Tunnel electromechanical equipment supervision method, equipment and medium

Abstract

The invention discloses a tunnel electromechanical equipment supervision method and device and a medium, and the method comprises the steps: carrying out the data collection of electromechanical equipment in a tunnel, so as to determine the state information of the electromechanical equipment, determining a preset equipment ledger, and recording the state information in the equipment ledger; determining historical data of the electromechanical equipment according to the equipment ledger, analyzing the historical data to obtain an operation mode of the electromechanical equipment, and determining an operation analysis model according to the operation mode; determining real-time data of the electromechanical equipment, and inputting the real-time data into the operation analysis model to determine a fault condition of the electromechanical equipment; and determining a fault type according to the fault condition, determining position information of the electromechanical equipment, determining a corresponding maintenance scheme according to the fault type and the position information, and maintaining the electromechanical equipment according to the maintenance scheme. Through real-time data acquisition and analysis of the electromechanical equipment in the tunnel, the state of the equipment is monitored in real time, and potential faults are found in time, so that preventive maintenance is implemented.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device and medium for monitoring tunnel electromechanical equipment. Background Art

[0002] With the rapid development of my country's economy, construction projects such as highway transportation are increasing day by day, among which the proportion of tunnel construction projects is increasing year by year. Tunnel construction, on the one hand, can shorten driving mileage, and on the other hand, can avoid huge damage to the ecological environment and alleviate the pressure of highway traffic operation.

[0003] However, due to the particularity of the tunnel environment, once the electromechanical equipment in the tunnel fails, the maintenance work is difficult and complicated, which may cause the information in the tunnel to be transmitted in a untimely manner, thus causing serious traffic paralysis problems. Summary of the invention

[0004] In order to solve the above problems, the present application proposes a supervision method for tunnel electromechanical equipment, including: collecting data on the electromechanical equipment in the tunnel to determine the status information of the electromechanical equipment, determining a pre-set equipment ledger, and recording the status information in the equipment ledger; determining the historical data of the electromechanical equipment according to the equipment ledger, analyzing the historical data to obtain the operation mode of the electromechanical equipment, and determining an operation analysis model according to the operation mode; determining the real-time data of the electromechanical equipment, inputting the real-time data into the operation analysis model to determine the fault condition of the electromechanical equipment; determining the fault type according to the fault condition, and determining the location information of the electromechanical equipment, determining the corresponding maintenance plan according to the fault type and the location information, and repairing the electromechanical equipment according to the maintenance plan.

[0005] In one example, the method also includes: determining location information of the electromechanical equipment, determining a collection plan based on the location information, the location information including the tunnel entrance and the inside of the tunnel; determining a corresponding collection frequency based on the collection plan, and starting a corresponding collection device to obtain the status information; determining a corresponding transmission plan based on the collection plan, and transmitting the status information to the equipment ledger based on the transmission plan.

[0006] In one example, the method further includes: determining an operating mode of the electromechanical equipment, the operating mode including a normal mode and an abnormal mode, and preprocessing the operating mode, the preprocessing including but not limited to data cleaning and normalization; grouping the operating modes after preprocessing to determine a training set and a test set, and training a preset neural network model based on the training set to obtain the operation analysis model, and testing the operation analysis model based on the test set.

[0007] In one example, determining the location information of the electromechanical equipment specifically includes: determining an acquisition mode of the sensor, and determining the number of devices corresponding to the sensor according to the acquisition mode, wherein the number of devices includes single and multiple; if the number of devices corresponding to the sensor is single, determining the location information according to the sensor; if the number of devices corresponding to the sensor is multiple, determining the acquisition range of the sensor, and determining the patrol equipment in the tunnel, and determining the location information according to the patrol equipment.

[0008] In one example, the fault type includes, but is not limited to, a damaging fault, a degenerative fault, a loose fault, and an imbalance fault.

[0009] In one example, determining the fault type according to the fault condition specifically includes: determining the equipment type of the electromechanical equipment, determining a corresponding fault detection scheme according to the equipment type, the fault detection scheme including but not limited to software analysis, appearance observation, vibration analysis, oil analysis, and X-ray detection; monitoring the electromechanical equipment according to the fault detection scheme to determine the fault type.

