Fault diagnosis and fault early warning method and system based on expert database

Abstract

The invention discloses a fault diagnosis and fault early warning method and system based on an expert database, and relates to the technical field of fault early warning, and the method comprises the steps: collecting the operation data of automation equipment in real time, and transmitting the operation data of the automation equipment to a processing center; the processing center performs periodic inspection comparison on the collected operation data of the single automation equipment and the standard parameters in the expert database to obtain a comparison analysis result, and gives an alarm if the parameters are found to be abnormal; periodic inspection automation equipment: performing periodic inspection comparison on the operation data of different equipment; and performing fault diagnosis by using the alarm information and the expert database, analyzing the cause of the fault, and generating a fault report according to the diagnosis result. According to the method, the timeliness, the accuracy and the efficiency of fault processing are remarkably improved, the maintenance response time is optimized, the fault prevention capability is enhanced, and the production loss and the safety risk are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of fault early warning, and in particular to a fault diagnosis and fault early warning method and system based on an expert database. Background Art

[0002] The widespread deployment and operation of automation equipment is of great significance to improving industrial production efficiency and quality control. With the advancement of Industry 4.0, the monitoring and maintenance technology of automation equipment is also developing. Traditional equipment maintenance strategies usually rely on regular inspections and scheduled maintenance plans, which may lead to waste of resources or failures due to untimely inspections. With the advancement of sensor technology and data analysis technology, condition-based monitoring (CBM) and predictive maintenance (PdM) technologies have gradually become a trend. These technologies can evaluate the health status of equipment based on real-time data, predict potential failures, and thus optimize maintenance plans and reduce downtime.

[0003] Despite this, existing fault warning and diagnosis technologies still face challenges in practical applications. First, the processing and analysis of massive data generated by a large number of devices requires extremely high computing efficiency and precise algorithm support to ensure the real-time and accuracy of fault warnings. Second, most existing systems use general algorithms to monitor equipment, which makes it difficult to fully consider the specific operating characteristics and environmental factors of various devices, thus affecting the accuracy of fault diagnosis.

[0004] The present invention proposes a fault diagnosis and fault warning method based on an expert database. This method effectively improves the accuracy and response speed of fault detection by collecting the operating data of automated equipment in real time and performing intelligent comparative analysis with standard parameters in the expert database. In addition, by introducing the concept of periodic inspections and adding differentiated processing for primary and secondary inspections, it is possible to more accurately evaluate the status of equipment based on the real-time and historical operating data of the equipment, and to promptly discover and diagnose potential anomalies. This method not only improves the timeliness and accuracy of early warnings, but also optimizes maintenance decisions by calculating the conditional probability of failures, significantly improving the pertinence and effectiveness of maintenance operations. Summary of the invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is: how to solve the problem that the fault warning system in the prior art is often based on a fixed threshold or simple pattern recognition, which not only limits the accuracy of the warning but also affects the timeliness.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: a fault diagnosis and fault warning method based on an expert database, comprising: real-time collection of automation equipment operation data, and transmission of the automation equipment operation data to a processing center; the processing center periodically compares the collected operation data of a single automation equipment with the standard parameters in the expert database to obtain the results of the comparative analysis, and issues an alarm if an abnormal parameter is found; periodically patrols the automation equipment, and periodically compares the operation data of different equipment; uses the alarm information and the expert database to perform fault diagnosis, analyze the cause of the fault, and generate a fault report based on the diagnosis result.

[0008] As a preferred solution of the fault diagnosis and fault warning method based on expert database described in the present invention, the operation data of the automation equipment includes communication status, analog quantity, input quantity, soft and hard pressure plates, constant value, software version, self-test alarm, timing, current and voltage loop, and GPS alarm.

