A coal mining machine fault diagnosis method, device, equipment and storage medium

Abstract

The application provides a coal mining machine fault diagnosis method, device, equipment and storage medium, which is applied to a computer device, and the method comprises the following steps: acquiring coal mining machine fault part information; acquiring sensor information of each key position installed on the coal mining machine fault part, and performing information fusion of multiple sensors to obtain first data; acquiring information of each key position installed on the coal mining machine fault part when the sensor is normally working, and fusing the information of multiple sensors when the sensor is normally working to obtain second data; comparing the first data and the second data, generating and displaying first diagnosis information. The application has the technical effect that the situation that the coal mine stops production, the whole coal mine production system is paralyzed, and manpower and financial resources are wasted due to the failure to timely eliminate faults is avoided as much as possible.

Description

Technical Field

[0001] This application relates to the field of coal mining machine fault diagnosis technology, specifically to a coal mining machine fault diagnosis method, device, equipment, and storage medium. Background Technology

[0002] Coal mining machines, as core equipment in coal production, have received widespread attention. However, due to their complex and harsh working environment and significant load variations, some key components are prone to overload and malfunction during production. Furthermore, their complex structure makes the causes of failure equally complex. A failure in a coal mining machine means the mine shuts down, paralyzing the entire mine's production system and resulting in a waste of human and financial resources.

[0003] Therefore, there is an urgent need for a method, device, equipment, and storage medium for diagnosing coal mining machine faults, so as to accurately and promptly eliminate faults after they occur, and to avoid situations where failure to eliminate faults in a timely manner leads to coal mine shutdowns, paralysis of the entire coal mine production system, and waste of human and financial resources. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and storage medium for diagnosing faults in coal mining machines. It aims to minimize the risk of mine shutdowns, paralysis of the entire coal mine production system, and significant waste of human and financial resources due to failure to promptly resolve faults.

[0005] In a first aspect, this application provides a method for diagnosing faults in a coal mining machine, applied to a computer device. The method includes: acquiring information about the fault location of the coal mining machine; acquiring sensor information installed at various key locations on the fault location of the coal mining machine, and performing multi-sensor information fusion to obtain first data; acquiring information about the sensors installed at various key locations on the fault location of the coal mining machine when they are working normally, and fusing the information about the sensors when they are working normally to obtain second data; comparing the first data and the second data to generate and display first diagnostic information.

[0006] By adopting the above technical solution, when a fault is detected in the coal mining machine, the location of the fault is obtained. Sensor information from various key locations on the faulty part of the coal mining machine is acquired and fused. Since the sensors at various key locations on the faulty part are interconnected and have certain relationships, the information from multiple sensors is fused to obtain the first data. Then, the information from the sensors under normal conditions is fused to obtain the second data. By comparing the first data and the second data, the cause of the fault can be obtained. The diagnosis result is accurate, and the failure to eliminate the fault in time can be avoided, which may lead to the shutdown of the coal mine, the paralysis of the entire coal mine production system, and the waste of human and financial resources.

[0007] Optionally, the step of obtaining the fault location of the coal mining machine includes: the coal mining machine includes a cutting section, a loading section, and a traveling section; when the values ​​of sensors in any one or more parts of the cutting section, the loading section, and the traveling section are not within a preset range, the location of the sensor whose value is not within the preset range is determined, thereby determining the fault location of the coal mining machine; and obtaining the fault location information of the coal mining machine.

[0008] By adopting the above technical solution, since the coal mining machine is composed of multiple parts, sensors are set at key positions in each part. When the vibration value of any one or more sensors is not within the first preset range, the fault location of the coal mining machine can be determined. The whole process does not require manual intervention, thus achieving automation, and the detection method is fast and accurate.

[0009] Optionally, after acquiring the information of the sensors installed at each key location on the faulty part of the coal mining machine when they are working normally, the method further includes: acquiring the waveform diagram of the sensor information at each key location in real time; comparing the waveform diagram of the sensor at each key location with the standard waveform diagram of the sensor at each key location; and if there is a difference between the waveform diagram of the sensor at each key location and the standard waveform diagram, sending an early warning message to enable maintenance personnel to carry out maintenance.

[0010] By adopting the above technical solution, and comparing the waveforms of sensors at each critical location with their standard waveforms, any discrepancies are considered indicative of a fault. An early warning message is then sent to the maintenance personnel's terminal equipment, facilitating timely repairs. This approach aims to minimize the risk of mine shutdowns, paralysis of the entire mine's production system, and waste of human and financial resources due to failure to promptly resolve faults.