[0010] In one example, a corresponding maintenance plan is determined according to the fault type and the location information, specifically including: determining the maintenance equipment and maintenance personnel of the electromechanical equipment according to the fault type; determining the traffic status in the tunnel, and determining the maintenance time according to the location information and the traffic status.

[0011] In one example, the method further includes: determining associated equipment based on the faulty electromechanical equipment, determining maintenance records corresponding to the associated equipment, and determining historical fault causes based on the maintenance records; and inspecting and repairing the associated equipment based on the historical fault causes.

[0012] On the other hand, the present application also proposes a monitoring device for tunnel electromechanical equipment, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the monitoring device for tunnel electromechanical equipment can execute: data collection on the electromechanical equipment in the tunnel to determine the status information of the electromechanical equipment, determine a pre-set equipment ledger, and record the status information in the equipment ledger; determine the historical data of the electromechanical equipment according to the equipment ledger, analyze the historical data to obtain the operation mode of the electromechanical equipment, and determine the operation analysis model according to the operation mode; determine the real-time data of the electromechanical equipment, and input the real-time data into the operation analysis model to determine the fault condition of the electromechanical equipment; determine the fault type according to the fault condition, and determine the location information of the electromechanical equipment, determine the corresponding maintenance plan according to the fault type and the location information, and repair the electromechanical equipment according to the maintenance plan.

[0013] On the other hand, the present application also proposes a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured to: collect data on electromechanical equipment in a tunnel to determine status information of the electromechanical equipment, determine a pre-set equipment ledger, and record the status information in the equipment ledger; determine historical data of the electromechanical equipment based on the equipment ledger, analyze the historical data to obtain an operation mode of the electromechanical equipment, and determine an operation analysis model based on the operation mode; determine real-time data of the electromechanical equipment, input the real-time data into the operation analysis model to determine a fault condition of the electromechanical equipment; determine a fault type based on the fault condition, and determine the location information of the electromechanical equipment, determine a corresponding maintenance plan based on the fault type and the location information, and repair the electromechanical equipment based on the maintenance plan.

[0014] This application collects and analyzes real-time data of electromechanical equipment in the tunnel, monitors the status of the equipment in real time, and promptly detects potential faults, thereby implementing preventive maintenance and avoiding the impact of equipment failures on tunnel operations. The operation analysis model built based on the equipment operation mode and real-time data predicts and diagnoses the type of equipment failure, allowing maintenance personnel to quickly determine the maintenance plan based on the fault type and location information, improving maintenance efficiency and accuracy. The operation analysis model based on data analysis and machine learning models provides maintenance personnel with intelligent decision-making support to help them better understand and solve equipment failure problems. This application is applicable to different types of tunnel electromechanical equipment, and can be expanded and adjusted according to actual needs. It has strong flexibility and scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0016] Figure 1 A schematic diagram of a flow chart of a method for supervising tunnel electromechanical equipment in an embodiment of the present application;

[0017] Figure 2 This is a schematic diagram of a monitoring device for tunnel electromechanical equipment in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0019] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0020] like Figure 1 As shown, in order to solve the above problems, an embodiment of the present application provides a method for supervising tunnel electromechanical equipment, the method comprising:

[0021] S101. Collect data on electromechanical equipment in a tunnel to determine status information of the electromechanical equipment, determine a pre-set equipment ledger, and record the status information in the equipment ledger.

[0022] Sensors, such as temperature sensors, humidity sensors, vibration sensors, etc., are installed at the electromechanical equipment in the tunnel to monitor the operating environment and status information of the electromechanical equipment in real time. Using remote monitoring systems and Internet of Things technology, sensor data is collected in real time and transmitted to the server for processing. Status information includes but is not limited to the temperature, humidity, vibration, current, voltage, power, etc. of the equipment. By analyzing the status information, it is determined whether the equipment is in normal working condition and whether there are potential faults or abnormalities. The equipment ledger is a database or document that records the basic information, technical parameters, maintenance records, etc. of all electromechanical equipment in the tunnel. Create files for each device to facilitate managers to query and understand the details of the equipment. When a device fails, the cause of the problem can be quickly located based on the maintenance records and historical data in the ledger. By viewing the status information in the ledger, you can understand the operation of the electromechanical equipment in the tunnel in real time.