[0009] As a preferred solution of the fault diagnosis and fault warning method based on expert database described in the present invention, wherein: the periodic inspection comparison includes one inspection and two inspections; the one inspection includes inspecting whether the operation mode and operation condition of the automation equipment are consistent with the standard, the standard is the equipment operation condition information that meets the operation mode at that time, and an inspection alarm is generated in case of abnormality. After one inspection task is completed, information about the completion of one inspection without abnormality or one inspection with abnormality is sent, and an inspection report is formed for each inspection; the two inspections include comparing the operation data of the automation equipment with no abnormality and one inspection with abnormality with the preset standard value or normal operation threshold in the expert database, and an inspection report is formed for each inspection; logical detection is used to identify abnormalities or deviations in the data, and for the communication status, the communication is monitored to see if it is interrupted, For analog quantities, set upper and lower limit thresholds for each analog quantity to monitor whether it crosses the limit. For input quantities, monitor the state changes of the switch quantities. For soft and hard pressure plates, check whether the states of the soft and hard pressure plates are consistent with the preset normal states. For fixed values, monitor the operating parameters and fixed values ​​of the equipment to check whether they are consistent with the preset parameter setting values. For the software version, confirm whether the software version is the latest. For self-test alarms, determine whether the equipment has self-test faults or configuration errors based on the content of the self-test alarms. For time synchronization, detect the deviation between the system time and the standard time to confirm whether there is a time synchronization problem. For current and voltage loops, set upper and lower limit thresholds for current and voltage to monitor whether there is current imbalance or voltage abnormality. For GPS alarms, monitor the GPS alarm status to check whether there is a signal interruption or position information deviation.

[0010] As a preferred solution of the fault diagnosis and fault warning method based on the expert library described in the present invention, the alarm includes: for the communication state, when the communication state changes from normal to interrupted, an alarm is immediately triggered to perform a communication interruption alarm; for the analog quantity, if any analog quantity exceeds the set threshold, an analog quantity out-of-bounds alarm is performed; for the input quantity, if the switch quantity state is not changed by a command, an unexpected state change alarm is performed; for the soft and hard pressure plates, if the state of the soft pressure plate or the hard pressure plate is inconsistent with the preset state, a state inconsistency alarm is performed; for the fixed value, if any fixed value or parameter of the equipment does not match the preset set value, a fixed value inconsistency alarm is performed; for the software version, if the software version is not updated to the latest version, a software version outdated alarm is performed; for the self-test alarm, if any error problem is reported during the equipment self-test, an equipment self-test failure alarm is performed; for the time synchronization, if the deviation between the system time and the standard time exceeds the set allowable range, a time synchronization error alarm is performed; for the current and voltage circuit, if the current or voltage exceeds the set upper and lower thresholds, a current or voltage abnormality alarm is performed; for the GPS alarm, if the GPS signal is interrupted or the position information is deviated, a GPS function failure alarm is performed.

[0011] As a preferred solution of the fault diagnosis and fault warning method based on expert database described in the present invention, wherein: the periodic patrol automation equipment includes measurement and control device patrol items, communication gateway machine patrol items, monitoring host patrol items, switch patrol items, timing device patrol items and operation and maintenance control substation patrol items; the measurement and control device patrol items include input quantities, soft pressure plates, hard pressure plates, fixed values, software versions, self-test alarms, timing, current and voltage circuits; the communication gateway machine patrol items include input quantities, fixed values, software versions, self-test alarms and timing; the monitoring host patrol items include software versions, self-test alarms and timing; the switch patrol items include input quantities, software versions, self-test alarms and timing; the timing device patrol items include input quantities, software versions, self-test alarms and timing; the operation and maintenance control substation patrol items include communication status.

[0012] As a preferred solution of the fault diagnosis and fault warning method based on expert database described in the present invention, wherein: the fault diagnosis includes: if there is no abnormality in the completion of the first patrol and the second patrol is completed without abnormality, then the automation equipment has no abnormality; if there is no abnormality in the completion of the first patrol and the second patrol is completed with an abnormality, it is a single two abnormalities; if there is an abnormality in the completion of the first patrol and the second patrol is completed without abnormality, it is a single abnormality; if there is an abnormality in the completion of the first patrol and the second patrol is completed with abnormality, it is a full abnormality.

