Digital twinning system construction method for mining working face and digital twinning method

Abstract

The digital twinning system construction method comprises the following steps: S1, acquiring equipment operation state data, environmental parameter data and visual and spatial perception data in real time to obtain a time sequence data set, the time sequence data set comprises equipment operation state data, environment parameter data, visual and spatial perception data and auxiliary data corresponding to each moment; s2, performing marginalization processing on the time sequence data set obtained in the S1 to obtain a preprocessed time sequence data set; and S3, modeling equipment for collecting equipment operation state data, environmental parameter data and visual and spatial perception data to obtain a virtual environment of the mining working face, and mapping the preprocessed time sequence data set and the virtual environment of the mining working face to obtain a digital twin system of the mining working face. The method can achieve the full-dimensional monitoring, improves the efficiency, improves the fault diagnosis accuracy, reduces the maintenance cost, and is suitable for a more complex mine scene.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of mine equipment control, and particularly relates to a digital twin system construction method and a digital twin method for a mining working face. BACKGROUND

[0002] In the process of underground coal mining, the coal mining machine is prone to failure, and the underground conditions are complex and difficult to repair, so the failure of the coal mining machine will hinder the process of coal mining, resulting in reduced production, and even threaten the life safety of underground personnel.

[0003] The existing monitoring system has single data: it relies on traditional sensors and lacks multi-source information fusion of environmental data, image data, etc.; static model: data processing and fault prediction rely on preset rules, which are difficult to adapt to complex working conditions; control lag: lack of real-time dynamic adjustment capability, and weak remote interaction function. SUMMARY

[0004] To solve the above problems, the application provides a digital twin system construction method and a digital twin method for a mining working face, which solves the problems of single data, difficulty in adapting to complex working conditions, and lack of real-time dynamic adjustment.

[0005] To achieve the above-mentioned purposes, the technical solutions adopted by the application include:

[0006] A digital twin system construction method for a mining working face, comprising the following steps:

[0007] S1, real-time acquisition of equipment running state data, environmental parameter data and visual and spatial perception data to obtain a time series data set, the time series data set comprising corresponding equipment running state data, environmental parameter data, visual and spatial perception data and auxiliary data at each time; the equipment running state data comprising coal mining machine motor housing vibration data, scraper conveyor drive part vibration data, coal mining machine cutting motor temperature data, hydraulic pump station oil tank temperature data, hydraulic support pressure data, conveyor drive chain wheel linear velocity data, hydraulic support angle deflection data and coal mining machine and conveyor motor power supply input end voltage data; the environmental parameter data comprising dust concentration data, gas concentration data, humidity data and oxygen data of the mining working face; the visual and spatial perception data comprising mining working face image data, roof subsidence amount and roadway convergence deformation data and temperature data of the coal mining machine cutting part and conveyor drive motor housing;

[0008] S2, edge processing of the time series data set obtained in S1 to obtain a preprocessed time series data set;

[0009] S3, modeling the device for collecting device running state data, environment parameter data and visual and spatial perception data, obtaining a virtual environment of the mining face, and mapping the preprocessed time series data set and the virtual environment of the mining face to obtain a digital twin system of the mining face.

[0010] A digital twin method of a mining face, device running state data, environment parameter data and visual and spatial perception data are obtained and input into the digital twin system of the mining face constructed by the present application.

[0011] Compared with the prior art, the advantages of the present application are:

[0012] The digital twin system construction method and digital twin method of the mining face of the present application can monitor in full dimension, realize real-time adjustment of device running parameters through edge computing and feedback control, improve efficiency, improve fault diagnosis accuracy, reduce maintenance cost, and are suitable for more complex mine scenes. DETAILED DESCRIPTION

[0013] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below, and the described embodiments should not be regarded as limiting the present application. All other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0014] In the following description, "some embodiments" are related to a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. Unless otherwise defined, all technical and scientific terms used in the embodiments of the present application have the same meaning as understood by those skilled in the art to which the embodiments of the present application belong. The terms used in the embodiments of the present application are only for the purpose of describing the embodiments of the present application, and are not intended to limit the present application.