[0023] S102: determining historical data of the electromechanical equipment according to the equipment ledger, analyzing the historical data to obtain an operation mode of the electromechanical equipment, and determining an operation analysis model according to the operation mode.

[0024] By consulting the equipment ledger, we can obtain the operating data of electromechanical equipment in the past period of time. The purpose of analyzing historical data is to understand the operating rules, performance change trends and possible problems of electromechanical equipment. Through analysis, we can find out the performance of equipment under certain specific conditions, such as performance changes under high load, low temperature or high temperature environment. Based on the analysis of historical data, several typical operating modes of electromechanical equipment are summarized. These modes include normal operating mode, high load operating mode, abnormal operating mode, etc. Each operating mode has its specific data characteristics and performance. After understanding the operating mode of electromechanical equipment, a corresponding operation analysis model is constructed for each mode. This model is used to predict the performance of equipment under different modes, detect abnormal conditions in time, and provide decision support for maintenance personnel.

[0025] S103: Determine the real-time data of the electromechanical equipment, and input the real-time data into the operation analysis model to determine the fault condition of the electromechanical equipment.

[0026] Real-time data refers to the operating status, performance parameters and other information of electromechanical equipment at the current moment. This data is usually collected in real time through sensors installed on the equipment. The previously trained operation analysis model is loaded into the analysis system. These models may be built based on machine learning algorithms such as neural networks, support vector machines, and decision trees. The real-time data is input into the operation analysis model, and the model performs forward propagation calculations based on the input data, and outputs the current operating status of the equipment and possible failure risks. Possible states include normal operation, minor abnormalities, and serious abnormalities. The failure risk is a probability value that indicates the possibility of equipment failure, and the current operating status of the equipment and possible failure risks are obtained.

[0027] S104: Determine a fault type according to the fault condition, determine location information of the electromechanical device, determine a corresponding maintenance plan according to the fault type and the location information, and perform maintenance on the electromechanical device according to the maintenance plan.

[0028] According to the output results of the operation analysis model, the fault type of the electromechanical equipment is determined. The fault type may include destructive fault, degenerative fault, loose fault, disorder fault, etc. After determining the fault type, it is necessary to determine the specific location of the faulty equipment in the tunnel. After obtaining the fault type and location information, start to formulate a maintenance plan. The maintenance plan should include maintenance personnel, maintenance equipment, maintenance steps, and maintenance time.

[0029] In one embodiment, the location information of the electromechanical equipment is determined, and a collection plan is determined based on the location information, the location information includes the tunnel entrance and the inside of the tunnel; the corresponding collection frequency is determined based on the collection plan, and the corresponding collection device is started to obtain status information; the corresponding transmission plan is determined based on the collection plan, and the status information is transmitted to the equipment ledger based on the transmission plan.

[0030] In one embodiment, the operation mode of the electromechanical equipment is determined, and the operation mode includes a normal mode and an abnormal mode. The operation mode is preprocessed, and the preprocessing includes but is not limited to data cleaning and normalization processing; grouping is performed according to the preprocessed operation mode to determine the training set and the test set. Generally, the training set accounts for a larger proportion, such as 70% or 80%, and is used to train the neural network model; the test set accounts for a smaller proportion, such as 20% or 30%, and is used to evaluate the performance of the model. When dividing the data set, ensure that the data in the training set and the test set are randomly shuffled to avoid the model's dependence on a specific data order. According to the training set, a pre-set neural network model is trained, such as a convolutional neural network, and the number of layers of the network, the number of neurons in each layer, the activation function and other parameters are defined. The data in the training set is input into the neural network for forward propagation calculation. The output value of the network is obtained through the linear combination and activation function of each layer. The error between the output value of the network and the true value is calculated, that is, the loss function value. The loss function is used to measure the quality of the model prediction performance, and the mean square error, cross entropy loss and other functions are usually selected. The gradient of the loss function relative to the model parameters is calculated using the back propagation algorithm. Starting from the output layer, the error gradient of each neuron is calculated layer by layer, and the gradient information is propagated from the output layer back to the input layer. Based on the calculated gradient information, optimization algorithms such as stochastic gradient descent SGD, Adam, RMSprop, etc. are used to update the parameters of the model. The optimization algorithm adjusts the model parameters according to the gradient information to minimize the loss function value. Repeat the above steps, including forward propagation, loss function calculation, back propagation, and parameter update, until the performance of the model on the training set is stable or the preset number of training rounds is reached. Use the test set to evaluate the trained neural network model. Calculate the accuracy, recall rate and other indicators of the model on the test set to evaluate the generalization ability of the model. According to the evaluation results on the test set, tune the model. Adjust the network architecture, optimization algorithm, learning rate and other parameters to improve the performance of the model, and finally obtain the running analysis model.