[0013] As a preferred solution of the fault diagnosis and fault warning method based on the expert database described in the present invention, the fault diagnosis also includes: if it is a single or double abnormality, it indicates that the initial state of the automation equipment is good, but a sudden fault occurs, and the fault is located, and the abnormal parameters found in the second inspection are checked in particular, and the affected components are identified. According to the fault diagnosis result, similar faults in the expert database are retrieved to generate a fault report, and the affected components are repaired; if it is a single fault, it indicates that the abnormality detected during the first inspection is temporary or accidental, or it has recovered by itself before the second inspection, and the first and second inspections are performed again; if it is a complete fault, the inspection reports in the first and second inspections are collected, and the probability of the automation equipment failure is calculated as: , in, is the conditional probability of equipment failure when both patrol data show abnormalities, is the probability of two abnormal patrol data when a known device fails, is the prior probability of failure, is the probability that both the first inspection and the second inspection have abnormalities, For a patrol of abnormal data, For the second inspection abnormal data, For automation equipment failure; set the failure probability threshold, if If the fault probability is greater than the fault probability threshold, the automation equipment is stopped immediately, and the expert database is retrieved based on the first and second patrol anomalies to generate fault reports of similar faults and perform repairs respectively; if If it is less than the fault probability threshold, a new inspection is conducted. If the first inspection is abnormal, similar faults are retrieved from the expert database and repaired until the first inspection is normal. A second inspection is conducted. If the second inspection is normal, it is handled according to the single-two fault.

[0014] Another object of the present invention is to provide a system of fault diagnosis and fault warning methods based on an expert database, which can solve the problem of fault diagnosis and fault warning based on an expert database by constructing a fault diagnosis and fault warning system.

[0015] In order to solve the above technical problems, the present invention provides the following technical solutions: a fault diagnosis and fault warning system based on an expert database, comprising a data acquisition module, a comparison module, a periodic inspection module and a fault diagnosis module; the data acquisition module collects the operation data of the automation equipment in real time, and transmits the operation data of the automation equipment to a processing center; the comparison module processing center performs periodic inspection and comparison on the collected operation data of a single automation equipment with the standard parameters in the expert database to obtain the results of the comparison and analysis, and issues an alarm if an abnormal parameter is found; the periodic inspection module periodically inspects the automation equipment, and performs periodic inspection and comparison on the operation data of different equipment; the fault diagnosis module uses the alarm information and the expert database to perform fault diagnosis, analyze the cause of the fault, and generate a fault report based on the diagnosis result.

[0016] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned expert library-based fault diagnosis and fault warning method when executing the computer program.

[0017] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned fault diagnosis and fault warning method based on an expert library.

[0018] The beneficial effects of the present invention are as follows: the fault diagnosis and fault warning method based on the expert database provided by the present invention collects equipment operation data, compares the data with the standard parameters in the expert database to identify deviations, and uses the alarm information and the expert database to accurately diagnose the cause of the fault, thereby significantly improving the timeliness, accuracy and efficiency of fault handling. It not only optimizes the maintenance response time and enhances the ability to prevent faults, but also reduces production losses and safety risks, providing an efficient and systematic solution for equipment management, while using periodic inspections to reduce consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0020] Figure 1 A flowchart of a fault diagnosis and fault warning method based on an expert database is provided for the first embodiment of the present invention.

[0021] Figure 2 A structural diagram of a fault diagnosis and fault warning system based on an expert database provided in accordance with the second embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0023] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0024] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides a fault diagnosis and fault warning method based on an expert database, including: collecting automation equipment operating data in real time, and transmitting the automation equipment operating data to a processing center; the processing center periodically inspects and compares the collected operating data of a single automation equipment with the standard parameters in the expert database to obtain the results of the comparison and analysis, and issues an alarm if abnormal parameters are found; periodically inspects the automation equipment, and periodically inspects and compares the operating data of different equipment; uses the alarm information and the expert database to perform fault diagnosis, analyze the cause of the fault, and generate a fault report based on the diagnosis results.

[0025] S1. Collect the operation data of automation equipment in real time and transmit the operation data of automation equipment to the processing center.

[0026] Equipment operation data includes communication status, analog quantity, input quantity, soft and hard pressure plates, set values, software version, self-test alarm, timing, current and voltage circuits, and GPS alarm.

[0027] Automation equipment includes measurement and control devices, communication gateways, monitoring hosts, network switches, time synchronization devices, operation and maintenance control substations, etc. Automation equipment provides equipment ledger information, communication status information, self-test alarm information, equipment resource information, internal environment information, and time synchronization status information to meet the requirements of online monitoring and abnormal analysis functions.

[0028] Collect the operating data of automated equipment in real time to ensure that the data can be accessed at any time for comparison during periodic inspections or manual inspections.

