Coal mine electromechanical equipment maintenance wireless supervision system and supervision method thereof

Abstract

The invention relates to the technical field of coal mine safety monitoring, and provides a coal mine electromechanical equipment maintenance wireless supervision system which comprises a data acquisition terminal based on a Bluetooth low energy (BLE) module and a LoRa wireless communication technology, a monitoring end platform based on cloud computing and a wireless network coverage system based on a LoRa gateway. According to the system, a comprehensive, efficient and sustainable solution is provided through technical integration, the operation safety and the maintenance efficiency of the coal mine electromechanical equipment are improved, and powerful technical support is provided for safety management of a mining area.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine safety monitoring, and in particular to a coal mine electromechanical equipment maintenance wireless monitoring system and a monitoring method thereof. Background Art

[0002] As an important energy resource, coal occupies an important position in the global energy structure. Although modern society is increasingly dependent on renewable energy, coal is still the cornerstone of energy supply in many countries, especially in industrial production and power generation. The coal mining industry has extremely high requirements for safe production due to the complexity of its operating environment and potential high risks. Therefore, improving the safety and efficiency of coal mines, especially in the maintenance and monitoring of electromechanical equipment, has become the key to the development of the industry.

[0003] Insufficient maintenance of existing coal mine electromechanical equipment Traditional monitoring and maintenance methods are highly dependent: Many coal mines still rely on traditional manual inspections and regular maintenance strategies. These methods are not only inefficient, but also susceptible to human error and unable to detect problems in real time, leading to increased risks of equipment failure and accidents.

[0004] Insufficient data utilization: Although field equipment may be equipped with various sensors, the collected data is often not effectively utilized. The lack of advanced data analysis tools and technologies prevents coal mines from gaining valuable insights from the data to guide maintenance decisions and predict equipment failures.

[0005] Long maintenance response time: Under existing technology conditions, there is often a time delay from the identification of equipment problems to the response of maintenance personnel. This delay may cause minor problems to evolve into serious failures, increasing repair costs and downtime.

[0006] Safety hazards and insufficient environmental monitoring: Traditional monitoring systems often ignore the impact of environmental factors on equipment performance. For example, poor working conditions and unforeseen environmental changes may cause rapid equipment degradation or failure.

[0007] Energy utilization and environmental protection issues: Traditional coal mine electromechanical equipment often requires continuous power supply, but in some mining areas, stable power supply is not always reliable. In addition, high efficiency of energy consumption and environmental protection standards are increasingly becoming the focus of public and policy attention.

[0008] Therefore, this invention proposes a wireless monitoring system and a monitoring method for maintenance of electromechanical equipment in coal mines to solve the above problems. Summary of the invention

[0009] In order to overcome the defects of the prior art, the object of the present invention is to provide a wireless monitoring system and a monitoring method for the maintenance of coal mine electromechanical equipment.

[0010] To achieve the above object, the technical solution of the present invention is implemented as follows: a wireless monitoring system for maintenance of electromechanical equipment in coal mines, the system comprising: The data acquisition terminal based on Bluetooth low energy (BLE) module and LoRa wireless communication technology includes a sensor module, a Bluetooth module, a display screen and a Bluetooth tag fixed on the electromechanical equipment. The Bluetooth tag uses the Nordic nRF52832 chip. The sensor module may include a vibration sensor, a temperature sensor and a humidity sensor to collect the operating status of the electromechanical equipment. The cloud computing-based monitoring platform includes a cloud database, data processing and analysis module, RESTful API server, Bluetooth tag reader and SMS gateway. The Bluetooth tag reader uses Bluetooth 5.0 technology, and the SMS gateway uses Twilio API. The monitoring platform can process and store data from the data collection terminal in real time. The wireless network coverage system based on LoRa gateway generates LoRa wireless network through LoRa gateway. LoRa gateway adopts Semtech SX1301 chip. LoRa network covers the area where the electromechanical equipment of coal mine is located, and is connected to the cloud computing platform through Ethernet to ensure the stable transmission of data. The above systems are connected in the following ways: the cloud database, data processing and analysis module and RESTful API server are deployed on the cloud computing platform, the Bluetooth tag reading device and SMS gateway are connected to the cloud computing platform through the API interface, and the LoRa gateway covers the area where the coal mine electromechanical equipment is located through the LoRa wireless network and is connected to the cloud computing platform through Ethernet.

