A data processing method, system and device based on online fault diagnosis mechanism

Abstract

The present invention discloses a data processing method, system and device based on an online fault diagnosis mechanism, which relates to the technical field of electrical digital data processing. The data processing method based on the online fault diagnosis mechanism includes the following steps: obtaining a stable state evaluation value; obtaining a slope stability index; and obtaining a fault diagnosis response score. The present invention determines whether to enter the slope guidance stage by using the obtained stable state evaluation value, and then monitors the slope guidance data of the specified conveyor at the current slope change moment in real time to obtain the slope stability index and determine whether to perform online fault diagnosis. Finally, the online fault diagnosis process is monitored in real time to obtain the fault diagnosis response score and determine whether to send a shutdown command, thereby achieving the effect of improving the online identification accuracy of the slope fault of the belt conveyor in the coal mine tunnel, and solving the problem of low accuracy of slope fault identification in the online fault diagnosis process of the belt conveyor in the coal mine tunnel in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular to a data processing method, system and device based on an online fault diagnosis mechanism. Background Art

[0002] With the rapid development of modern industrial technology, various mobile equipment, such as heavy machinery, wind turbines, and high-speed trains, are playing an increasingly important role in production and daily life. The operating status of these devices is directly related to production efficiency, safety performance, and economic benefits. Therefore, real-time monitoring and fault diagnosis of these devices have become important issues in the industrial field. Data processing methods based on online fault diagnosis mechanisms can monitor the operating status of equipment in real time, detect and address faults promptly, and thus ensure the normal operation of the production line. Online fault diagnosis enables precise maintenance of equipment, avoiding unnecessary downtime and repair costs. At the same time, by analyzing historical equipment data, it is possible to predict equipment lifespan and maintenance cycles, providing a scientific basis for equipment maintenance planning.

[0003] Existing technologies collect and preprocess the operating data of equipment in real time, and convert the preprocessed operating data into feature extraction patterns to identify abnormal patterns. Then, algorithms and models are used to process the abnormal data in the abnormal patterns to determine the root cause of the fault. Finally, the data processing algorithm is optimized to adapt to new fault diagnosis needs.

[0004] For example, the invention patent announcement with announcement number: CN118606869B discloses a chromatograph fault diagnosis and analysis method and system based on data processing, including: S1, obtaining the operating data of the chromatograph at n time points and preprocessing it to obtain standardized operating data; S2, generating a similarity matrix based on the standardized operating data; S3, clustering the standardized operating data based on the similarity matrix using an improved clustering algorithm to obtain N clusters; S4, calculating the density center and dispersion of each cluster, and constructing a fault feature vector based on the density center and dispersion; using a pre-built classification model to classify the fault feature vector, obtain the fault type and send it to the control terminal.

[0005] For example, the invention patent announcement with announcement number: CN118378151B discloses an intelligent substation data processing and control system and method, including: obtaining historical substation operating status data, performing data preprocessing to extract fault features and generate a fault sample data set; dividing the fault sample data set into a training data set and a test data set; using the C5.0 decision tree algorithm to calculate the information gain rate of the fault features of the training data set; inputting the test set data into the trained decision tree to obtain the final fault diagnosis result, and evaluating the model performance by analyzing the amount of data diagnosed correctly and incorrectly in the test set, outputting the model with the best performance as the fault diagnosis model.

[0006] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the existing technology, the existing pattern recognition algorithm fails to be specifically optimized for slope change faults, and the existing feature extraction method does not fully consider the slope change faults of conveying equipment during operation, so that the key operating parameters in the slope change faults cannot be fully captured, resulting in reduced reliability of the conveying equipment fault diagnosis results. There is a problem of low accuracy in identifying slope change faults during online fault diagnosis of belt conveyors in coal mine tunnels. Summary of the Invention

[0008] The embodiments of the present application solve the problem of low accuracy in identifying slope change faults during online fault diagnosis of belt conveyors in coal mine tunnels in the prior art by providing a data processing method, system, and device based on an online fault diagnosis mechanism, thereby improving the accuracy of online identification of slope change faults of belt conveyors in coal mine tunnels.

[0009] An embodiment of the present application provides a data processing method based on an online fault diagnosis mechanism, comprising the following steps: Step 1: real-time monitoring of the operating data of a designated conveyor at a current working moment to obtain a stable state evaluation value, and at the same time, judging whether to enter a slope change guidance stage based on the obtained stable state evaluation value, wherein the stable state evaluation value is used to evaluate the operating stability of the designated conveyor under the current working state; Step 2: if entering a slope change guidance stage, real-time monitoring of the slope change guidance data of the designated conveyor at the current slope change moment to obtain a slope change stability index, and at the same time, judging whether to perform online fault diagnosis based on the obtained slope change stability index, wherein the slope change stability index is used to quantify the stability of the designated conveyor during the slope change guidance process; Step 3: if online fault diagnosis is performed, a fault warning signal is issued and the online fault diagnosis process is monitored in real time to obtain a fault diagnosis response score, and at the same time, judging whether to send a shutdown command based on the obtained fault diagnosis response score, wherein the fault diagnosis response score is used to quantify the response speed and accuracy of the designated conveyor to fault diagnosis.

[0010] Furthermore, the stable state evaluation value is obtained by the following method: real-time monitoring of the noise intensity and vibration amplitude of the specified conveyor at the current working moment, when the obtained noise intensity is less than the noise intensity preset in the database and the obtained vibration amplitude is less than the vibration amplitude preset in the database, obtaining the belt tension and belt conveying speed of the specified conveyor at the current working moment; obtaining the motor current and bearing surface temperature of the specified conveyor at the current working moment, and combining the reference working data in the database and the dynamic data after de-unitization processing to obtain the stable state evaluation value; the dynamic data includes noise intensity, vibration amplitude, belt tension and belt conveying speed; the reference working data includes the maximum allowable belt tension, the maximum allowable belt conveying speed, the maximum allowable motor current and the maximum allowable bearing surface temperature.

