CN111160579A - Platform door fault diagnosis and analysis method based on weight - Google Patents

Platform door fault diagnosis and analysis method based on weight Download PDF

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Publication number
CN111160579A
CN111160579A CN201911393602.7A CN201911393602A CN111160579A CN 111160579 A CN111160579 A CN 111160579A CN 201911393602 A CN201911393602 A CN 201911393602A CN 111160579 A CN111160579 A CN 111160579A
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fault
event
weight
platform door
diagnosis
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高振天
赵晗
孙奎
张育超
肖虎斌
邵刚
何启明
刘小伟
胡扬超
张乐彬
闫娟
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713th Research Institute of CSIC
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    • G06Q50/40—Business processes related to the transportation industry

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Abstract

A platform door fault diagnosis and analysis method based on weight comprises the following steps: establishing a fault tree model of a platform door system, wherein the fault tree model comprises a top event, a middle event and a bottom event; when a platform door system has a fault, inquiring all bottom events causing the fault through a fault tree model, sequencing all the bottom events from high to low according to the weight, and sending the bottom events to maintenance personnel; the maintainer searches the fault reason and maintains according to the received sorted bottom event list; and after the maintenance personnel finish the treatment, updating the weight of the bottom event according to the fault reason corresponding to the adopted fault. The fault diagnosis system provided by the invention adopts the platform door system fault tree model as a diagnosis basis, diagnoses the fault reason by adopting a mode of comparing the field fault number with the fault tree, pushes the diagnosis result to maintenance personnel for fault maintenance, and feeds back and registers the maintenance result.