[0011] Preferably, the data acquisition terminal also includes an environmental sensor, which includes a gas sensor and a light intensity sensor for collecting information such as temperature, humidity, gas concentration and light intensity in the coal mine environment, so as to more comprehensively monitor the safety status of the coal mine environment.

[0012] Preferably, the monitoring terminal platform also includes a data analysis module based on a machine learning algorithm, which can perform multivariate time series analysis, and is used to perform predictive maintenance analysis and anomaly detection on the collected electromechanical equipment operation data, and provide equipment failure prediction and maintenance recommendations.

[0013] Preferably, the data acquisition terminal adopts a solar power supply module and is equipped with a high-efficiency lithium battery energy storage system to reduce the frequency of battery replacement and ensure the continuous operation of the data acquisition terminal.

[0014] Preferably, the monitoring terminal platform provides real-time monitoring and historical data query functions through a Web interface and supports access by mobile devices. The Web interface has a user-friendly interactive interface and supports data visualization, alarm notification and inspection task management functions.

[0015] Preferably, the method comprises the following steps: Enter the electromechanical equipment information on the cloud computing platform, enter and generate inspection tasks according to the inspection items, and the system automatically generates an inspection plan and assigns tasks. The inspection plan includes specific inspection time, inspection personnel, inspection equipment and inspection content; A unique identification number is stored in the Bluetooth tag fixed on the electromechanical equipment. The coal mine electromechanical equipment uses the unique identification number in the Bluetooth tag as identity authentication information. The data collection terminal reads the unique identification number in the Bluetooth tag through Bluetooth communication and submits it to the RESTful API server. The data collection terminal can also collect the operating parameters of the equipment. According to the task arrangement of the monitoring platform, the inspection personnel fill in the inspection form through the data collection terminal. After filling in, the inspection data is generated. The inspection data is sent to the RESTful API server in real time through the LoRa wireless network and stored in the cloud database. The inspection form includes the equipment operation status, environmental parameters and the inspection personnel's notes; The data processing and analysis module displays the transmitted data and generated charts in real time to observe the operating status of electromechanical equipment, and uses machine learning algorithms to perform predictive maintenance analysis and generate equipment health status reports.

[0016] Preferably, the following steps are also included: when the monitoring platform detects abnormal operation of the electromechanical equipment, it automatically sends an early warning message to the relevant maintenance personnel through the SMS gateway. The early warning message includes the equipment number, abnormality type, recommended handling measures and emergency contact information.

[0017] Preferably, the inspection data also includes environmental data collected by environmental sensors, and the environmental data includes temperature, humidity, gas concentration and light intensity, so as to comprehensively evaluate the operating status of the electromechanical equipment and the safety of the surrounding environment.

[0018] Preferably, the monitoring terminal platform provides a data export function and supports multiple data formats, including CSV, Excel and PDF formats, so as to generate reports for further analysis and decision support. The exported reports include equipment operating status, historical data trends and predictive maintenance recommendations.

[0019] Preferably, the data processing and analysis module can generate trend analysis charts based on historical data. The trend analysis charts include equipment operation status trends, environmental parameter change trends and equipment failure prediction charts to help managers make equipment maintenance decisions. The charts support custom time ranges and parameter selections.

[0020] The beneficial effects of the present invention are embodied in: Real-time monitoring and remote management: Through the integrated Web interface and mobile device application, real-time monitoring of coal mine electromechanical equipment is achieved, allowing managers to obtain equipment status and environmental parameters at any time, greatly improving response speed and management efficiency.

[0021] Predictive maintenance and fault warning: Using advanced machine learning algorithms, the system can analyze the equipment's operating data, predict potential failures and maintenance needs, and send early warning information in a timely manner via SMS or other communication methods, thereby reducing unexpected downtime and repair costs.

[0022] Optimized inspection process: Automated inspection task generation and allocation reduces the burden of manual operations, ensures the accuracy and timeliness of inspection work, and simplifies data management and tracking processes through digital records.