[0011] Furthermore, the specific steps for obtaining the slope stability index are as follows: when the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database and the current slope change moment is not equal to 1, the slope change guide data of the specified conveyor at the current slope change moment is compared with the slope change guide data corresponding to the previous slope change moment, and the slope stability index is obtained in combination with the maximum allowable deviation data in the database; when the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database and the current slope change moment is equal to 1, the slope change guide data of the specified conveyor at the current slope change moment is compared with the corresponding initial slope change guide data to obtain the slope stability index; the slope change guide data include the slope change angle, the slope change speed, the belt tension during the slope change period, and the roller force during the slope change period; the initial slope change guide data include the initial slope change angle, the initial slope change speed, the belt tension during the initial slope change period, and the roller force during the initial slope change period; the maximum allowable deviation data include the maximum allowable slope change angle deviation, the maximum allowable slope change speed deviation, the maximum allowable slope change period belt tension deviation, and the maximum allowable slope change period roller force deviation.

[0012] Furthermore, the specific limiting expression of the slope stability index is:

[0013]

[0014] Wherein, j is the number of the current slope change moment, j = 1, 2, ..., J, J is the total number of the current slope change moments, e is a natural constant, PO represents the slope stability index of the specified conveyor during the slope change guidance process, TAI represents the stability state evaluation value of the specified conveyor in the current working state, TAI0 represents the preset stability state evaluation value, G j Indicates the slope angle of the specified conveyor at the current slope change time j, G j-1 Indicates the slope angle of the specified conveyor at the last slope change time j-1, ΔG max Indicates the maximum allowable slope angle deviation, Hj Indicates the slope change speed of the specified conveyor at the current slope change time j, H j-1 Indicates the slope change speed of the specified conveyor at the last slope change time j-1, ΔH max Indicates the maximum allowable slope speed deviation, K j It represents the belt tension of the specified conveyor during the slope change period at the current slope change time j, K j-1 Indicates the belt tension of the specified conveyor during the slope change period at the last slope change time j-1, ΔK max Indicates the maximum allowable belt tension deviation during the slope change period, L j It represents the force on the roller of the specified conveyor during the slope change period at the current slope change moment j, L j-1 Indicates the force on the roller of the specified conveyor during the slope change period at the last slope change time j-1, ΔL max It represents the maximum allowable roller force deviation during the slope change period, G0 represents the initial slope change angle, H0 represents the initial slope change speed, K0 represents the belt tension during the initial slope change period, and L0 represents the roller force during the initial slope change period.

[0015] Furthermore, the fault diagnosis response score is obtained by the following method: when the acquired variable slope stability index is less than the preset variable slope stability index in the database, online fault diagnosis data corresponding to the fault diagnosis is obtained; when the fault diagnosis response time is greater than the reference fault diagnosis response time in the database and the total fault diagnosis time is greater than the reference fault diagnosis total time in the database, the fault diagnosis response score is obtained by combining the reference online fault diagnosis data in the database and the acquired variable slope stability index, otherwise the fault diagnosis response score is not calculated and the response fault repair instruction is sent; the online fault diagnosis data includes the fault diagnosis response time, the total fault diagnosis time and the average electromagnetic field strength after denormalization; the reference online fault diagnosis data includes the maximum allowable fault diagnosis response time, the maximum allowable fault diagnosis total time and the maximum allowable electromagnetic field strength.

[0016] An embodiment of the present application provides a data processing system based on an online fault diagnosis mechanism, comprising: a stable state evaluation value acquisition module, a slope stability index module, and a fault diagnosis response score acquisition module; wherein the stable state evaluation value acquisition module is used to monitor the operating data of a specified conveyor at the current working moment in real time to obtain a stable state evaluation value, and at the same time, determine whether to enter the slope change guidance stage based on the obtained stable state evaluation value, and the stable state evaluation value is used to evaluate the operating stability of the specified conveyor in the current working state; the slope change stability index module is used to monitor the slope change guidance data of the specified conveyor at the current slope change moment in real time to obtain a slope change stability index if entering the slope change guidance stage, and at the same time, determine whether to perform online fault diagnosis based on the obtained slope change stability index, and the slope change stability index is used to quantify the stability of the specified conveyor during the slope change guidance process; the fault diagnosis response score acquisition module is used to issue a fault warning signal and monitor the online fault diagnosis process in real time to obtain a fault diagnosis response score if online fault diagnosis is performed, and at the same time, determine whether to send a shutdown command based on the obtained fault diagnosis response score, and the fault diagnosis response score is used to quantify the response speed and accuracy of the specified conveyor to fault diagnosis.

[0017] An embodiment of the present application provides an apparatus applying the data processing method based on an online fault diagnosis mechanism, comprising: a motor current collector, a belt speed meter, a belt tension meter, a bearing temperature meter, a vibration meter, a noise meter, a slope meter, a force sensor, a timer and an electromagnetic field strength detector; the motor current collector is used to obtain the motor current; the belt speed meter is used to obtain the belt conveying speed, the slope change speed and the initial slope change speed; the belt tension meter is used to obtain the belt tension, the belt tension during the slope change period and the belt tension during the initial slope change period; the bearing temperature meter is used to obtain the bearing surface temperature; the vibration meter is used to obtain the vibration amplitude; the noise meter is used to obtain the noise intensity; the slope meter is used to obtain the slope change angle and the initial slope change angle; the force sensor is used to obtain the roller force during the slope change period and the roller force during the initial slope change period; the timer is used to obtain the fault diagnosis response time and the total fault diagnosis time; the electromagnetic field strength detector is used to obtain the average electromagnetic field strength.

[0018] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0019] 1. Determine whether to enter the slope change guidance stage by using the obtained stable state evaluation value, then monitor the slope change guidance data of the specified conveyor at the current slope change moment in real time to obtain the slope change stability index and determine whether to perform online fault diagnosis. Finally, monitor the online fault diagnosis process in real time to obtain the fault diagnosis response score and determine whether to send a shutdown command, thereby improving the reliability of the fault diagnosis results and further improving the online identification accuracy of slope change faults of belt conveyors in coal mine tunnels, effectively solving the problem of low accuracy in slope change fault identification during online fault diagnosis of belt conveyors in coal mine tunnels in the existing technology.

[0020] 2. By judging whether the current slope change moment is not equal to 1, the slope change guidance data of the specified conveyor at the current slope change moment is compared with the slope change guidance data corresponding to the previous slope change moment, and the slope change stability index is obtained in combination with the maximum allowable deviation data in the database, thereby improving the accuracy of obtaining the slope change stability index and achieving a more accurate assessment of the slope change guidance stability of the specified conveyor.