[0011] Optionally, after acquiring the waveforms of the sensor information at each key location in real time, the method further includes: calculating the overall trend curve of the waveforms of the sensors at each key location; predicting the possible failure of the coal mining machine based on the overall trend curve, and sending the prediction information to the terminal equipment of the maintenance personnel.

[0012] By adopting the above technical solution, the overall trend curve of the waveform of the sensors at each key location is calculated. Based on the overall trend curve, the possible failures of the coal mining machine can be predicted, problems can be detected in advance, and the situation of coal mine shutdown due to coal mining machine failure, resulting in the paralysis of the entire coal mine production system and the waste of human and financial resources can be avoided as much as possible.

[0013] Optionally, the method further includes: obtaining the associated part of the faulty part of the coal mining machine; obtaining the working data of the associated part to obtain third data; combining the first data and the third data to obtain fourth data; combining the second data and the third data to obtain fifth data; comparing the fourth data and the fifth data to generate and display second diagnostic information.

[0014] By adopting the above technical solution, since the coal mining machine consists of multiple parts that are interconnected and whose working data are also interconnected, when any part malfunctions, the cause of the malfunction can be determined by detecting other parts. This improves detection efficiency and the accuracy of fault diagnosis, and minimizes the occurrence of fault diagnosis errors, which could lead to repeated diagnoses and waste of manpower and resources.

[0015] Optionally, after comparing the first data and the second data, the method further includes: if the displayed diagnostic information is not generated; sending a diagnostic request to the maintenance personnel's terminal device so that the maintenance personnel can diagnose the cause of the coal mining machine malfunction and store the cause of the coal mining machine malfunction.

[0016] By adopting the above technical solution, since computer equipment may not be able to diagnose the cause of the current coal mining machine failure, maintenance personnel will be notified in a timely manner when an undiagnosable failure occurs. This will help to avoid situations where failure to eliminate the fault in time leads to coal mine shutdown, paralysis of the entire coal mine production system, and a significant waste of human and financial resources.

[0017] Optionally, if the diagnostic information is not generated, the method further includes: sending detection information to the maintenance personnel's terminal device so that the maintenance personnel can detect the sensors installed at various key locations on the faulty part of the coal mining machine and determine the sensor fault and / or the coal mining machine fault.

[0018] By adopting the above technical solution, since the sensors also have their own faults, when abnormal sensor data is detected, it is necessary to notify maintenance personnel to conduct inspections and determine the sensor fault and / or coal mining machine fault, so as to avoid misjudgment and waste of manpower and resources.

[0019] Secondly, this application provides a coal mining machine fault diagnosis device, the device comprising an acquisition module, a fusion module, and a comparison module; wherein, the acquisition module is used to acquire information on the fault location of the coal mining machine; acquire sensor information installed at various key locations on the fault location of the coal mining machine; acquire information on the normal operation of the sensors installed at various key locations on the fault location of the coal mining machine; the fusion module is used to perform multi-sensor information fusion to obtain first data; fuse the information from the normal operation of the multiple sensors to obtain second data; the comparison module is used to compare the first data and the second data, and generate and display first diagnostic information.

[0020] By adopting the above technical solution, when a fault is detected in the coal mining machine, the location of the fault is obtained. Sensor information from various key locations on the faulty part of the coal mining machine is acquired and fused together. Since the sensors at various key locations on the faulty part are interconnected and have certain relationships, the information from multiple sensors is fused to obtain the first data. Then, the information from the sensors under normal conditions is fused to obtain the second data. By comparing the first data and the second data, the cause of the fault can be determined. The diagnosis result is accurate, and the failure to eliminate the fault in time can be avoided, which could lead to the shutdown of the coal mine, the paralysis of the entire coal mine production system, and a great waste of human and financial resources.

[0021] Thirdly, this application provides an electronic device that adopts the following technical solution: it includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a computer program such as any of the interview matching degree judgment methods described above.

[0022] Fourthly, this application provides a computer-readable storage medium that stores a computer program capable of being loaded by a processor and executing any of the above-mentioned interview matching degree judgment methods.