[0023] Data-driven decision support: By collecting and analyzing historical operating data, generating trend analysis and equipment status reports, it helps management make scientific maintenance decisions and optimize resource allocation.

[0024] Environmental and safety monitoring: The integrated use of multiple sensors not only monitors the equipment status, but also assesses the safety of the surrounding environment, such as gas leaks or other potential hazards, enhancing overall safety management.

[0025] Energy saving and sustainable operation: The use of solar power supply and high-capacity lithium batteries ensures that the device can continue to operate stably without external power supply, supporting the use of green energy.

[0026] The system provides a comprehensive, efficient and sustainable solution through technical integration, which not only improves the operational safety and maintenance efficiency of coal mine electromechanical equipment, but also provides strong technical support for mine safety management. In addition, the scalability and flexibility of the system enable it to adapt to the ever-changing industrial environment and technological development, laying a solid foundation for future intelligent coal mine operations. Through this highly integrated monitoring system, coal mining companies can effectively reduce operating costs and improve production efficiency while ensuring the safety of staff and environmental protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In the attached picture: Figure 1 It is a schematic diagram of the system structure of the present invention; Figure 2 It is a schematic diagram of the structure of the environmental sensor of the present invention; Figure 3 It is a schematic diagram of the operation steps of the present invention; DETAILED DESCRIPTION

[0028] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only part of the embodiments of the invention, rather than all of the embodiments. In the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other. Based on the embodiments in the invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the invention.

[0029] It should be noted that if the embodiments of the invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0030] In addition, "multiple" means more than two. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the fact that ordinary technicians in the field can implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection required by the invention.

[0031] Please refer to the instruction manual Figure 1-Figure 3 The present invention provides an implementation method of a wireless monitoring system for coal mine electromechanical equipment maintenance and a monitoring method thereof: System overall architecture The system consists of three parts: data acquisition terminal, monitoring platform and wireless network coverage system. The specific system architecture is as follows: Data collection terminal The data acquisition terminal is installed on the electromechanical equipment of the coal mine to collect the equipment operating status and environmental parameters. Specifically include: Sensor module: including vibration sensor, temperature sensor, humidity sensor, gas sensor and light intensity sensor. The vibration sensor adopts MEMS technology and can detect the vibration frequency, amplitude and direction of the equipment. The temperature sensor adopts accurate digital temperature sensor, the humidity sensor adopts high-precision humidity sensor, the gas sensor adopts combustible gas sensor and toxic gas sensor, and the light intensity sensor adopts photodiode to measure the ambient light intensity.

[0032] Bluetooth module: Adopts Nordic nRF52832 chip to realize low-power Bluetooth communication, which can stably transmit data and maintain long-term connection. The Bluetooth tag is fixed on the electromechanical equipment to store the unique identification number.

[0033] Display screen: Displays the equipment's operating status, sensor data and alarm information in real time.

[0034] Power module: The solar power supply module uses high-efficiency solar photovoltaic panels and MPPT chargers, combined with a high-capacity lithium battery energy storage system, to ensure that the data acquisition terminal can operate stably for a long time without an external power supply.

[0035] Monitoring platform The cloud computing-based monitoring platform mainly includes: Cloud database: A highly reliable distributed database system is used to store the collected equipment operation data and environmental parameters.

[0036] Data processing and analysis module: Perform multivariate time series analysis based on machine learning algorithms (specifically using Python programming language and Scikit-learn machine learning library) for predictive maintenance analysis and anomaly detection, and generate equipment health status reports.

[0037] RESTful API server: The interface is used to receive and process data sent from the data acquisition terminal.

[0038] Bluetooth tag reading device: uses Bluetooth 5.0 technology to read the unique identification number in the Bluetooth tag, read the unique identification number in the Bluetooth tag, and transmit the data to the cloud database.

[0039] SMS Gateway: Using Twilio API, early warning information is sent to relevant maintenance personnel via SMS in real time to ensure that equipment abnormalities are handled in a timely manner.

[0040] Web interface: provides real-time monitoring and historical data query functions, supports access from mobile devices, and has data visualization, alarm notification, and inspection task management functions.