[0015] EMBODIMENTS

[0016] The present embodiment provides a digital twin system construction method of a mining face, comprising the following steps:

[0017] S1, real-time collection of device running state data, environment parameter data and visual and spatial perception data to obtain a time series data set, the time series data set comprising corresponding device running state data, environment parameter data, visual and spatial perception data and auxiliary data at each time;

[0018] The device operating state data includes coal winning machine motor shell vibration data, scraper conveyor drive part vibration data, coal winning machine cutting motor temperature data, hydraulic pump station oil tank temperature data, hydraulic support pressure data, conveyor drive chain wheel linear velocity data, hydraulic support angle deflection data, and coal winning machine and conveyor motor power input voltage data;

[0019] The environmental parameter data includes dust concentration data, gas concentration data, humidity data, and oxygen data of the mining working face;

[0020] The visual and spatial perception data includes mining working face image data, roof subsidence amount and roadway convergence deformation data, and temperature data of the coal winning machine cutting part and conveyor drive motor shell;

[0021] S2, edge processing is performed on the time series data set obtained in S1 to obtain a preprocessed time series data set;

[0022] The edge processing of the embodiment adopts a real-time noise reduction algorithm combining wavelet transform and LSTM to dynamically eliminate noise.

[0023] S3, the devices for collecting device operating state data, environmental parameter data, and visual and spatial perception data are modeled to obtain a virtual environment of the mining working face, and the preprocessed time series data set and the virtual environment of the mining working face are mapped to obtain a digital twin system of the mining working face.

[0024] The device for collecting device operating state data of the embodiment includes a vibration sensor, a temperature sensor, a pressure sensor, a linear velocity sensor, an angle sensor, a current and voltage sensor, the vibration sensor is installed on the coal winning machine motor shell and the scraper conveyor drive part, is used for monitoring the vibration frequency and amplitude of key components such as the coal winning machine cutting part and the conveyor bearing, is used for detecting mechanical looseness, wear or imbalance failure, the temperature sensor is installed on the coal winning machine cutting motor and the hydraulic pump station oil tank, is used for collecting temperature data of parts such as motor winding and hydraulic system oil temperature in real time, prevents overheating from causing equipment damage or fire, the pressure sensor is installed on the hydraulic support stand column and the hydraulic valve interface, is used for measuring the support pressure of the hydraulic support and the hydraulic pipeline pressure, ensures the stability and safety of the support system, the linear velocity sensor is installed near the conveyor drive chain wheel, is used for monitoring the chain running speed of the scraper conveyor, prevents equipment failure caused by chain jamming or overspeed, the angle sensor is installed on the hydraulic support roof beam and the coal winning machine rocker arm joint, is used for detecting the inclination angle of the hydraulic support and the pitch angle of the coal winning machine rocker arm, ensures that the device posture meets the safety specification, and the current and voltage sensor is installed on the power input end of the coal winning machine and the conveyor motor, is used for monitoring the motor working current and voltage, analyzing the load state and energy consumption, and preventing overload or short circuit.

[0025] The device for collecting environmental parameter data of the embodiment includes a dust concentration sensor, a gas concentration sensor, a humidity sensor, and an oxygen sensor. The dust concentration sensor is installed behind the cutting drum of the coal mining machine and in the return airway of the working face, and is used to detect the dust concentration in the air of the working face in real time, trigger the spray dust reduction system, and ensure the safety of the breathing of the operating personnel. The gas concentration sensor is installed in the air inlet of the working face and the sealed area of the goaf, and is used to monitor the methane concentration in the mine. When the concentration exceeds the threshold, an alarm is triggered and the ventilation system is started. The humidity sensor is installed on the operating table of the hydraulic support and the transfer point of the conveyor, and is used to detect the environmental humidity to prevent the equipment from being short-circuited due to moisture or the working face from being muddy due to excessive spraying. The oxygen sensor is installed in the working area of the working face and the intersection of the roadway, and is used to monitor the oxygen content in the mine to prevent the threat of anoxic environment to personnel safety.

[0026] The device for collecting visual and spatial perception data of the embodiment includes an industrial explosion-proof camera, a laser displacement sensor, and an infrared thermal imager. The industrial explosion-proof camera is installed on the top of the coal mining machine body, the top beam of the hydraulic support, and the roadway roof, and is used to capture images of the working face in real time for visual monitoring of the running state of the equipment, analysis of personnel behavior, and accident tracing. The laser displacement sensor is installed at the monitoring point of the roadway roof and the advanced support area of the working face, and is used to measure the subsidence of the roof and the convergence deformation of the roadway to warn of the risk of collapse. The infrared thermal imager is installed on the cutting part of the coal mining machine and the drive motor housing of the conveyor, and is used to detect the temperature distribution on the surface of the equipment in a non-contact manner to identify local overheating faults such as abnormal heating of bearings.