[0023] In summary, this application includes at least one of the following beneficial technical effects:

[0024] 1. Try to avoid situations where failure to troubleshoot in a timely manner leads to coal mine shutdowns, paralysis of the entire coal mine production system, and waste of human and financial resources;

[0025] 2. By detecting other locations to determine the cause of the fault, the detection efficiency and the accuracy of fault diagnosis are improved, and the situation of fault diagnosis errors, repeated diagnosis, and waste of manpower and resources is avoided as much as possible. Attached Figure Description

[0026] Figure 1This is a flowchart illustrating a method for diagnosing a coal mining machine fault according to an embodiment of this application;

[0027] Figure 2 This is a schematic diagram of the structure of a coal mining machine fault diagnosis device according to an embodiment of this application;

[0028] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0029] Explanation of reference numerals in the attached figures: 1. Acquisition module; 2. Fusion module; 3. Comparison module; 1000. Electronic device; 1001. Processor; 1002. Communication bus; 1003. User interface; 1004. Network interface; 1005. Memory. Detailed Implementation

[0030] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0031] In the description of the embodiments in this application, words such as "illustrative," "for example," or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "illustrative," "for example," or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of words such as "illustrative," "for example," or "for example" is intended to present the relevant concepts in a specific manner.

[0032] Figure 1 This is a flowchart illustrating a method for diagnosing faults in a coal mining machine according to an embodiment of this application. It should be understood that, although... Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows; unless explicitly stated otherwise, there is no strict order requirement for the execution of these steps, and they can be executed in other orders; and Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0033] This application discloses a method for diagnosing faults in a coal mining machine, such as... Figure 1 As shown, the method includes S1-S4.

[0034] S1, obtain information on the fault location of the coal mining machine.

[0035] In a typical example, a coal mining machine consists of a cutting section, a loading section, a traveling section, an electric motor, an operation control system, and auxiliary devices. The cutting section, loading section, and traveling section are all located at the coal mining site. The working process of the coal mining machine is as follows: while the left and right cutting drums of the cutting section rotate, the coal mining machine moves left or right along the coal face. As the machine moves and the cutting drums rotate, coal is continuously cut from the coal face and falls onto the scraper conveyor in the loading section at the bottom of the machine. The scraper conveyor transports the cut coal, powered by the traveling section. Because the coal chunks cut by the cutting drums are sometimes too large for the scraper conveyor to transport, a crushing drum is also included on the coal mining machine to crush larger coal pieces. Due to the varying thickness of the coal seam, the front and rear cutting drums may sometimes need to be adjusted to cut coal seams of different thicknesses. Because of the complex mechanical structure of the various parts of the coal mining machine, it is easy for the computer to fail to detect the location of the fault when the machine malfunctions. In this solution, it is not necessary to obtain the exact location of the fault; it is sufficient to determine the area where the fault occurs. Alternatively, workers can directly transmit the exact location of the fault via their terminal devices.

[0036] The coal mining machine includes a cutting section, a loading section, and a traveling section. When the vibration value of the sensor in any one or more parts of the cutting section, loading section, and traveling section is not within a first preset range, the location of the sensor whose vibration value is not within the preset range is determined, thereby determining the fault location of the coal mining machine; and information on the fault location of the coal mining machine is obtained.

[0037] In one example, a coal mining machine typically consists of three parts working together at a coal mining site: a cutting section, a loading section, and a traveling section. Vibration sensors are installed at one or more locations within these three sections. Since each part of the machine has a vibration range during operation, if the vibration value of any vibration sensor is outside the set range, it is considered that the coal mining machine is malfunctioning. However, this method can only determine which of the three sections the malfunction occurs in, but it cannot determine the specific location and cause of the malfunction.

[0038] S2, acquire sensor information from various key locations installed on the faulty part of the coal mining machine, and perform multi-sensor information fusion to obtain the first data.

[0039] In one example, taking the cutting section as an example, the cutting section suffers from various common faults, such as slow arm descent, arm failure to rise, arm failure to descend, abnormal noises, and high temperature. Therefore, based on historical fault data of the cutting section, corresponding sensors are installed at corresponding locations. For example, temperature sensors are installed at locations with excessively high temperatures, and vibration sensors can be installed on the machine body. Obtaining sensor information from key locations on the faulty parts of the coal mining machine involves acquiring information from the aforementioned temperature and vibration sensors. Since the sensors at different locations are not independent but interconnected—for example, prolonged operation of the cutting section's engine causing the motor to heat up and affecting the vibration data of the vibration sensor, as well as the rotation speed of the cutting head—there is a connection between the sensors at different locations. Fusing the information from these sensors yields the first data, which can be understood as the total data obtained by integrating the data from all sensors.

[0040] S3: Obtain information from sensors installed at key locations on the faulty part of the coal mining machine when they are working normally, and fuse the information from multiple sensors when they are working normally to obtain the second data.