[0031] In one embodiment, the acquisition mode of the sensor is determined, and the number of devices corresponding to the sensor is determined based on the acquisition mode, and the number of devices includes single and multiple. If the number of devices corresponding to the sensor is single, the location information is determined based on the sensor. If the number of devices corresponding to the sensor is multiple, the acquisition range of the sensor is determined, and the patrol equipment in the tunnel is determined, and the location information is determined based on the patrol equipment.

[0032] In one embodiment, the device type of the electromechanical equipment is determined, and a corresponding fault detection scheme is determined based on the device type. The fault detection scheme includes but is not limited to software analysis, appearance observation, vibration analysis, oil analysis, and X-ray detection; the electromechanical equipment is monitored according to the fault detection scheme to determine the fault type.

[0033] In one embodiment, maintenance equipment and maintenance personnel for the electromechanical equipment are determined according to the fault type; the traffic status in the tunnel is determined, and the maintenance time is determined according to the location information and the traffic status.

[0034] In one embodiment, the associated equipment is determined according to the failed electromechanical equipment, the maintenance records corresponding to the associated equipment are determined, and the historical fault causes are determined according to the maintenance records; the associated equipment is inspected and repaired according to the historical fault causes.

[0035] like Figure 2 As shown, the embodiment of the present application also provides a monitoring device for tunnel electromechanical equipment, including:

[0036] at least one processor; and,

[0037] a memory communicatively connected to at least one processor; wherein,

[0038] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor to enable a supervisory device for tunnel electromechanical equipment to execute:

[0039] Collecting data on electromechanical equipment in the tunnel to determine status information of the electromechanical equipment, determining a pre-set equipment ledger, and recording the status information in the equipment ledger;

[0040] Determining historical data of the electromechanical equipment according to the equipment ledger, analyzing the historical data to obtain an operation mode of the electromechanical equipment, and determining an operation analysis model according to the operation mode;

[0041] Determining real-time data of the electromechanical device, and inputting the real-time data into the operation analysis model to determine a fault condition of the electromechanical device;

[0042] The fault type is determined according to the fault condition, and the location information of the electromechanical equipment is determined. A corresponding maintenance plan is determined according to the fault type and the location information, so as to repair the electromechanical equipment according to the maintenance plan.

[0043] The embodiment of the present application further provides a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured as follows:

[0044] Collecting data on electromechanical equipment in the tunnel to determine status information of the electromechanical equipment, determining a pre-set equipment ledger, and recording the status information in the equipment ledger;

[0045] Determining historical data of the electromechanical equipment according to the equipment ledger, analyzing the historical data to obtain an operation mode of the electromechanical equipment, and determining an operation analysis model according to the operation mode;

[0046] Determining real-time data of the electromechanical device, and inputting the real-time data into the operation analysis model to determine a fault condition of the electromechanical device;

[0047] The fault type is determined according to the fault condition, and the location information of the electromechanical equipment is determined. A corresponding maintenance plan is determined according to the fault type and the location information, so as to repair the electromechanical equipment according to the maintenance plan.

[0048] In the 1990s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method flow). However, with the development of technology, many improvements to the method flow today can be regarded as direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0049] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0050] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0051] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0052] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0053] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0054] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0055] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0056] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0057] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0058] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0059] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0060] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0061] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0062] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for supervising tunnel electromechanical equipment, characterized in that: include: Collecting data on electromechanical equipment in the tunnel to determine status information of the electromechanical equipment, determining a pre-set equipment ledger, and recording the status information in the equipment ledger; Determining historical data of the electromechanical equipment according to the equipment ledger, analyzing the historical data to obtain an operation mode of the electromechanical equipment, and determining an operation analysis model according to the operation mode; Determining real-time data of the electromechanical device, and inputting the real-time data into the operation analysis model to determine a fault condition of the electromechanical device; The fault type is determined according to the fault condition, and the location information of the electromechanical equipment is determined. A corresponding maintenance plan is determined according to the fault type and the location information, so as to repair the electromechanical equipment according to the maintenance plan.