[0029] S2. The processing center will periodically compare the collected operating data of a single automated device with the standard parameters in the expert database to obtain the results of the comparative analysis. If any abnormal parameters are found, an alarm will be issued.

[0030] The periodic inspection comparison includes one inspection and two inspections; one inspection includes inspecting whether the operation mode and operating conditions of the automation equipment are consistent with the standards. The standard is the equipment operation condition information that meets the current operation mode. Inspection alarms are generated in case of abnormalities. After one inspection task is completed, information about the completion of one inspection without abnormalities or one inspection with abnormalities is sent, and an inspection report is generated for each inspection; the second inspection includes comparing the operation data of the automation equipment with no abnormalities in the first inspection and with abnormalities in the first inspection with the preset standard values ​​or normal operation thresholds in the expert database, and an inspection report is generated for each inspection.

[0031] Periodic inspections are conducted once or twice at a certain interval, and inspections can be manually selected. The interval is determined according to actual needs and can be adjusted. Both normal and abnormal results should be visible in the inspection report, and abnormal results need to describe the difference information in more detail.

[0032] The expert database includes equipment preset standard values, normal operation thresholds, fault types and treatment measures, and is updated.

[0033] Compare the collected data with the preset standard values ​​or normal operation thresholds in the expert database; use logic detection to identify anomalies or deviations in the data; for communication status, monitor whether the communication is interrupted; for analog quantities, set upper and lower thresholds for each analog quantity to monitor whether it is out of bounds; for input quantities, monitor the state changes of the switch quantity, especially the changes that are not triggered by operation instructions; for soft and hard pressure plates, check whether the states of the soft and hard pressure plates are consistent with the preset normal states; for fixed values, monitor the operating parameters and fixed values ​​of the equipment to check whether they are consistent with the preset parameter setting values; for software versions, confirm whether the software version is the latest; for self-test alarms, determine whether the equipment has specific faults or configuration errors based on the content of the self-test alarms; for time synchronization, detect the deviation between the system time and the standard time to confirm whether there is a time synchronization problem; for current and voltage circuits, set upper and lower thresholds for current and voltage to monitor whether there is current imbalance or voltage anomaly; for GPS alarms, monitor the GPS alarm status to check whether there is a signal interruption or position information deviation problem. As shown in Table 1.

[0034] Table 1 Inspection items , For the communication status, when the communication status changes from normal to interrupted, an alarm is triggered immediately, and a communication interruption alarm is issued. For analog quantities, if any analog quantity exceeds the set threshold, an analog quantity out-of-bounds alarm is issued. For input quantities, if the switch quantity status is changed without a command, such as accidentally changing from closed to open, an unexpected status change alarm is issued. For soft and hard pressure plates, if the status of the soft pressure plate or the hard pressure plate is inconsistent with the preset status, an inconsistent status alarm is issued. For fixed values, if any fixed value or parameter of the equipment does not match the preset setting value, an inconsistent fixed value alarm is issued.

[0035] For the software version, if the software version is not updated to the latest version, an outdated software version alarm will be issued. For the self-test alarm, if any error problem is reported during the device self-test, an equipment self-test failure alarm will be issued. For time synchronization, if the deviation between the system time and the standard time exceeds the set allowable range, a time synchronization error alarm will be issued. For the current and voltage circuits, if the current or voltage exceeds the set upper and lower thresholds, a current or voltage abnormality alarm will be issued. For the GPS alarm, if the GPS signal is interrupted or the position information is deviated, a GPS function failure alarm will be issued.

[0036] S3. Periodically inspect automated equipment and conduct periodic inspections and comparisons of operating data of different equipment.

[0037] The equipment inspection scope includes inspection items of measurement and control devices, communication gateways, monitoring hosts, switches, timing devices and operation and maintenance control substations; inspection items of measurement and control devices include other analog quantities, input quantities, soft pressure plates, hard pressure plates, fixed values, software versions, self-test alarms, timing, current and voltage circuits; inspection items of communication gateways include other analog quantities, input quantities, fixed values, software versions, self-test alarms and timing; inspection items of monitoring hosts include other analog quantities, software versions, self-test alarms and timing; inspection items of switches include other analog quantities, input quantities, software versions, self-test alarms and timing; inspection items of timing devices include other analog quantities, input quantities, software versions, self-test alarms and timing; and inspection items of operation and maintenance control substations include communication status and other analog quantities. As shown in Table 2. Other analog quantities include other analog quantities related to the equipment except current and voltage.