[0021] 3. By obtaining the online fault diagnosis data corresponding to the fault diagnosis, when the fault diagnosis response time is greater than the reference fault diagnosis response time in the database and the total fault diagnosis time is greater than the reference fault diagnosis total time in the database, the fault diagnosis response score is obtained by combining the reference online fault diagnosis data in the database and the obtained slope stability index, thereby improving the accuracy of obtaining the fault diagnosis response score, and further achieving a more accurate evaluation of the reliability of the fault diagnosis response of the specified conveyor. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flowchart of a data processing method based on an online fault diagnosis mechanism provided in an embodiment of the present application;

[0023] Figure 2 Flowchart of online monitoring and fault diagnosis provided by the embodiment of the present application;

[0024] Figure 3 A structural diagram of a data processing system based on an online fault diagnosis mechanism provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The embodiments of the present application solve the problem of low accuracy in identifying slope-changing faults during online fault diagnosis of belt conveyors in coal mine tunnels in the prior art by providing a data processing method, system, and device based on an online fault diagnosis mechanism. The method monitors the operating data of a specified conveyor at the current working moment in real time to obtain a stable state evaluation value, and at the same time, determines whether to enter the slope-changing guidance stage based on the obtained stable state evaluation value. If the slope-changing guidance stage is entered, the slope-changing guidance data of the specified conveyor at the current slope-changing moment is monitored in real time to obtain a slope-changing stability index. Then, based on the obtained slope-changing stability index, determines whether to perform online fault diagnosis. If online fault diagnosis is performed, a fault warning signal is issued and the online fault diagnosis process is monitored in real time to obtain a fault diagnosis response score. Finally, based on the obtained fault diagnosis response score, determines whether to send a shutdown command, thereby improving the accuracy of online identification of slope-changing faults of belt conveyors in coal mine tunnels.

[0026] The technical solution in the embodiment of the present application is to solve the problem of low accuracy in identifying slope-changing faults during the online fault diagnosis of the belt conveyor in the coal mine tunnel. The overall idea is as follows:

[0027] The obtained stable state evaluation value is used to determine whether to enter the slope change guidance stage. Then, the slope change guidance data of the specified conveyor at the current slope change moment is monitored in real time to obtain the slope change stability index and determine whether to perform online fault diagnosis. Finally, the online fault diagnosis process is monitored in real time to obtain the fault diagnosis response score and determine whether to send a shutdown command. This achieves the effect of improving the online identification accuracy of slope change faults of belt conveyors in coal mine tunnels.

[0028] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0029] like Figure 1As shown, it is a flow chart of a data processing method based on an online fault diagnosis mechanism provided by an embodiment of the present application, the method comprising the following steps: Step 1, real-time monitoring of the operating data of a designated conveyor at the current working moment to obtain a stable state evaluation value, and at the same time, judging whether to enter the slope change guidance stage based on the obtained stable state evaluation value, the designated conveyor is a belt conveyor in a coal mine tunnel, and the stable state evaluation value is used to evaluate the operating stability of the designated conveyor under the current working state; Step 2, if entering the slope change guidance stage, real-time monitoring of the slope change guidance data of the designated conveyor at the current slope change moment to obtain a slope change stability index, and at the same time, judging whether to perform online fault diagnosis based on the obtained slope change stability index, the slope change stability index is used to quantify the stability of the designated conveyor during the slope change guidance process; Step 3, if online fault diagnosis is performed, a fault warning signal is issued and the online fault diagnosis process is monitored in real time to obtain a fault diagnosis response score, and at the same time, judging whether to send a shutdown command based on the obtained fault diagnosis response score, the fault diagnosis response score is used to quantify the response speed and accuracy of the designated conveyor to fault diagnosis.

[0030] In this embodiment, the operating data includes motor current, tape conveying speed, tape tension, bearing surface temperature, vibration amplitude, and noise intensity.

[0031] Online fault diagnosis is used to identify fault risk information of a specified conveyor; fault warning signals include fault type, fault location and fault level.

[0032] Fault risk information is used to reflect abnormal conditions that may occur during the operation of a specified conveyor, usually including material blockage, belt breakage and bearing damage. For example, when the belt tension of a specified conveyor at the current working moment is greater than the maximum allowable belt tension set by the preset personnel, it is usually determined that there is a belt breakage. When the motor current of a specified conveyor at the current working moment is greater than the maximum allowable motor current set by the preset personnel and the bearing surface temperature is greater than the maximum allowable bearing surface temperature set by the preset personnel, it is usually determined that the bearing is damaged due to excessive thermal friction.

[0033] like Figure 2 As shown, it is a flow chart of online monitoring and fault diagnosis provided in an embodiment of the present application. By real-time monitoring of the operating data, slope change guidance data and online fault diagnosis process of the specified conveyor, it realizes the assessment of the stability of the specified conveyor, the sending of fault warnings and shutdown instructions, and improves the accuracy of online identification of slope change faults of belt conveyors in coal mine tunnels. The application of the online monitoring and fault diagnosis system makes the maintenance of conveyors more intelligent and automated, providing more reliable and efficient protection for mine production.

[0034] Furthermore, the stable state evaluation value is obtained by the following method: real-time monitoring of the noise intensity and vibration amplitude of the specified conveyor at the current working moment, when the obtained noise intensity is less than the noise intensity preset in the database and the obtained vibration amplitude is less than the vibration amplitude preset in the database, obtaining the belt tension and belt conveying speed of the specified conveyor at the current working moment; obtaining the motor current and bearing surface temperature of the specified conveyor at the current working moment, and combining the reference working data in the database and the dynamic data after de-unitization processing to obtain the stable state evaluation value; the dynamic data includes noise intensity, vibration amplitude, belt tension and belt conveying speed; the reference working data includes the maximum allowable belt tension, the maximum allowable belt conveying speed, the maximum allowable motor current and the maximum allowable bearing surface temperature.

[0035] Among them, the specific limiting expression of the steady-state evaluation value is:

[0036]

[0037] Where i is the number of the current working moment, i = 1, 2, ..., U, U is the total number of the current working moment, e is a natural constant, TAI represents the stable state evaluation value of the specified conveyor in the current working state, A i Indicates the noise intensity of the specified conveyor at the current working time i, B i Indicates the vibration amplitude of the specified conveyor at the current working moment i, A0 represents the preset noise intensity, B0 represents the preset vibration amplitude, C i It represents the belt tension of the specified conveyor at the current working time i, C max Indicates the maximum allowable tape tension, D i Indicates the belt conveying speed of the specified conveyor at the current working time i, D max Indicates the maximum allowable belt conveying speed, E i Indicates the motor current of the specified conveyor at the current working moment i, E max Indicates the maximum allowable motor current, F i Indicates the bearing surface temperature of the specified conveyor at the current working time i, F max Indicates the maximum allowable bearing surface temperature.