[0041] In one example, under the premise of S2, taking the cutting section as an example, the information of the sensors at each position of the cutting section when the cutting section is in a normal state is called. Similarly, the second data can be understood as integrating the information of the sensors at each position when the cutting section is in a normal state.

[0042] The system acquires waveforms from sensors at various key locations in real time; compares these waveforms with standard waveforms at each key location; and sends warning messages if discrepancies exist between the waveforms and the standard waveforms, prompting maintenance personnel to perform repairs.

[0043] In one example, in this application, the data from multiple sensors can be converted into waveforms using a computer or oscilloscope and displayed. By comparing the waveforms of the sensors during normal operation, if there is an error between the two waveforms, it indicates that the coal mining machine has a fault or potential danger. In this case, the location information of the corresponding sensor is sent to the mobile terminal of the maintenance personnel to facilitate maintenance.

[0044] Calculate the overall trend curve of the waveforms of sensors at each key location; based on the overall trend curve, predict possible failures of the coal mining machine and send the prediction information to the terminal equipment of maintenance personnel.

[0045] In one example, after obtaining the waveforms of sensors at various key locations, the computer calculates the overall trend curve of the waveforms, which is the prediction curve, to predict the current trend of the waveforms and thus predict potential failures of the coal mining machine. The potential failures are then sent to the mobile terminals of maintenance personnel to detect the relevant locations and nip potential risks in the bud.

[0046] S4. Compare the first data and the second data to generate and display the first diagnostic information.

[0047] In one example, comparing the first and second data can be understood as follows: first, all data in the first and second data are compared one by one to determine if there are any errors in each data. Then, by calling historical comparison data, the type of anomaly of the current fault can be determined. Then, the overall data can be compared. Since the data between the various sensors are interconnected, any abnormal data in any sensor will cause fluctuations in the remaining sensors. Therefore, by comparing the first and second data, the cause of the current fault can be found out, and the cause of the current fault can be displayed on the computer device.

[0048] Obtain working data from the relevant parts to obtain the third data; combine the first and third data to obtain the fourth data; combine the second and third data to obtain the fifth data; compare the fourth and fifth data to generate and display the second diagnostic information.

[0049] In one example, the coal mining machine includes a cutting section, a loading section, and a traveling section. The cutting section transfers the cut coal through the loading section, and then the traveling section adjusts its speed and provides traction. These three parts are interconnected. For example, if the cutting rate of the cutting head in the cutting section decreases, the amount of coal on the conveyor belt in the loading section will decrease, and its weight will also decrease. Therefore, the traveling section requires less power. Thus, all parts of the coal mining machine are interconnected, allowing for the integration of operational data from each part. This operational data can also be obtained from sensors, as explained in the above embodiments. The third data can be understood as acquiring data from the loading and traveling sections when the cutting section malfunctions, correlating them, and using historical data to determine the cause of the malfunction. Simultaneously, the second and third data can be combined—that is, combining the sensor data from each part when the coal mining machine is operating normally and comparing it with the combined sensor data when the coal mining machine malfunctions—to determine the cause and location of the malfunction.

[0050] If no diagnostic information is generated, a diagnostic request is sent to the maintenance personnel's terminal device so that the maintenance personnel can diagnose the cause of the coal mining machine malfunction and store the cause of the malfunction.

[0051] In one example, since computer equipment cannot detect all causes of a fault, when a fault occurs and the computer equipment fails to recognize the fault, the computer sends a diagnostic request to the maintenance personnel's terminal equipment. After the maintenance personnel detect the cause of the fault, they send the cause of the fault to the computer equipment and store it so that the cause of the fault can be diagnosed in a timely manner when the fault is found again.

[0052] The system sends detection information to the maintenance personnel's terminal equipment, enabling them to inspect the sensors installed at various critical locations on the faulty parts of the coal mining machine and determine sensor faults and / or coal mining machine faults.

[0053] In one example, the transmission of whether the coal mining machine is faulty is done through a sensor as an intermediary. Since the sensor itself may also fail due to special reasons, even if the coal mining machine is not faulty, it is necessary to also test the sensor to determine whether the fault is in the sensor or the coal mining machine.

[0054] This application also discloses a fault diagnosis device for a coal mining machine, such as... Figure 1 As shown, Figure 1 This is a schematic diagram of the structure of a coal mining machine fault diagnosis device according to an embodiment of this application.

