alarm for emergency failures that seriously affect production and notify personnel in a timely manner; a low-priority alarm module, which is used to issue a low-priority alarm for minor failures or potential hidden dangers, and conduct centralized display and statistical analysis to facilitate unified processing by maintenance personnel.

[0058] The data acquisition module includes: a vibration sensor module, which is used to collect the vibration signal of the coal conveying equipment in real time during operation. The vibration signal is an important parameter reflecting the operating status of the equipment. By analyzing the vibration amplitude and frequency characteristics, it can be judged whether the equipment has imbalance, wear, or looseness faults; a temperature sensor module, which is used to monitor the temperature of the coal conveying equipment during operation; a current sensor module, which is used to measure the current of the coal conveying equipment during operation; a belt deviation sensor module, which is used to detect whether the belt has deviated. When the belt deviates, the belt wear will increase and material will spill. In severe cases, it may even cause the belt to tear; a coal flow sensor module, which is used to detect whether there is coal flow on the belt and the size of the coal flow. By monitoring the coal flow, it can be judged whether the operation of the coal conveying system is normal, and equipment failure caused by interruption or excessive coal flow can be avoided.

[0059] The data processing and analysis module includes: a data preprocessing module, which is used to preprocess the data transmitted by the data transmission module, including data cleaning, denoising, and normalization operations to improve the quality and availability of the data; a feature extraction module, which is used to extract feature parameters reflecting the operating status of the equipment from the preprocessed data performed by the data preprocessing module; a data analysis and modeling module, which is used to conduct in-depth analysis of the feature parameters extracted by the feature extraction module, so as to evaluate and predict the operating status of the equipment by establishing an equipment fault prediction model; and a fault diagnosis module, which is used to determine the fault type and fault location by comparing the current operating data of the equipment with the data features in the fault mode library when the data analyzed by the data analysis and modeling module indicates the existence of a fault.

[0060] The equipment life prediction module includes: a data acquisition module for acquiring the data analyzed by the data processing and analysis module; a data storage module for storing the data acquired by the data acquisition module; a data statistics module for classifying and organizing the data in the data storage module; and a data evaluation module for establishing a component life model based on the data collected by the data statistics module, comprehensively considering the equipment's usage time, operating conditions, and maintenance record factors, to predict the probability of equipment failure in the future and the remaining service life of the components.

[0061] The energy management module includes: an energy consumption data monitoring module for real-time monitoring of the energy consumption data of the coal handling equipment; an energy consumption data analysis module for analyzing the energy consumption data to identify peak periods of energy consumption and inefficient operating links; and an optimization module for optimizing the operating parameters of the equipment in combination with the operating requirements of the equipment to achieve energy-saving operation of the equipment.

[0062] A method for monitoring coal conveying equipment faults includes the following specific steps:

[0063] Step 1: Use the vibration sensor module to collect the vibration signal of the coal conveyor during operation in real time, use the temperature sensor module to monitor the temperature of the coal conveyor during operation, use the current sensor module to measure the current of the coal conveyor during operation, use the belt deviation sensor module to detect whether the belt is deviating, and use the coal flow sensor module to detect whether there is coal flow on the belt and the amount of coal flow;

[0064] Step 2: Transmitting the data collected by the data acquisition module through the data transmission module;

[0065] Step 3: The data transmitted by the data transmission module is preprocessed by the data preprocessing module. After preprocessing, the feature extraction module can extract the feature parameters reflecting the operating status of the equipment from the preprocessed data performed by the data preprocessing module. After extraction, the feature parameters extracted by the feature extraction module are deeply analyzed by the data analysis and modeling module, so as to be able to evaluate and predict the operating status of the equipment by establishing an equipment fault prediction model. Afterwards, when the data analyzed by the data analysis and modeling module indicates that there is a fault, the fault diagnosis module can determine the fault type and fault location by comparing the current operating data of the equipment with the data features in the fault mode library;