[0038] Table 2 Equipment inspection range , S4. Use the alarm information and expert database to perform fault diagnosis, analyze the cause of the fault, and generate a fault report based on the diagnosis results.

[0039] If there are no abnormalities in the first inspection and the second inspection, there are no abnormalities in the automation equipment. If there are no abnormalities in the first inspection and the second inspection, there are abnormalities, it is a single-two abnormalities. If there are abnormalities in the first inspection and the second inspection, there are no abnormalities, it is a single abnormality. If there are abnormalities in the first inspection and the second inspection, there are all abnormalities.

[0040] If it is a single-two abnormality, it means that the automation equipment is in good initial condition, but a sudden failure occurs in a short period of time. It may be due to operating errors, changes in environmental factors or sudden failure of equipment components. Fault location is carried out, focusing on checking the abnormal parameters found in the second inspection, identifying the affected components, and based on the fault diagnosis results, retrieving similar faults from the expert database to generate a fault report and repair the affected components.

[0041] If it is a single fault, it means that the abnormality detected during the first inspection is temporary or accidental, or it has recovered by itself before the second inspection, and the first and second inspections should be carried out again.

[0042] If it is a complete failure, collect the inspection reports from the first and second inspections, and calculate the probability of failure of the automation equipment as: , in, is the conditional probability of equipment failure when both patrol data show abnormalities, The probability of two abnormal patrol data in the case of a known equipment failure is given by using statistical methods based on the historical data at the time of failure. is the prior probability of failure, given based on historical failure records, is the probability that both the first inspection and the second inspection have abnormalities, For a patrol of abnormal data, For the second inspection abnormal data, It is a failure of automation equipment.

[0043] Set the fault probability threshold based on historical data. If the probability of a fault is greater than the fault probability threshold, this usually means that there is strong evidence that the equipment has or is about to have a serious fault, the automation equipment is immediately stopped, and the expert database is retrieved based on the first and second patrol anomalies to generate a fault report of the same type of fault, and repairs are performed separately; if If the probability of failure is less than the threshold, a new inspection is conducted. If the first inspection is abnormal, similar faults are retrieved from the expert database and repaired until the first inspection is normal. A second inspection is conducted. If the second inspection is normal, the fault is handled according to the single-two fault. Sensors and monitoring tools in automation systems may generate false alarms due to various reasons (such as environmental factors, sensor aging, etc.). By setting a reasonable fault probability threshold and re-checking when it is lower than the threshold, unnecessary repairs or downtime caused by false alarms can be reduced, and operational efficiency can be optimized.

[0044] The fault report includes the first inspection, second inspection and overall abnormal information, and the expert database processing measures. If the expert database has similar faults, the processing measures for similar faults will be given. If the expert database does not have similar faults, it will be processed urgently, and the processing measures and faults will be entered into the expert database for storage.

[0045] Example 2, reference Figure 2 , which is the second embodiment of the present invention, is different from the previous embodiment in that it provides a fault diagnosis and fault warning system based on an expert database, including: a data acquisition module 100, a comparison module 200, a periodic inspection module 300 and a fault diagnosis module 400.

[0046] The data acquisition module 100 collects the automation equipment operation data in real time and transmits the automation equipment operation data to the processing center.

[0047] The comparison module 200 processing center periodically compares the collected operating data of a single automation device with the standard parameters in the expert database to obtain the results of the comparison analysis. If any abnormal parameters are found, an alarm is issued.

[0048] The periodic inspection module 300 periodically inspects the automation equipment and performs periodic inspections and comparisons on the operating data of different equipment.

[0049] The fault diagnosis module 400 uses the alarm information and the expert database to perform fault diagnosis, analyze the cause of the fault, and generate a fault report based on the diagnosis result.

[0050] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0051] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0052] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0053] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0054] Embodiment 3 is the third embodiment of the present invention. It is different from the first two embodiments in that it is used to verify the technical effects adopted in the present invention so as to verify the real effects of the method.