[0041] Wireless network coverage system LoRa Gateway: Using Semtech SX1301 chip, it covers the area where the coal mine electromechanical equipment is located through the LoRa wireless network, and connects to the cloud computing platform through Ethernet to achieve long-distance, low-power data transmission.

[0042] System workflow Inspection task generation and allocation The electromechanical equipment information is entered into the cloud computing platform, and the inspection tasks are entered and generated according to the inspection item classification. The system automatically generates the inspection plan and assigns tasks. The inspection plan includes the specific inspection time, inspection personnel, inspection equipment and inspection content.

[0043] Data collection and transmission The data acquisition terminal reads the unique identification number in the Bluetooth tag fixed on the electromechanical equipment through Bluetooth communication, and collects the operating parameters and environmental parameters of the equipment.

[0044] Inspection personnel fill in the inspection form through the data collection terminal according to the task arrangement of the monitoring platform, and generate inspection data after completion.

[0045] Inspection data is sent to the RESTful API server in real time via the LoRa wireless network and stored in the cloud database. The inspection table includes equipment operating status, environmental parameters, and inspection personnel's notes.

[0046] Data processing and analysis The data processing and analysis module processes and analyzes the received data in real time, generates equipment operation status reports and predictive maintenance recommendations, and generates trend analysis charts to monitor equipment status changes.

[0047] Perform predictive maintenance analysis through machine learning algorithms to generate equipment health status reports.

[0048] Abnormal warning When the monitoring platform detects abnormal operation of electromechanical equipment, it automatically sends an early warning message to relevant maintenance personnel through the SMS gateway. The early warning message includes the equipment number, abnormality type, recommended handling measures and emergency contact information.

[0049] Data export and report generation The monitoring platform provides data export function and supports multiple data formats, including CSV, Excel and PDF. The exported reports include equipment operation status, historical data trends and predictive maintenance recommendations for further analysis and decision support.

[0050] Trend Analysis The data processing and analysis module can generate trend analysis charts based on historical data. The trend analysis charts include equipment operation status trends, environmental parameter change trends and equipment failure prediction charts to help managers make equipment maintenance decisions. The charts support custom time ranges and parameter selections.

[0051] System Advantages Real-time monitoring: Real-time monitoring of device operating status and environmental parameters through the web interface and mobile devices.

[0052] Predictive maintenance: Multivariate time series analysis based on machine learning algorithms provides equipment failure prediction and maintenance recommendations.

[0053] Efficient communication: Adopt LoRa and Bluetooth low energy technology to achieve long-distance and low-power data transmission.

[0054] Sustainable operation: Solar power supply and high-efficiency lithium battery energy storage system ensure the continuous operation of the data collection terminal.

[0055] Comprehensive assessment: Collect environmental data through a variety of sensors to comprehensively assess the operating status of the equipment and the safety of the surrounding environment.

[0056] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0057] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0058] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A wireless monitoring system for coal mine electromechanical equipment maintenance, characterized in that The system includes: The data acquisition terminal based on Bluetooth low energy (BLE) module and LoRa wireless communication technology includes a sensor module, a Bluetooth module, a display screen and a Bluetooth tag fixed on the electromechanical equipment. The Bluetooth tag uses the Nordic nRF52832 chip. The sensor module may include a vibration sensor, a temperature sensor and a humidity sensor to collect the operating status of the electromechanical equipment. The cloud computing-based monitoring platform includes a cloud database, data processing and analysis module, RESTful API server, Bluetooth tag reader and SMS gateway. The Bluetooth tag reader uses Bluetooth 5.0 technology, and the SMS gateway uses TwilioAPI. The monitoring platform can process and store data from the data collection terminal in real time. The wireless network coverage system based on LoRa gateway generates LoRa wireless network through LoRa gateway. LoRa gateway adopts Semtech SX1301 chip. LoRa network covers the area where the electromechanical equipment of coal mine is located, and is connected to the cloud computing platform through Ethernet to ensure the stable transmission of data. The above systems are connected in the following ways: the cloud database, data processing and analysis module and RESTful API server are deployed on the cloud computing platform, the Bluetooth tag reading device and SMS gateway are connected to the cloud computing platform through the API interface, and the LoRa gateway covers the area where the coal mine electromechanical equipment is located through the LoRa wireless network and is connected to the cloud computing platform through Ethernet.