[0066] Step 4: When the data processing and analysis module analyzes that there is a fault in the coal handling equipment through the classification module, the alarm information can be graded according to the severity of the equipment fault, the frequency of the fault, and the impact on production. Among them, for emergency faults that seriously affect production, a high-priority alarm will be issued through the priority alarm module to notify personnel in time. For minor faults or potential hidden dangers, a low-priority alarm will be issued through the low-priority alarm module, and centralized display and statistical analysis will be carried out to facilitate unified processing by maintenance personnel;

[0067] Step 5: The data analyzed by the data processing and analysis module is acquired through the data acquisition module. After acquisition, the data acquired by the data acquisition module will be stored through the data storage module. After storage, the data in the data storage module will be classified and sorted through the data statistics module. After that, the component life model will be established based on the data collected by the data statistics module through the data evaluation module. Taking into account the equipment's usage time, operating conditions, and maintenance records, the probability of equipment failure in the future and the remaining service life of the components are predicted;

[0068] Step 6: The energy consumption data of the coal handling equipment is monitored in real time through the energy consumption data monitoring module. After monitoring, the energy consumption data will be analyzed through the energy consumption data analysis module to find out the peak periods of energy consumption and inefficient operation links. Afterwards, the optimization module will be used to optimize the equipment's operating parameters in combination with the equipment's operating requirements to achieve energy-saving operation of the equipment.

[0069] Although the present invention has been described above with reference to embodiments, various modifications may be made thereto and equivalent components may be substituted without departing from the scope of the present invention. In particular, as long as there are no structural conflicts, the various features of the embodiments disclosed herein may be combined with each other in any manner, and the omission of an exhaustive description of such combinations in this specification is solely for the sake of space and resource conservation. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A coal handling equipment fault monitoring system, characterized in that: include: Data acquisition module, used to collect various parameter data of coal handling equipment; A data transmission module, used for transmitting the data collected by the data acquisition module; The data processing and analysis module is used to process and analyze the data transmitted by the data transmission module to analyze whether there is a fault in the coal conveying equipment; The intelligent alarm optimization module is used to classify the coal handling equipment failure and then issue an alarm when the data processing and analysis module analyzes that the coal handling equipment has a failure; The equipment life prediction module is used to organize the data analyzed by the data processing and analysis module so as to predict the life of the coal handling equipment based on the organized data; Energy management module, used to optimize the operating parameters of coal handling equipment according to its energy consumption; The intelligent alarm optimization module includes: The classification module is used to classify the alarm information according to the severity of the equipment failure, the frequency of the failure, and the impact on production when the data processing and analysis module analyzes that there is a failure in the coal handling equipment; Priority alarm module, used to issue high-priority alarms for emergency failures that seriously affect production and notify personnel in a timely manner; The low-priority alarm module is used to issue low-priority alarms for minor faults or potential hidden dangers, and conduct centralized display and statistical analysis to facilitate unified processing by maintenance personnel.

2. A coal handling equipment fault monitoring system according to claim 1, characterized in that: The data acquisition module includes: The vibration sensor module is used to collect real-time vibration signals from coal handling equipment during operation. The vibration signal is an important parameter reflecting the operating status of the equipment. By analyzing the vibration amplitude and frequency characteristics, it can be determined whether the equipment has imbalance, wear, or loose faults. Temperature sensor module, used to monitor the temperature of coal handling equipment during operation; The current sensor module is used to measure the current of the coal conveying equipment during operation.

3. A coal handling equipment fault monitoring system according to claim 2, characterized in that: The data acquisition module also includes: The belt deviation sensor module is used to detect whether the belt is deviating. If the belt deviates, it will cause increased belt wear, material spillage, and even cause belt tearing in severe cases. The coal flow sensor module is used to detect whether there is coal flow on the belt and the size of the coal flow. By monitoring the coal flow, it can be determined whether the coal conveying system is operating normally, avoiding equipment failure caused by interruption or excessive coal flow.

4. A coal handling equipment fault monitoring system according to claim 1, characterized in that: The data processing and analysis module includes: The data preprocessing module is used to preprocess the data transmitted by the data transmission module, including data cleaning, denoising, and normalization operations to improve the quality and availability of the data; The feature extraction module is used to extract feature parameters reflecting the operating status of the equipment from the preprocessed data performed by the data preprocessing module.