[0038] In this embodiment, the noise intensity is generally used to reflect the wear of the mechanical parts on the specified conveyor at the current working moment; the vibration amplitude is generally used to reflect the balance of the specified conveyor at the current working moment; the belt tension in this example is greater than the reference belt tension in the database, which is generally used to reflect the tightness of the belt on the specified conveyor at the current working moment; the belt conveying speed is greater than the reference belt conveying speed in the database, which is generally used to reflect the rate at which the belt on the specified conveyor conveys materials at the current working moment; the motor current is greater than the reference motor current in the database, which is generally used to reflect the load condition of the specified conveyor at the current working moment; the bearing surface temperature is greater than the reference bearing surface temperature in the database, which is generally used to reflect the degree of wear of the bearing on the specified conveyor at the current working moment.

[0039] Among them, the reference dynamic data is represented by the sum and average of the dynamic data in the historical time period in the database. The reference dynamic data includes the preset noise intensity, the preset vibration amplitude, the reference tape tension, the reference tape conveying speed, the reference motor current and the reference bearing surface temperature; the reference working data represents the maximum value of the working data in the historical time period in the database. The working data includes the tape tension, the tape conveying speed, the motor current and the bearing surface temperature.

[0040] The aforementioned database is a database for storing various types of setting data established before the design of the data processing method based on the online fault diagnosis mechanism. The database includes but is not limited to preset stable state evaluation values, preset slope stability indicators, maximum allowable fault diagnosis response scores, current working times, and current slope change times. Various numerical values ​​are directly set by technical personnel. Among them, the setting basis of the preset slope stability indicator can be determined according to the actual slope change scenario of the specified conveyor. For example, the preset slope stability index is represented by the sum and average of the historical slope stability indicators of the specified conveyor at each historical slope change time in the database. In addition, various numerical values ​​in the database can be set and fine-tuned by technical personnel according to actual debugging.

[0041] It should be understood that the steady-state evaluation value decreases with the increase of noise intensity, vibration amplitude, belt tension, belt conveying speed, motor current and bearing surface temperature. Among them, the noise intensity indirectly affects the value of the vibration amplitude. When the noise intensity increases, it means that the frequency of friction and collision between the mechanical parts in the specified conveyor increases, resulting in these worn mechanical parts not being able to fit as tightly as new parts, causing more shaking and vibration during operation, and thus increasing the vibration amplitude.

[0042] Belt tension indirectly affects the value of the belt conveying speed. When the belt tension increases, the belt will become tight, which will increase the friction between the belt and the drive roller. Since friction is the main force driving the belt movement, the increase in friction will directly lead to an increase in the belt conveying speed.

[0043] The motor current also indirectly affects the value of the bearing surface temperature. When the weight of the material carried by a specified conveyor increases, the drive motor in the specified conveyor needs to provide more power to drive the belt, which will cause the motor current to increase because the motor needs to generate greater torque to cope with the increased load. The increase in motor current will generate more heat, which is transferred to the bearing through heat conduction, causing the bearing surface temperature to increase.

[0044] By considering the above-mentioned indirect influence mechanism, the stable state of the conveyor can be evaluated more accurately. For example, when the noise intensity is monitored to increase, it can be predicted that the vibration amplitude may also increase. When the motor current increases abnormally, measures can be taken in advance to reduce the bearing surface temperature to prevent failures caused by overheating. By real-time monitoring of the indirect influence relationship between these parameters, the online identification accuracy of slope change faults of belt conveyors in coal mine tunnels is improved, effectively solving the problem of low accuracy in identifying slope change faults in the online fault diagnosis process of belt conveyors in coal mine tunnels in the existing technology.

[0045] Furthermore, the specific process of judging whether to enter the slope-changing guidance stage based on the obtained stable state evaluation value is as follows: judging whether the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database: if the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database, it indicates that the designated conveyor is in a stable operating state and enters the slope-changing guidance stage; if the obtained stable state evaluation value is not greater than the stable state evaluation value preset in the database, then judging whether the obtained stable state evaluation value is equal to the stable state evaluation value preset in the database: if so, it indicates that the designated conveyor is in a critical operating state and sends a yellow warning signal, otherwise it indicates that the designated conveyor is in an abnormal operating state and sends a red warning signal; the yellow warning signal is used to prompt the operation and maintenance personnel to increase the frequency of online monitoring; the red warning signal is used to prompt the operation and maintenance personnel to immediately shut down for maintenance.

[0046] In this embodiment, the preset stable state evaluation value is represented by the sum and average of the historical stable state evaluation values ​​of the specified conveyor under historical working conditions in the database; this example subdivides the operating state of the specified conveyor into stable operating state, critical operating state and abnormal operating state by comparing the stable state evaluation value with the preset stable state evaluation value. For coal mine managers, it is convenient for them to make reasonable production scheduling and decisions. At the same time, timely early warning signals also reduce production losses caused by faults, and further improve the overall intelligence level of the specified conveyor operation.

[0047] Furthermore, the specific steps for obtaining the slope stability index are as follows: when the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database and the current slope change moment is not equal to 1, the slope guide data of the specified conveyor at the current slope change moment is compared with the slope guide data corresponding to the previous slope change moment, and the slope stability index is obtained in combination with the maximum allowable deviation data in the database; when the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database and the current slope change moment is equal to 1, the slope guide data of the specified conveyor at the current slope change moment is compared with the corresponding initial slope guide data to obtain the slope stability index; the slope guide data includes the slope angle, the slope speed, the belt tension during the slope change period, and the roller force during the slope change period; the initial slope guide data includes the initial slope angle, the initial slope speed, the belt tension during the initial slope change period, and the roller force during the initial slope change period; the maximum allowable deviation data includes the maximum allowable slope angle deviation, the maximum allowable slope speed deviation, the maximum allowable slope belt tension deviation during the slope change period, and the maximum allowable slope roller force deviation during the slope change period.