[0055] The method of the present invention and the traditional method are used to simultaneously detect the automation equipment.

[0056] This embodiment uses the traditional method and the method of the present invention to perform detection simultaneously, and the detection comparison results are shown in Table 3 below: Table 3 Comparison table of traditional method and method of the present invention , The method of the present invention collects equipment data in real time and conducts periodic inspections and comparative analysis with standard parameters in the expert database to perform diagnosis. The traditional threshold monitoring method sets a separate fixed parameter threshold. When the monitored data exceeds the threshold, a fault alarm is triggered. Based on the maintenance plan recommended by the equipment manufacturer or past experience, the equipment is maintained regularly (for example, monthly or quarterly), regardless of the actual operating status of the equipment. This method may lead to excessive maintenance or failure to perform necessary maintenance before a fault occurs. Inspection and repair are only performed after the fault occurs, which usually leads to unexpected downtime and production losses.

[0057] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A fault diagnosis and fault warning method based on an expert database, characterized in that: include, Collect automation equipment operation data in real time and transmit the automation equipment operation data to the processing center; The processing center will periodically compare the collected operating data of a single automated device with the standard parameters in the expert database to obtain the results of the comparative analysis. If any abnormal parameters are found, an alarm will be issued. Periodically inspect automation equipment and compare the operating data of different equipment; Use alarm information and expert database to diagnose faults, analyze the causes of faults, and generate fault reports based on the diagnosis results.

2. A fault diagnosis and fault warning method based on an expert database as claimed in claim 1, characterized in that: The automation equipment operation data includes communication status, analog quantity, input quantity, soft and hard pressure plates, fixed values, software version, self-test alarm, timing, current and voltage loop, and GPS alarm.

3. A fault diagnosis and fault warning method based on an expert database as claimed in claim 2, characterized in that: The periodic inspection comparison includes a first inspection and a second inspection; The inspection includes inspecting whether the operation mode and operation condition of the automation equipment are consistent with the standard. The standard is the equipment operation condition information that meets the current operation mode. Inspection alarms are generated when abnormalities occur. After an inspection task is completed, information about the inspection completion without abnormality or the inspection completion with abnormality is sent. An inspection report is generated for each inspection. The second inspection includes comparing the operation data of the automation equipment that has no abnormality after the first inspection and the operation data of the automation equipment that has abnormality after the first inspection with the preset standard value or normal operation threshold in the expert database, and forming an inspection report for each inspection; Use logical detection to identify anomalies or deviations in data. For communication status, monitor whether the communication is interrupted. For analog quantities, set upper and lower limit thresholds for each analog quantity to monitor whether it is out of bounds. For input quantities, monitor the state changes of the switch quantities. For soft and hard pressure plates, check whether the status of the soft and hard pressure plates is consistent with the preset normal state. For fixed values, monitor the operating parameters and fixed values ​​of the equipment to check whether they are consistent with the preset parameter setting values. For the software version, confirm whether the software version is the latest. For self-test alarms, determine whether the equipment has self-test faults or configuration errors based on the content of the self-test alarm. For time synchronization, detect the deviation between the system time and the standard time to confirm whether there is a time synchronization problem. For current and voltage circuits, set upper and lower limit thresholds for current and voltage to monitor whether there is current imbalance or voltage abnormality. For GPS alarms, monitor the GPS alarm status to check whether there is a signal interruption or position information deviation.

4. A fault diagnosis and fault warning method based on an expert database as claimed in claim 3, characterized in that: The alarm includes, for the communication status, when the communication status changes from normal to interrupted, an alarm is immediately triggered, and a communication interruption alarm is issued; for the analog quantity, if any analog quantity exceeds the set threshold, an analog quantity out-of-bounds alarm is issued; for the input quantity, if the switch quantity state is changed without a command, an unexpected state change alarm is issued; for the soft and hard pressure plates, if the state of the soft pressure plate or the hard pressure plate is inconsistent with the preset state, a state inconsistency alarm is issued; for the fixed value, if any fixed value or parameter of the device does not match the preset set value, a fixed value inconsistency alarm is issued; For software version, if the software version is not updated to the latest version, an outdated software version alarm will be issued; for self-check alarm, if the device reports any error during self-check, an equipment self-check failure alarm will be issued; for time synchronization, if the deviation between the system time and the standard time exceeds the set allowable range, an error alarm will be issued; For the current and voltage loop, if the current or voltage exceeds the set upper and lower thresholds, a current or voltage abnormality alarm will be issued. For the GPS alarm, if the GPS signal is interrupted or the position information is deviated, a GPS function failure alarm will be issued.