5. A coal handling equipment fault monitoring system according to claim 4, characterized in that: The data processing and analysis module also includes: The data analysis and modeling module is used to conduct in-depth analysis of the characteristic parameters extracted by the feature extraction module, so as to be able to evaluate and predict the operating status of the equipment by establishing an equipment failure prediction model; The fault diagnosis module is used to determine the fault type and location by comparing the current operating data of the equipment with the data characteristics in the fault mode library when the data analyzed by the data analysis and modeling module indicates the existence of a fault.

6. A coal handling equipment fault monitoring system according to claim 1, characterized in that: The equipment life prediction module includes: A data acquisition module is used to acquire the data analyzed by the data processing and analysis module; The data storage module is used to store the data acquired by the data acquisition module.

7. A coal handling equipment fault monitoring system according to claim 6, characterized in that: The equipment life prediction module also includes: Data statistics module, used to classify and organize the data in the data storage module; The data evaluation module is used to establish a component life model based on the data collected by the data statistics module, comprehensively considering the equipment's usage time, operating conditions, and maintenance records, and predict the probability of equipment failure in the future and the remaining service life of the components.

8. A coal handling equipment fault monitoring system according to claim 1, characterized in that: The energy management module includes: Energy consumption data monitoring module, used to monitor the energy consumption data of coal handling equipment in real time; Energy consumption data analysis module, used to analyze energy consumption data to identify peak energy consumption periods and inefficient operation links; The optimization module is used to optimize the operating parameters of the equipment in accordance with the operating requirements of the equipment to achieve energy-saving operation of the equipment.

9. A method for monitoring coal handling equipment failure, characterized in that: The specific steps are as follows: Step 1: Use the vibration sensor module to collect the vibration signal of the coal conveyor during operation in real time, use the temperature sensor module to monitor the temperature of the coal conveyor during operation, use the current sensor module to measure the current of the coal conveyor during operation, use the belt deviation sensor module to detect whether the belt is deviating, and use the coal flow sensor module to detect whether there is coal flow on the belt and the amount of coal flow; Step 2: Transmitting the data collected by the data acquisition module through the data transmission module; Step 3: The data transmitted by the data transmission module is preprocessed by the data preprocessing module. After preprocessing, the feature extraction module can extract the feature parameters reflecting the operating status of the equipment from the preprocessed data performed by the data preprocessing module. After extraction, the feature parameters extracted by the feature extraction module are deeply analyzed by the data analysis and modeling module, so as to be able to evaluate and predict the operating status of the equipment by establishing an equipment fault prediction model. Afterwards, when the data analyzed by the data analysis and modeling module indicates that there is a fault, the fault diagnosis module can determine the fault type and fault location by comparing the current operating data of the equipment with the data features in the fault mode library; Step 4: When the data processing and analysis module analyzes that there is a fault in the coal handling equipment through the classification module, the alarm information can be graded according to the severity of the equipment fault, the frequency of the fault, and the impact on production. Among them, for emergency faults that seriously affect production, a high-priority alarm will be issued through the priority alarm module to notify personnel in time. For minor faults or potential hidden dangers, a low-priority alarm will be issued through the low-priority alarm module, and centralized display and statistical analysis will be carried out to facilitate unified processing by maintenance personnel; Step 5: The data analyzed by the data processing and analysis module is acquired through the data acquisition module. After acquisition, the data acquired by the data acquisition module will be stored through the data storage module. After storage, the data in the data storage module will be classified and sorted through the data statistics module. After that, the component life model will be established based on the data collected by the data statistics module through the data evaluation module. Taking into account the equipment's usage time, operating conditions, and maintenance records, the probability of equipment failure in the future and the remaining service life of the components are predicted; Step 6: The energy consumption data of the coal handling equipment is monitored in real time through the energy consumption data monitoring module. After monitoring, the energy consumption data will be analyzed through the energy consumption data analysis module to find out the peak periods of energy consumption and inefficient operation links. Afterwards, the optimization module will be used to optimize the equipment's operating parameters in combination with the equipment's operating requirements to achieve energy-saving operation of the equipment.

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