[0048] The specific limiting expression of the slope stability index is:

[0049]

[0050] Where, j is the number of the current slope change moment, j = 1, 2, ..., J, J is the total number of the current slope change moments, e is a natural constant, PO represents the slope stability index of the specified conveyor during the slope change guidance process, TAI represents the stability state evaluation value of the specified conveyor in the current working state, TAI0 represents the preset stability state evaluation value, G j Indicates the slope angle of the specified conveyor at the current slope change time j, G j-1 Indicates the slope angle of the specified conveyor at the last slope change time j-1, ΔG max Indicates the maximum allowable slope angle deviation, H j Indicates the slope change speed of the specified conveyor at the current slope change time j, H j-1 Indicates the slope change speed of the specified conveyor at the last slope change time j-1, ΔH maxIndicates the maximum allowable slope speed deviation, K j It represents the belt tension of the specified conveyor during the slope change period at the current slope change time j, K j-1 Indicates the belt tension of the specified conveyor during the slope change period at the last slope change time j-1, ΔK max Indicates the maximum allowable belt tension deviation during the slope change period, L j It represents the force on the roller of the specified conveyor during the slope change period at the current slope change moment j, L j-1 Indicates the force on the roller of the specified conveyor during the slope change period at the last slope change time j-1, ΔL max It represents the maximum allowable roller force deviation during the slope change period, G0 represents the initial slope change angle, H0 represents the initial slope change speed, K0 represents the belt tension during the initial slope change period, and L0 represents the roller force during the initial slope change period.

[0051] In this embodiment, the roller force during the variable wave period represents the resultant force of the vertical and horizontal forces borne by the roller on the specified conveyor from the belt and the material on the belt at the current working moment, and the maximum allowable deviation data represents the maximum value of the historical deviation parameters corresponding to the specified conveyor in the database at each historical slope change moment, wherein the historical deviation parameters include the historical slope change angle deviation, the historical slope change speed deviation, the historical slope change period belt tension deviation, and the historical slope change period roller force deviation.

[0052] It should be understood that when j≠1and TAI>TAI0, the slope stability index increases with the slope angle deviation (i.e. |G j -G j-1 |), slope speed deviation (i.e. |H j -H j-1 |), belt tension deviation during slope change period (i.e. |K j -K j-1 |) and the roller force deviation during the slope change period (i.e. |L j -L j-1 |) increases, and increases with the increase of the steady-state evaluation value.

[0053] It should be noted that the stable state evaluation value also indirectly affects the value of the slope angle deviation. When the stable state evaluation value increases, it means that the operating stability of the specified conveyor is improved, and the wear and deformation of its mechanical components (such as rollers and idlers) are reduced. Therefore, the deviation of the slope angle will also be relatively reduced. By monitoring the changes in the stable state evaluation value, the trend of the slope angle deviation can be predicted to avoid the occurrence of slope failure.

[0054] The slope change speed deviation also indirectly affects the value of the belt tension deviation during the slope change period. When the slope change speed deviation increases, it means that the speed change degree of the specified conveyor increases, which will cause the impact force on the belt during the slope change period to increase, and the resulting tension deviation will also increase. By monitoring the changes in the slope change speed deviation, the tension fluctuation of the belt during the slope change period can be reduced, and the operating stability of the conveyor can be improved.

[0055] The belt tension deviation during the slope change period also indirectly affects the value of the roller force deviation during the slope change period. When the belt tension deviation increases during the slope change period, the roller needs to withstand greater tension and torque, which may cause increased wear or deformation of the roller. By monitoring the changes in the belt tension deviation, the force state of the roller can be evaluated, and timely measures can be taken for maintenance or replacement to avoid the impact of roller failure on the overall operation of the conveyor.

[0056] By considering the above-mentioned indirect influence mechanism, we can have a more comprehensive understanding of the relationship between the slope stability index and various parameters, and then more accurately identify the slope failure of the conveyor, which helps to reduce the impact of the failure on the operational stability of the conveyor, thereby achieving an improvement in the online identification accuracy of the slope failure of the belt conveyor in the coal mine tunnel, and effectively solving the problem of low accuracy in the online fault diagnosis process of the belt conveyor in the coal mine tunnel in the existing technology.

[0057] Furthermore, the specific process of determining whether to perform online fault diagnosis based on the acquired slope stability index is as follows: determine whether the acquired slope stability index is less than the slope stability index preset in the database; if so, it indicates that the designated conveyor is in a stable slope state and online fault monitoring continues; otherwise, it indicates that the designated conveyor is in an abnormal slope state and the fault level is classified, and online fault diagnosis is performed according to the classified fault level; the fault level includes a first fault and a second fault; the first fault indicates that the acquired slope stability index is greater than the fault corresponding to the slope stability index preset in the database; the second fault indicates that the acquired slope stability index is equal to the fault corresponding to the slope stability index preset in the database.

[0058] In this embodiment, the specific process of online fault diagnosis is: inputting the acquired operating data and slope guidance data into the constructed fault diagnosis model to output the fault status of the specified conveyor at the current working moment; the fault diagnosis model is used to automatically identify different fault modes of the specified conveyor.

[0059] Specifically, the acquired operating data and slope guidance data are input into the convolutional neural network in the neural network model for training, thereby obtaining a fault diagnosis model with the ability to process nonlinear relationships. At the same time, the constructed fault diagnosis model is deployed into the fault diagnosis response score acquisition module, and the fault state prediction result of the specified conveyor is output, thereby improving the reliability of the online fault diagnosis results of the specified conveyor and providing a strong guarantee for the safe operation of the specified conveyor.

[0060] Furthermore, the fault diagnosis response score is obtained by the following method: when the obtained variable slope stability index is less than the preset variable slope stability index in the database, the online fault diagnosis data corresponding to the fault diagnosis is obtained; when the fault diagnosis response time is greater than the reference fault diagnosis response time in the database and the total fault diagnosis time is greater than the reference fault diagnosis total time in the database, the fault diagnosis response score is obtained by combining the reference online fault diagnosis data in the database and the obtained variable slope stability index, otherwise the fault diagnosis response score is not calculated and the response fault repair instruction is sent; the online fault diagnosis data includes the fault diagnosis response time, the total fault diagnosis time and the average electromagnetic field strength after denormalization; the reference online fault diagnosis data includes the maximum allowable fault diagnosis response time, the maximum allowable fault diagnosis total time and the maximum allowable electromagnetic field strength.