5. A fault diagnosis and fault early warning method based on an expert database as claimed in claim 4, characterized in that: The periodic inspection automation equipment includes inspection items of measurement and control devices, inspection items of communication gateway machines, inspection items of monitoring hosts, inspection items of switches, inspection items of timing devices and inspection items of operation and maintenance control substations; The inspection items of the measurement and control device include input quantity, soft pressure plate, hard pressure plate, fixed value, software version, self-test alarm, time synchronization, current and voltage circuit; The communication gateway machine inspection items include input quantity, fixed value, software version, self-check alarm and time synchronization; The monitoring host inspection items include software version, self-check alarm and time synchronization; The switch inspection items include input quantity, software version, self-check alarm and time synchronization; The inspection items of the timing device include input quantity, software version, self-check alarm and time synchronization; The inspection items of the operation and maintenance control substation include communication status.

6. A fault diagnosis and fault warning method based on an expert database as claimed in claim 5, characterized in that: The fault diagnosis includes: if there is no abnormality in the completion of the first patrol and the second patrol, then there is no abnormality in the automation equipment; if there is no abnormality in the completion of the first patrol and there is an abnormality in the completion of the second patrol, then it is a single-two abnormalities; if there is an abnormality in the completion of the first patrol and there is no abnormality in the completion of the second patrol, then it is a single abnormality; if there is an abnormality in the completion of the first patrol and there is an abnormality in the completion of the second patrol, then it is a full abnormality.

7. A fault diagnosis and fault early warning method based on an expert database as claimed in claim 6, characterized in that: The fault diagnosis also includes if it is a single-second abnormality, it indicates that the automation equipment is in good initial condition, but a sudden fault occurs, and the fault is located, focusing on checking the abnormal parameters found in the secondary inspection, identifying the affected components, and according to the fault diagnosis results, retrieving the expert database for similar faults to generate a fault report, and repairing the affected components; If it is a single fault, it means that the abnormality detected during the first inspection is temporary or accidental, or it has recovered by itself before the second inspection, and the first and second inspections are repeated; If it is a complete failure, the inspection reports from the first and second inspections are collected, and the probability of failure of the automation equipment is calculated as: ， in, is the conditional probability of equipment failure when both patrol data show abnormalities, is the probability of two abnormal patrol data when a known device fails, is the prior probability of failure, is the probability that both the first inspection and the second inspection have abnormalities, For a patrol of abnormal data, For the second inspection abnormal data, Automation equipment failure; Set the failure probability threshold if If the probability is greater than the fault probability threshold, the automation equipment will be stopped immediately, and similar faults in the expert database will be retrieved based on the first and second patrol anomalies to generate fault reports and perform repairs respectively; like If it is less than the fault probability threshold, a new inspection is conducted. If the first inspection is abnormal, similar faults are retrieved from the expert database and repaired until the first inspection is normal. A second inspection is conducted. If the second inspection is abnormal, it is handled according to the single-two fault.

8. A system using a fault diagnosis and fault warning method based on an expert database as claimed in any one of claims 1 to 7, characterized in that: It comprises a data acquisition module (100), a comparison module (200), a periodic inspection module (300) and a fault diagnosis module (400); The data acquisition module (100) collects the automation equipment operation data in real time, and transmits the automation equipment operation data to the processing center; The comparison module (200) processing center periodically compares the collected operation data of a single automated device with the standard parameters in the expert database to obtain the result of the comparison analysis, and issues an alarm if an abnormal parameter is found; The periodic inspection module (300) periodically inspects the automated equipment and performs periodic inspections and comparisons on the operating data of different equipment; The fault diagnosis module (400) uses the alarm information and the expert database to perform fault diagnosis, analyze the cause of the fault, and generate a fault report based on the diagnosis result.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a fault diagnosis and fault warning method based on an expert library as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a fault diagnosis and fault warning method based on an expert library as described in any one of claims 1 to 7 are implemented.

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