[0027] When mining coal, if the vibration sensor detects abnormal high-frequency vibration of the cutting part bearing and the infrared thermal imager shows that the bearing temperature has risen to 85°C, the edge node removes noise through wavelet transform, extracts vibration frequency spectrum features, and the digital twin fuses vibration and temperature data to trigger the CNN-LSTM model to predict the remaining life of the bearing. The digital twin determines that the bearing wear degree has reached 90%, pushes a replacement work order to the AR terminal, and automatically reduces the cutting speed to a safety threshold. The device can collect full-dimensional data from equipment operation, environmental safety, and spatial perception. The sensor data interacts with the digital twin and the control system in real time to realize active early warning and dynamic adjustment, and can accurately perceive complex underground conditions to provide high-quality data support for digital twin modeling and intelligent control.

[0028] When the digital twin predicts an increase in cutting resistance, it is recommended to reduce the rotation speed to 2.0 m / s. The central controller calls the reinforcement learning algorithm and generates optimal control parameters in combination with the current load to generate control instructions. The 5G module sends a PWM speed signal to the shearer frequency converter to realize instruction issuance. The AR glasses display "the rotation speed has been adjusted to 2.0 m / s", the voice broadcast confirms the instruction execution, the operation monitor interacts to confirm the instruction, the authority system verifies the operator's identity, records the operation log to the database, and the 5G communication + edge control realizes millisecond-level response to avoid control lag. Voice, gesture, and AR interface reduce the operation difficulty in the complex underground environment. The intelligent control and interaction layer realizes precise control and efficient human-machine collaboration of coal mining equipment, providing core support for intelligent mining.

[0029] When the laser displacement sensor detects a sudden increase in roof displacement rate to 6 mm / min, the digital twin ST-GCN model combines historical data to determine high risk, and the warning trigger displays a red warning on the AR interface. The audible and visual alarm starts, automatically sends a stop command to the shearer PLC controller, and the UWB positioning system forces personnel in the dangerous area to evacuate. The roof support equipment is started, the hydraulic support is pressurized to 20 MPa, the authority system verifies the operator's identity, the event data is stored in the log, and the optimization model provides 10-minute early warning for similar risks. It can integrate gas, displacement, and personnel positioning data to improve warning accuracy, trigger different measures according to risk levels, avoid excessive intervention, quickly link, and continuously update the knowledge graph. The model prediction accuracy improves with data accumulation, the processing flow cooperates with the equipment, the safety situation awareness and emergency layer can significantly reduce the accident rate in the coal mine, and ensure the safety of personnel and equipment.

[0030] The above is only an embodiment of the present application and is not intended to limit the protection scope of the present application. Any modifications, equivalent replacements, and improvements made within the spirit and scope of the present application are included in the protection scope of the present application.

[0031] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures, or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that the size of the sequence number of each process in various embodiments of the present application does not mean the order of execution. The execution order of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The sequence number of the above embodiments of the present application is only for description, not representing the advantages and disadvantages of the embodiments.

[0032] It should be noted that, in the present document, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element preceded by "comprises... a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the recited element. In the several embodiments provided in the present document, it is to be understood that the disclosed devices and methods can be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the units is only a logical function division, and in actual implementation, there can be another division manner, for example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0033] The above description is merely specific implementation of the present document, but the protection scope of the present document is not limited thereto, any skilled person in the art can easily think of changes or replacements within the technical range disclosed by the present document, which should be covered in the protection scope of the present document. Therefore, the protection scope of the present document should be subject to the protection scope of the claims.

Claims

1. A method for constructing a digital twin system of a mining face, characterized in that, Comprising the following steps: S1, collecting device running state data, environmental parameter data and visual and spatial perception data in real time to obtain a time series data set, the time series data set comprising corresponding device running state data, environmental parameter data, visual and spatial perception data and auxiliary data at each time; The device running state data comprises coal mining machine motor shell vibration data, scraper conveyor drive part vibration data, coal mining machine cutting motor temperature data, hydraulic pump station oil tank temperature data, hydraulic support pressure data, conveyor drive chain wheel linear velocity data, hydraulic support angle deflection data and coal mining machine and conveyor motor power input end voltage data; The environmental parameter data comprises dust concentration data, gas concentration data, humidity data and oxygen data of the mining and excavation working face; The visual and spatial perception data comprises mining and excavation working face image data, roof subsidence amount and roadway convergence deformation data and temperature data of the coal mining machine cutting part and conveyor drive motor shell; S2, performing edge processing on the time series data set obtained in S1 to obtain a preprocessed time series data set; S3, modeling the device for collecting device running state data, environmental parameter data and visual and spatial perception data to obtain a virtual environment of the mining and excavation working face, and mapping the preprocessed time series data set and the virtual environment of the mining and excavation working face to obtain a digital twin system of the mining and excavation working face.

2. A method of digital twinning of a mining face, characterized by, Obtaining device running state data, environmental parameter data and visual and spatial perception data and inputting the digital twin system of the mining and excavation working face constructed in claim 1.