[0055] A coal mining machine fault diagnosis device includes: an acquisition module 1, a fusion module 2, and a comparison module 3; wherein, the acquisition module 1 is used to acquire information about the fault location of the coal mining machine; acquire sensor information installed at various key locations on the fault location of the coal mining machine; acquire information when the sensors installed at various key locations on the fault location of the coal mining machine are working normally; the fusion module 2 is used to perform information fusion of multiple sensors to obtain first data; fuse the information when the multiple sensors are working normally to obtain second data; the comparison module 3 is used to compare the first data and the second data, and generate and display first diagnostic information.

[0056] In one example, module 1 is also used to determine the location of the sensor whose vibration value is not within the preset range when the vibration value of the sensor in any one or more parts of the cutting section, loading section and traveling section is not within the first preset range, thereby determining the fault location of the coal mining machine; and to obtain information on the fault location of the coal mining machine.

[0057] In one example, module 1 is also used to acquire waveforms of sensors at various key locations in real time; acquire the parts associated with the faulty parts of the coal mining machine; acquire the working data of the associated parts, and obtain third data.

[0058] In one example, fusion module 2 is also used to fuse the first data and the third data to obtain the fourth data; and to fuse the second data and the third data to obtain the fifth data.

[0059] In one example, the comparison module 3 is also used to compare the waveforms of the sensors at each key location with the standard waveforms of the sensors at each key location; if there is a difference between the waveforms of the sensors at each key location and the standard waveforms, an early warning message is sent so that maintenance personnel can carry out maintenance; the fourth data and the fifth data are compared to generate and display the second diagnostic information.

[0060] In one example, the device is also used to calculate the overall trend curve of the waveforms of sensors at various key locations; based on the overall trend curve, it predicts possible failures of the coal mining machine and sends the prediction information to the terminal equipment of maintenance personnel.

[0061] In one example, the device is also used to send a diagnostic request to the maintenance personnel's terminal device if no diagnostic information is generated, so that the maintenance personnel can diagnose the cause of the coal mining machine failure and store the cause of the coal mining machine failure.

[0062] In one example, the device is also used to send detection information to the maintenance personnel's terminal equipment so that the maintenance personnel can detect sensors installed at various key locations on the faulty part of the coal mining machine and determine sensor failure and / or coal mining machine failure.

[0063] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0064] Please see Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 3 As shown, the electronic device 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, a memory 1005, and at least one communication bus 1002.

[0065] The communication bus 1002 is used to realize the connection and communication between these components.

[0066] The user interface 1003 may include a display screen and a camera. Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface.

[0067] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0068] The processor 1001 may include one or more processing cores. The processor 1001 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 1005, and by calling data stored in the memory 1005. Optionally, the processor 1001 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 1001 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 1001 and may be implemented as a separate chip.

[0069] The memory 1005 may include random access memory (RAM) or read-only memory. Optionally, the memory 1005 may include a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 1005 may also be at least one storage device located remotely from the aforementioned processor 1001. Figure 3 As shown, the memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a coal mining machine fault diagnosis method.

[0070] exist Figure 3In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 1001 can be used to call an application program stored in the memory 1005 for a coal mining machine fault diagnosis method. When executed by one or more processors, the electronic device performs one or more of the methods described in the above embodiments.

[0071] An electronic device readable storage medium stores instructions that, when executed by one or more processors, cause the electronic device to perform one or more of the methods described in the above embodiments.

[0072] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0073] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0074] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some service interfaces; indirect couplings or communication connections between devices or units may be electrical or other forms.

[0075] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0076] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0077] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0078] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for diagnosing a fault of a coal mining machine, characterized by, The method is applied to a computer device, and comprises: obtaining coal mining machine fault position information; the obtaining of the coal mining machine fault position information comprises: the coal mining machine comprises a cutting part, a loading part and a walking part; when the value of a sensor of any one or more parts of the cutting part, the loading part and the walking part is not within a preset range, the position of the sensor whose value is not within the preset range is determined, so that the coal mining machine fault position is determined; the coal mining machine fault position information is obtained; sensor information at each key position on the coal mining machine fault position is obtained, and information fusion of multiple sensors is performed to obtain first data; information when the sensors at each key position on the coal mining machine fault position are normally working is obtained, and information fusion of multiple sensors when the sensors are normally working is performed to obtain second data; the first data and the second data are compared to generate and display first diagnostic information; the comparison of the first data and the second data to generate and display the first diagnostic information comprises: all data in the first data and the second data are compared one by one, whether each data has an error is judged, and the current fault is judged to be what kind of abnormality according to historical comparison data by calling the historical comparison data; overall data is compared, wherein the data of each sensor is associated with each other, and data abnormality of any one sensor will cause fluctuation of the remaining sensors, and the current fault reason is generated by comparing the first data and the second data; correlated positions of the coal mining machine fault position are obtained; working data of the correlated positions are obtained to obtain third data; the first data and the third data are combined to obtain fourth data; the second data and the third data are combined to obtain fifth data; the fourth data and the fifth data are compared to generate and display second diagnostic information; each part of the coal mining machine is associated with each other, and working data of each part are integrated, and the working data of each part is obtained by a sensor, and when the cutting part fails, the data of the loading part and the walking part are taken as third data.