[0061] The specific restriction expression of the fault diagnosis response score is:

[0062]

[0063] In the formula, e is a natural constant, GU represents the fault diagnosis response score of the specified conveyor during the fault diagnosis process, PO represents the slope stability index of the specified conveyor during the slope guidance process, and PO0 represents the preset slope stability index. It represents the average electromagnetic field strength of a specified conveyor during the fault diagnosis process, Q max represents the maximum allowable electromagnetic field strength, P represents the fault diagnosis response time of the specified conveyor during the fault diagnosis process, P0 represents the reference fault diagnosis response time, P max Indicates the maximum allowable fault diagnosis response time, R indicates the total fault diagnosis time of the specified conveyor during the fault diagnosis process, R0 indicates the reference fault diagnosis time, and R max Indicates the maximum allowable total fault diagnosis time.

[0064] In this embodiment, the reference fault diagnosis response time and the reference fault diagnosis total time are respectively represented by the sum and average of the historical fault diagnosis response time and the historical fault diagnosis total time of the specified conveyor in the database during the historical slope change process, and the reference online fault diagnosis data represents the maximum value of the historical online fault diagnosis data corresponding to the historical slope change process of the specified conveyor in the database, wherein the maximum value of the historical online fault diagnosis data includes the maximum value of the historical fault diagnosis response time, the maximum value of the historical fault diagnosis total time and the maximum value of the historical electromagnetic field strength.

[0065] Specifically, assuming that the preset slope stability index is set to 0.9, the reference fault diagnosis response time is set to 0.45s, the reference fault diagnosis total time is set to 2.5s, the maximum allowable electromagnetic field strength is set to 0.65, the maximum allowable fault diagnosis response time is set to 0.85s, and the maximum allowable fault diagnosis total time is set to 3.5s, the change statistics of the fault diagnosis response score are shown in Table 1:

[0066] Table 1 Statistics of changes in fault diagnosis response scores

[0067]

[0068]

[0069] It should be understood that, from the first to the third groups of data in Table 1, it can be seen that the fault diagnosis response score decreases with the increase of the average electromagnetic field strength, the fault diagnosis response time and the total fault diagnosis time. From the fourth and fifth groups of data in Table 1, it can be seen that the fault diagnosis response score increases with the increase of the slope stability index.

[0070] It should be noted that the slope stability index also indirectly affects the value of the average electromagnetic field strength. When the slope stability index increases, it means that the slope change process of the specified conveyor is smoother, reducing the mechanical vibration and impact caused by the slope change. This smooth slope change process helps to reduce the fluctuation of the electromagnetic field, thereby reducing the electromagnetic interference caused by friction and collision, making the measurement value of the average electromagnetic field strength more accurate and stable.

[0071] The average electromagnetic field strength also indirectly affects the value of the fault diagnosis response time. Since the electromagnetic field strength is closely related to the operating status of a specified conveyor, when the average electromagnetic field strength increases, it means that the mechanical vibration and impact caused by the slope change process increase. At this time, it is necessary to identify the fault type more quickly, thereby shortening the fault diagnosis response time.

[0072] By considering the above-mentioned indirect influence mechanism, we can more comprehensively understand the relationship between various parameters in the process of online fault diagnosis of conveyors, which helps operation and maintenance personnel to promptly repair designated conveyors, improves the accuracy and efficiency of fault diagnosis, and thus achieves an improvement in the online identification accuracy of slope change faults of belt conveyors in coal mine tunnels, effectively solving the problem of low accuracy in identifying slope change faults in the process of online fault diagnosis of belt conveyors in coal mine tunnels in the existing technology.

[0073] Furthermore, the specific process of determining whether to send a shutdown command based on the acquired fault diagnosis response score is as follows: determining whether the acquired fault diagnosis response score is less than the maximum allowable fault diagnosis response score: if the acquired fault diagnosis response score is less than the maximum allowable fault diagnosis response score, a non-emergency shutdown command is sent; if the acquired fault diagnosis response score is not less than the maximum allowable fault diagnosis response score, an emergency shutdown command is sent; the shutdown command includes an emergency shutdown command and a non-emergency shutdown command.

[0074] In this embodiment, the maximum allowable fault diagnosis response score represents the maximum value of the historical fault diagnosis response scores of the specified conveyor in the database during the historical fault diagnosis process.

[0075] Compared with the existing technology, this example sets the maximum allowable fault diagnosis response score and sends different types of shutdown instructions according to the changes in the value of the fault diagnosis response score. This can ensure that the specified conveyor can be quickly shut down when a serious fault occurs (such as the drive motor burns out, and the motor current at this time is greater than the maximum allowable motor current), thereby improving the operating safety of the conveyor; for non-emergency faults (such as the bearing surface temperature increases and causes bearing wear, and the bearing surface temperature at this time is less than the maximum allowable bearing surface temperature), sending a non-emergency shutdown instruction can allow maintenance without affecting the production progress, avoiding production interruptions and losses caused by emergency shutdowns, and realizing real-time monitoring and intelligent judgment of the operating status of the specified conveyor, which helps to improve the intelligence level of belt conveyors in coal mine tunnels and provide strong support for safe production and efficient operation of coal mines.

[0076] like Figure 3As shown, it is a structural schematic diagram of a data processing system based on an online fault diagnosis mechanism provided in an embodiment of the present application. The data processing system based on an online fault diagnosis mechanism provided in an embodiment of the present application includes: a stable state evaluation value acquisition module, a slope stability index module and a fault diagnosis response score acquisition module; wherein, the stable state evaluation value acquisition module is used to monitor the operating data of the specified conveyor at the current working moment in real time to obtain a stable state evaluation value, and at the same time, judge whether to enter the slope guidance stage based on the obtained stable state evaluation value. The specified conveyor is a belt conveyor in a coal mine tunnel, and the stable state evaluation value is used to evaluate the operating stability of the specified conveyor in the current working state. The slope stability index module is used to monitor the slope guidance data of the specified conveyor at the current slope change moment in real time to obtain the slope stability index if the slope guidance stage is entered, and to determine whether to perform online fault diagnosis based on the obtained slope stability index. The slope stability index is used to quantify the stability of the specified conveyor during the slope guidance process; the fault diagnosis response score acquisition module is used to issue a fault warning signal and monitor the online fault diagnosis process in real time to obtain the fault diagnosis response score if online fault diagnosis is performed, and to determine whether to send a shutdown command based on the obtained fault diagnosis response score. The fault diagnosis response score is used to quantify the response speed and accuracy of the specified conveyor to fault diagnosis.