2. The method according to claim 1, characterized in that The method further comprises: Determine the location information of the electromechanical equipment, and determine a collection plan according to the location information, wherein the location information includes a tunnel entrance and a tunnel interior; Determine a corresponding acquisition frequency according to the acquisition scheme, and start a corresponding acquisition device to obtain the status information; A corresponding transmission scheme is determined according to the collection scheme, and the status information is transmitted to the device ledger according to the transmission scheme.

3. The method according to claim 1, characterized in that The method further comprises: Determine an operation mode of the electromechanical device, the operation mode including a normal mode and an abnormal mode, and preprocess the operation mode, the preprocessing including but not limited to data cleaning and normalization processing; The preprocessed operation modes are grouped to determine a training set and a test set, and a preset neural network model is trained according to the training set to obtain the operation analysis model, and the operation analysis model is tested according to the test set.

4. The method according to claim 1, characterized in that: Determining the location information of the electromechanical equipment specifically includes: Determine a collection mode of the sensor, and determine the number of devices corresponding to the sensor according to the collection mode, where the number of devices includes a single device and a plurality of devices; If the number of devices corresponding to the sensor is single, determining the location information according to the sensor; If the sensor corresponds to multiple devices, the collection range of the sensor is determined, and the inspection equipment in the tunnel is determined, and the location information is determined according to the inspection equipment.

5. The method according to claim 1, characterized in that The fault types include, but are not limited to, destructive faults, degenerative faults, loose faults, and imbalance faults.

6. The method according to claim 1, characterized in that Determine the fault type according to the fault condition, including: Determine the device type of the electromechanical device, and determine a corresponding fault detection scheme according to the device type, wherein the fault detection scheme includes but is not limited to software analysis, appearance observation, vibration analysis, oil analysis, and radiographic detection; The electromechanical device is monitored according to the fault detection scheme to determine the fault type.

7. The method according to claim 1, characterized in that Determining a corresponding maintenance plan according to the fault type and the location information specifically includes: Determining maintenance equipment and maintenance personnel for the electromechanical equipment according to the fault type; The traffic status in the tunnel is determined, and a maintenance time is determined according to the location information and the traffic status.

8. The method according to claim 1, characterized in that The method further comprises: Determine associated equipment according to the electromechanical equipment that has failed, determine maintenance records corresponding to the associated equipment, and determine historical fault causes according to the maintenance records; The associated equipment is inspected and repaired according to the historical fault causes.

9. A monitoring device for tunnel electromechanical equipment, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the monitoring device of the tunnel electromechanical equipment to execute: Collecting data on electromechanical equipment in the tunnel to determine status information of the electromechanical equipment, determining a pre-set equipment ledger, and recording the status information in the equipment ledger; Determining historical data of the electromechanical equipment according to the equipment ledger, analyzing the historical data to obtain an operation mode of the electromechanical equipment, and determining an operation analysis model according to the operation mode; Determining real-time data of the electromechanical device, and inputting the real-time data into the operation analysis model to determine a fault condition of the electromechanical device; The fault type is determined according to the fault condition, and the location information of the electromechanical equipment is determined. A corresponding maintenance plan is determined according to the fault type and the location information, so as to repair the electromechanical equipment according to the maintenance plan.

10. A non-volatile computer storage medium storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Collecting data on electromechanical equipment in the tunnel to determine status information of the electromechanical equipment, determining a pre-set equipment ledger, and recording the status information in the equipment ledger; Determining historical data of the electromechanical equipment according to the equipment ledger, analyzing the historical data to obtain an operation mode of the electromechanical equipment, and determining an operation analysis model according to the operation mode; Determining real-time data of the electromechanical device, and inputting the real-time data into the operation analysis model to determine a fault condition of the electromechanical device; The fault type is determined according to the fault condition, and the location information of the electromechanical equipment is determined. A corresponding maintenance plan is determined according to the fault type and the location information, so as to repair the electromechanical equipment according to the maintenance plan.

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