2. The fault diagnosis method for a coal mining machine according to claim 1, characterized in that, After the obtaining of the information when the sensors at each key position on the coal mining machine fault position are normally working, the method further comprises: obtaining a waveform diagram of the sensor information at each key position in real time; comparing the waveform diagram of the sensor at each key position with a standard waveform diagram of the sensor at each key position; if there is a difference between the waveform diagram of the sensor at each key position and the standard waveform diagram, sending early warning information to enable a maintenance personnel to perform maintenance.

3. The fault diagnosis method of a coal mining machine according to claim 2, characterized in that, After the obtaining of the waveform diagram of the sensor information at each key position in real time, the method further comprises: calculating an overall trend curve diagram of the waveform diagram of the sensor at each key position; predicting a possible fault of the coal mining machine according to the overall trend curve diagram, and sending prediction information to a terminal device of the maintenance personnel.

4. The fault diagnosis method of a coal mining machine according to claim 1, characterized in that, After the comparison of the first data and the second data, the method further comprises: if the first diagnostic information is not generated, sending a diagnostic request to a terminal device of a maintenance personnel to enable the maintenance personnel to diagnose the coal mining machine fault reason, and storing the coal mining machine fault reason.

5. The fault diagnosis method of a coal mining machine according to claim 4, characterized in that, If the first diagnostic information is not generated, the method further comprises: sending detection information to a terminal device of the maintenance personnel, so that the maintenance personnel detects sensors installed at each key position of the fault part of the coal mining machine, and judges sensor faults and / or the fault of the coal mining machine.

6. A coal cutter failure diagnosing device characterized by comprising: The device comprises an acquisition module (1), a fusion module (2) and a comparison module (3); wherein the acquisition module (1) is used to acquire the fault part information of the coal mining machine; the acquisition of the fault part information of the coal mining machine comprises: the coal mining machine comprises a cutting part, a loading part and a walking part; when the value of the sensor of any one or more parts of the cutting part, the loading part and the walking part is not within a preset range, the position of the sensor whose value is not within the preset range is determined, thereby determining the fault part of the coal mining machine; the fault part information of the coal mining machine is acquired; the sensor information installed at each key position of the fault part of the coal mining machine is acquired; the information of the sensor installed at each key position of the fault part of the coal mining machine when the sensor is working normally is acquired; the fusion module (2) is used to fuse the information of multiple sensors to obtain first data; the information of multiple sensors when the sensors are working normally is fused to obtain second data; the comparison module (3) is used to compare the first data and the second data, generate and display first diagnostic information; the comparison of the first data and the second data to generate and display first diagnostic information comprises: corresponding one-to-one comparison of all data in the first data and the second data, judgment of whether there is an error in each data, judgment of what kind of abnormality the current fault is according to historical comparison data by calling the historical comparison data; comparison of overall data, wherein the data between each sensor is related to each other, and data anomaly of any one sensor will cause fluctuation of the remaining sensors, and the first data and the second data are compared to generate the current fault reason; The device further acquires the associated part of the fault part of the coal mining machine; acquires the working data of the associated part to obtain third data; combines the first data and the third data to obtain fourth data; combines the second data and the third data to obtain fifth data; compares the fourth data and the fifth data to generate and display second diagnostic information; each part of the coal mining machine is related to each other, and the working data of each part is integrated, and the working data of each part is obtained by a sensor, and when the cutting part fails, the data of the loading part and the walking part is taken as the third data.

7. An electronic device, comprising: The electronic device (1000) comprises a processor (1001), a memory (1005), a user interface (1003) and a network interface (1004); the memory (1005) is used to store instructions; the user interface (1003) and the network interface (1004) are used to communicate with other devices; and the processor (1001) is used to execute the instructions stored in the memory, so that the electronic device (1000) executes the method of any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer program stored in the memory can be loaded and executed by the processor to execute the method of any one of claims 1-5.

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