[0077] In this embodiment, in a large coal mine, there are multiple coal mine tunnels, and a belt conveyor is installed in each tunnel for continuous transportation of coal. In order to ensure production efficiency and safety, the coal mine manager decided to introduce a data processing system based on an online fault diagnosis mechanism to monitor the operating status of the belt conveyor in real time. This can greatly reduce the probability of conveyor failure, thereby improving the safety of coal mine production.

[0078] An embodiment of the present application provides an apparatus for applying a data processing method based on an online fault diagnosis mechanism, including: a motor current collector, a belt speed meter, a belt tension meter, a bearing temperature meter, a vibration meter, a noise meter, a slope meter, a force sensor, a timer and an electromagnetic field strength detector; the motor current collector is used to obtain the motor current; the belt speed meter is used to obtain the belt conveying speed, the slope change speed and the initial slope change speed; the belt tension meter is used to obtain the belt tension, the belt tension during the slope change period and the belt tension during the initial slope change period; the bearing temperature meter is used to obtain the bearing surface temperature; the vibration meter is used to obtain the vibration amplitude; the noise meter is used to obtain the noise intensity; the slope meter is used to obtain the slope change angle and the initial slope change angle; the force sensor is used to obtain the roller force during the slope change period and the roller force during the initial slope change period; the timer is used to obtain the fault diagnosis response time and the total fault diagnosis time; the electromagnetic field strength detector is used to obtain the average electromagnetic field strength.

[0079] To sum up, the embodiment of the present application determines whether to enter the slope change guidance stage through the obtained stable state evaluation value, and then monitors the slope change guidance data of the specified conveyor at the current slope change moment in real time to obtain the slope change stability index and determine whether to perform online fault diagnosis, and finally monitors the online fault diagnosis process in real time to obtain the fault diagnosis response score and determine whether to send a shutdown command, thereby achieving a more accurate evaluation of the fault diagnosis response speed and accuracy, and further achieving an improvement in the online identification accuracy of the slope change fault of the belt conveyor in the coal mine tunnel, effectively solving the problem of low accuracy in the identification of slope change faults in the online fault diagnosis process of the belt conveyor in the coal mine tunnel in the prior art.

[0080] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, 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 produce 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 flowcharts and / or block diagrams. 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.

[0082] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0084] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0085] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A data processing method based on an online fault diagnosis mechanism, characterized in that: The following steps are involved: Step 1: Real-time monitoring of the operating data of the designated conveyor at the current working moment to obtain a stable state evaluation value, and at the same time, judging whether to enter the slope-changing guidance stage based on the obtained stable state evaluation value, wherein the stable state evaluation value is used to evaluate the operating stability of the designated conveyor in the current working state; Step 2: If the slope change guidance phase is entered, the slope change guidance data of the specified conveyor at the current slope change moment is monitored in real time to obtain a slope change stability index. At the same time, based on the obtained slope change stability index, it is determined whether to perform online fault diagnosis. The slope change stability index is used to quantify the stability of the specified conveyor during the slope change guidance process; Step 3: If online fault diagnosis is performed, a fault warning signal is issued and the online fault diagnosis process is monitored in real time to obtain a fault diagnosis response score. Based on the obtained fault diagnosis response score, a decision is made as to whether to issue a shutdown command. The fault diagnosis response score is used to quantify the response speed and accuracy of the specified conveyor to the fault diagnosis. The specific process of judging whether to enter the slope-changing guidance stage based on the obtained stable state evaluation value is as follows: Determine whether the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database: If the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database, it indicates that the designated conveyor is in a stable operating state and enters the slope-changing guidance stage; If the obtained steady state evaluation value is not greater than the steady state evaluation value preset in the database, then determine whether the obtained steady state evaluation value is equal to the steady state evaluation value preset in the database: If so, it indicates that the designated conveyor is in a critical operating state and a yellow warning signal is sent; otherwise, it indicates that the designated conveyor is in an abnormal operating state and a red warning signal is sent. The yellow warning signal is used to prompt the operation and maintenance personnel to increase the frequency of online monitoring, and the red warning signal is used to prompt the operation and maintenance personnel to immediately shut down the machine for maintenance.

2. A data processing method based on an online fault diagnosis mechanism as claimed in claim 1, characterized in that: The operating data includes motor current, belt conveying speed, belt tension, bearing surface temperature, vibration amplitude and noise intensity; The online fault diagnosis is used to identify fault risk information of a specified conveyor; The failure risk information includes material blockage, belt breakage and bearing damage; The fault warning signal includes the fault type, fault location and fault level; The steady state evaluation value is obtained by the following method: Real-time monitoring of the noise intensity and vibration amplitude of the specified conveyor at the current working moment. When the obtained noise intensity is less than the noise intensity preset in the database and the obtained vibration amplitude is less than the vibration amplitude preset in the database, the belt tension and belt conveying speed of the specified conveyor at the current working moment are obtained. Obtain the motor current and bearing surface temperature of the specified conveyor at the current working moment, and combine the reference working data in the database and the dynamic data after de-normalization to obtain the stable state evaluation value; The dynamic data include noise intensity, vibration amplitude, tape tension and tape conveying speed; The reference operating data include a maximum allowable belt tension, a maximum allowable belt conveying speed, a maximum allowable motor current, and a maximum allowable bearing surface temperature.

3. A data processing method based on an online fault diagnosis mechanism as claimed in claim 1, characterized in that: The specific steps for obtaining the slope stability index are as follows: When the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database and the current slope change moment is not equal to 1, the slope change guidance data of the specified conveyor at the current slope change moment is compared with the slope change guidance data corresponding to the previous slope change moment, and the slope change stability index is obtained in combination with the maximum allowable deviation data in the database; When the obtained stable state evaluation value is greater than the stable state evaluation value preset in the database and the current slope change moment is equal to 1, the slope change guidance data of the specified conveyor at the current slope change moment is compared with the corresponding initial slope change guidance data to obtain the slope change stability index; The slope change guidance data includes the slope change angle, slope change speed, belt tension during the slope change period, and roller force during the slope change period; The initial slope change guidance data includes the initial slope change angle, the initial slope change speed, the belt tension during the initial slope change period, and the roller force during the initial slope change period; The maximum allowable deviation data includes the maximum allowable slope change angle deviation, the maximum allowable slope change speed deviation, the maximum allowable belt tension deviation during the slope change period, and the maximum allowable roller force deviation during the slope change period.