2. A coal mine electromechanical equipment maintenance wireless monitoring system according to claim 1, characterized in that: The data acquisition terminal also includes environmental sensors, which include gas sensors and light intensity sensors for collecting information such as temperature, humidity, gas concentration and light intensity in the coal mine environment, so as to more comprehensively monitor the safety status of the coal mine environment.

3. A coal mine electromechanical equipment maintenance wireless monitoring system according to claim 1, characterized in that: The monitoring platform also includes a data analysis module based on a machine learning algorithm. The data analysis module can perform multivariate time series analysis, and is used to perform predictive maintenance analysis and anomaly detection on the collected electromechanical equipment operation data, and provide equipment failure prediction and maintenance recommendations.

4. A coal mine electromechanical equipment maintenance wireless monitoring system according to claim 1, characterized in that: The data acquisition terminal adopts a solar power supply module and is equipped with a high-efficiency lithium battery energy storage system to reduce the frequency of battery replacement and ensure the continuous operation of the data acquisition terminal.

5. A coal mine electromechanical equipment maintenance wireless monitoring system according to claim 1, characterized in that: The monitoring platform provides real-time monitoring and historical data query functions through a Web interface and supports access from mobile devices. The Web interface has a user-friendly interactive interface and supports data visualization, alarm notification, and inspection task management functions.

6. A supervision method for a wireless supervision system for maintenance of electromechanical equipment in coal mines, characterized in that The method comprises the following steps: Enter the electromechanical equipment information on the cloud computing platform, enter and generate inspection tasks according to the inspection items, and the system automatically generates an inspection plan and assigns tasks. The inspection plan includes specific inspection time, inspection personnel, inspection equipment and inspection content; A unique identification number is stored in the Bluetooth tag fixed on the electromechanical equipment. The coal mine electromechanical equipment uses the unique identification number in the Bluetooth tag as identity authentication information. The data collection terminal reads the unique identification number in the Bluetooth tag through Bluetooth communication and submits it to the RESTful API server. The data collection terminal can also collect the operating parameters of the equipment. According to the task arrangement of the monitoring platform, the inspection personnel fill in the inspection form through the data collection terminal. After filling in, the inspection data is generated. The inspection data is sent to the RESTful API server in real time through the LoRa wireless network and stored in the cloud database. The inspection form includes the equipment operation status, environmental parameters and the inspection personnel's notes; The data processing and analysis module displays the transmitted data and generated charts in real time to observe the operating status of electromechanical equipment, and uses machine learning algorithms to perform predictive maintenance analysis and generate equipment health status reports.

7. A monitoring method for a wireless monitoring system for maintenance of electromechanical equipment in coal mines according to claim 6, characterized in that: The following steps are also included: When the monitoring platform detects abnormal operation of electromechanical equipment, it automatically sends an early warning message to relevant maintenance personnel through the SMS gateway. The early warning message includes the equipment number, abnormality type, recommended handling measures and emergency contact information.

8. A coal mine electromechanical equipment maintenance wireless monitoring system and monitoring method according to claim 6, characterized in that: The inspection data also includes environmental data collected by environmental sensors, including temperature, humidity, gas concentration and light intensity, so as to comprehensively evaluate the operating status of the electromechanical equipment and the safety of the surrounding environment.

9. A coal mine electromechanical equipment maintenance wireless monitoring system and monitoring method according to claim 6, characterized in that: The monitoring platform provides a data export function and supports multiple data formats, including CSV, Excel and PDF, so as to generate reports for further analysis and decision support. The exported reports include equipment operating status, historical data trends and predictive maintenance recommendations.

10. A coal mine electromechanical equipment maintenance wireless monitoring system and monitoring method according to claim 6, characterized in that: The data processing and analysis module can generate trend analysis charts based on historical data. The trend analysis charts include equipment operation status trends, environmental parameter change trends and equipment failure prediction charts to help managers make equipment maintenance decisions. The charts support custom time ranges and parameter selections.

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