4. A data processing method based on an online fault diagnosis mechanism as claimed in claim 3, characterized in that: The specific limiting expression of the slope stability index is: ； Where j is the number of the current slope change moment, , J is the total number of current slope change moments, e is a natural constant, It indicates the slope stability index of the specified conveyor during the slope guidance process. Indicates the stable state evaluation value of the specified conveyor in the current working state, represents the preset steady-state assessment value, Indicates the slope angle of the specified conveyor at the current slope change time j, Indicates the slope angle of the specified conveyor at the last slope change time j-1. Indicates the maximum allowable slope angle deviation, Indicates the slope changing speed of the specified conveyor at the current slope changing moment j, Indicates the slope change speed of the specified conveyor at the last slope change time j-1, Indicates the maximum allowable slope speed deviation. It represents the belt tension of the specified conveyor during the slope change period at the current slope change time j. It represents the belt tension of the specified conveyor during the slope change period at the last slope change time j-1. Indicates the maximum allowable belt tension deviation during the slope change period. It represents the force on the roller of the specified conveyor during the slope change period at the current slope change moment j. It represents the force on the roller of the specified conveyor during the slope change period at the last slope change moment j-1. Indicates the maximum allowable roller force deviation during the slope change period. Indicates the initial slope angle, represents the initial slope change speed, Indicates the belt tension during the initial slope change period, Indicates the force on the roller during the initial slope change period.

5. A data processing method based on an online fault diagnosis mechanism as claimed in claim 1, characterized in that: The specific process of determining whether to perform online fault diagnosis based on the acquired slope stability index is as follows: Determine whether the obtained slope stability index is less than the slope stability index preset in the database. If so, it indicates that the specified conveyor is in a stable slope state and continues to perform online fault monitoring. Otherwise, it indicates that the specified conveyor is in an abnormal slope state and performs fault level classification. At the same time, perform online fault diagnosis according to the classified fault level. The fault level includes a first fault and a second fault; The first fault indicates that the acquired slope stability index is greater than the slope stability index preset in the database; The second fault indicates that the acquired slope stability index is equal to a fault corresponding to a slope stability index preset in a database.

6. A data processing method based on an online fault diagnosis mechanism as claimed in claim 1, characterized in that: The fault diagnosis response score is obtained by the following method: When the acquired slope stability index is less than the slope stability index preset in the database, online fault diagnosis data corresponding to the fault diagnosis is acquired; When the fault diagnosis response time is greater than the reference fault diagnosis response time in the database and the total fault diagnosis time is greater than the reference fault diagnosis total time in the database, the fault diagnosis response score is obtained by combining the reference online fault diagnosis data in the database and the obtained slope stability index; otherwise, the fault diagnosis response score is not calculated and a response fault repair instruction is sent; The online fault diagnosis data includes fault diagnosis response time, total fault diagnosis time and average electromagnetic field strength after denormalization; The reference online fault diagnosis data includes a maximum allowable fault diagnosis response time, a maximum allowable fault diagnosis total time, and a maximum allowable electromagnetic field strength.

7. A data processing method based on an online fault diagnosis mechanism as claimed in claim 1, characterized in that: The specific process of determining whether to send a shutdown instruction based on the acquired fault diagnosis response score is as follows: Determine whether the obtained fault diagnosis response score is less than the maximum allowable fault diagnosis response score: If the acquired fault diagnosis response score is less than the maximum allowable fault diagnosis response score, a non-emergency shutdown command is sent; If the acquired fault diagnosis response score is not less than the maximum allowable fault diagnosis response score, an emergency shutdown command is sent; The shutdown instructions include emergency shutdown instructions and non-emergency shutdown instructions.

8. A system using a data processing method based on an online fault diagnosis mechanism as claimed in any one of claims 1 to 7, characterized in that: include: Stable state evaluation value acquisition module, slope stability index module and fault diagnosis response score acquisition module; The stable state evaluation value acquisition module is used to monitor the operating data of the specified conveyor at the current working moment in real time to obtain a stable state evaluation value, and at the same time, judge whether to enter the slope-changing guidance stage based on the obtained stable state evaluation value. The stable state evaluation value is used to evaluate the operating stability of the specified conveyor in the current working state; The slope stability index module is used to monitor the slope guidance data of the specified conveyor at the current slope change moment in real time to obtain a slope stability index when entering the slope guidance stage. At the same time, based on the obtained slope stability index, it is determined whether to perform online fault diagnosis. The slope stability index is used to quantify the stability of the specified conveyor during the slope guidance process. The fault diagnosis response score acquisition module is used to issue a fault warning signal and monitor the online fault diagnosis process in real time to obtain a fault diagnosis response score when performing online fault diagnosis. At the same time, it determines whether to send a shutdown command based on the acquired fault diagnosis response score. The fault diagnosis response score is used to quantify the response speed and accuracy of the specified conveyor to fault diagnosis.

9. A device using a data processing method based on an online fault diagnosis mechanism as claimed in any one of claims 1 to 7, characterized in that: include: Motor current collector, belt speed meter, belt tension meter, bearing temperature meter, vibration meter, noise meter, slope meter, force sensor, timer and electromagnetic field strength detector; The motor current collector is used to obtain the motor current; The belt speed measuring instrument is used to obtain the belt conveying speed, slope changing speed and initial slope changing speed; The belt tension measuring instrument is used to obtain the belt tension, the belt tension during the slope change period, and the belt tension during the initial slope change period; The bearing temperature meter is used to obtain the bearing surface temperature; The vibration measuring instrument is used to obtain the vibration amplitude; The noise meter is used to obtain noise intensity; The slope measuring instrument is used to obtain the slope change angle and the initial slope change angle; The force sensor is used to obtain the force on the roller during the slope change period and the force on the roller during the initial slope change period; The timer is used to obtain the fault diagnosis response time and the total fault diagnosis time; The electromagnetic field strength detector is used to obtain the average electromagnetic field strength.

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