Description

Platform door fault diagnosis and analysis method based on weight
Technical Field
The invention belongs to a fault tree analysis method, and particularly relates to a platform door fault diagnosis analysis method based on weight.
Background
With the rapid development of urban rail transit in China, the platform door system is widely applied, and when the platform door system breaks down on site, on-site maintenance personnel are required to judge the fault and make corresponding measures, so that the influence of the fault on the platform door system is eliminated, and the normal and safe operation of the subway is guaranteed. However, the diagnosis of the failure of the platform door system by the field maintenance personnel requires the maintenance personnel to have basic theoretical knowledge, skilled platform door system operation procedures, and technical skills such as standard operation in case of emergency. Once a maintainer encounters an emergency fault or a difficult problem, the maintainer often cannot accurately diagnose the fault and take correct maintenance measures, so that the optimal fault processing time is missed, the late point of a train is caused, and severe influence is caused on subway operation service.
In the traditional platform door fault diagnosis system, fault diagnosis experience of platform door system experts is normalized, a platform door system fault tree model is established, and fault diagnosis is carried out according to a certain logic mode; although the fault diagnosis adopts a fault tree form, the weight of each fault reason to the system fault cannot be accurately matched, usually, one fault is caused by a plurality of bottom events together, or any one of the plurality of bottom events can cause the same fault; for the requirements of fault diagnosis of different levels of a complex large system, sometimes the fault source can not be refined to the root cause; when some new faults are faced, the existing fault diagnosis system cannot be used for diagnosis, and often experts are required to be in the spot for diagnosis, so that the faults cannot be processed in time. Therefore, the faults in the fault tree of the platform door system need to be numbered, field maintenance personnel register and feed back fault maintenance results, the fault maintenance results are incorporated into a fault diagnosis system, and weight analysis is carried out according to the occurrence probability of a fault mode and the key importance of a bottom event.
The existing platform door system fault diagnosis has the advantages and disadvantages that: when a platform door breaks down on site, problems can be found in time, and in the capacity range of maintenance personnel, the maintenance personnel can determine the cause of the failure in time and take corresponding solving measures in time; when the fault is associated with various devices, maintenance personnel often cannot judge the cause of the fault or cannot take effective measures to influence the normal operation of the train.
Disclosure of Invention
The invention solves the technical problem of providing a weight-based platform door system fault diagnosis and analysis method, which can quickly and accurately judge the fault reason according to fault information in the platform door system fault diagnosis and provide a corresponding fault solution plan according to the fault, so that field maintenance personnel can quickly, accurately and efficiently process the fault problem aiming at the problem and ensure the safe operation of a train.
The invention adopts the following technical scheme:
a method for diagnosing and analyzing the fault of a platform door based on weight,
establishing a fault tree model of a platform door system, wherein the fault tree model comprises a top event, a middle event and a bottom event;
when a platform door system has a fault, inquiring all bottom events causing the fault through a fault tree model, sequencing all the bottom events from high to low according to the weight, and sending the bottom events to maintenance personnel;
the maintainer searches the fault reason and maintains according to the received sorted bottom event list;
and after the maintenance personnel finish the treatment, updating the weight of the bottom event according to the fault reason corresponding to the adopted fault.
The weight of the bottom event is as follows:
and when the fault corresponding to the top event occurs N times, the probability that the occurrence frequency N of the fault reason corresponding to each bottom event occurs in the N faults.
And each bottom event is simultaneously associated with a fault maintenance scheme of the fault event, and after receiving the sorted bottom event list, maintenance personnel search the bottom events according to the sorting and fault reasons corresponding to the bottom events until the bottom event causing the top event is found, and maintain the bottom events according to the fault maintenance schemes corresponding to the bottom events.
In the maintenance process of maintenance personnel, if the fault reason causing the occurrence of the top event is not in the bottom event list, the fault reason is added into the bottom event to update the fault tree model, and meanwhile, the weight of the bottom event is updated.
The invention has the beneficial effects that:
(1) the fault diagnosis system adopts a platform door system fault tree model as a diagnosis basis, diagnoses fault reasons in a mode of comparing field fault numbers with a fault tree, pushes diagnosis results to maintenance personnel for fault maintenance, and feeds back and registers maintenance results.
(2) And performing weight analysis on the fault maintenance information fed back by the maintenance personnel each time, inputting the analysis result into a station local database, and finally summarizing the fault data of different stations into a diagnosis database. Along with the continuous expansion of the data volume of the diagnosis database, the accuracy rate of fault diagnosis is improved.
Drawings
FIG. 1 is a flow chart of the present invention.
FIG. 2 is a fault tree section model with a door-closing fault as the top event.
FIG. 3 is a fault tree section model for an intermediate event of sliding door resistance being excessive.
FIG. 4 is a partial model of a fault tree when a DCU fault is an intermediate event.
FIG. 5 is a fault tree section model for a door lock fault as an intermediate event.
FIG. 6 is a fault tree section model at an intermediate event of a motor fault.
Fig. 7 is a fault tree section model at cable/plug loosening intermediate events.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same technical meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
The invention discloses a platform door fault diagnosis and analysis method based on weight, which specifically comprises the following steps:
the method comprises the following steps: establishing a fault tree model of a platform door system in a fault diagnosis system, wherein the fault tree model comprises a top event, a middle event and a bottom event;
in this step, when the fault tree model is established, a large amount of data such as the fault point, the fault reason, the fault handling measure and the like of the platform door system need to be collected, and the platform door system fault model is established according to the data.
Step two: when a platform door system has a fault, inquiring all bottom events causing the fault and the weight of the bottom events through a fault tree model, sequencing all the bottom events from high to low according to the weight, and sending the bottom events to a terminal of a maintainer;
in the fault tree of the present invention, each bottom event has a weight, and the weight is the probability of occurrence of the bottom event, that is: assuming that the fault corresponding to the top event occurs N times, the weight P = N/N of the occurrence frequency N of the fault cause corresponding to each bottom event.
Therefore, according to the fault diagnosis processing flow, when the field platform door system has a fault, firstly, the fault is numbered so that the computer can identify the fault, and secondly, all bottom events causing the fault are inquired through the fault tree model, so that the fault diagnosis range is reduced. And finally, pushing the diagnosis result to field maintenance personnel for fault treatment.
Step three: the maintainer searches the fault reason according to the received sorted bottom event list and maintains the fault reason; when the fault tree model is established, each bottom event is simultaneously associated with the fault maintenance scheme or the suggested measures of the fault event, and after receiving the sorted bottom event list, maintenance personnel search the fault reasons corresponding to the bottom events according to the sorting until the bottom event causing the top event is found and maintain according to the fault maintenance scheme corresponding to the bottom event.
Step four: and after the maintenance personnel finish the treatment, updating the weight of the bottom event according to the fault reason corresponding to the adopted fault.
In this step, after each fault occurs and maintenance is completed, the weight of the bottom event is updated according to the feedback of the maintenance personnel, and because the probability of the bottom event changes when each fault occurs, the probability of all the bottom events changes, the system can judge the fault according to the feedback information of the maintenance personnel when each fault is processed, and if the fault is caused by misinformation or non-equipment reasons, the fault diagnosis system does not need to feed back; in addition, feedback is required for each fault. When feedback is needed, the system updates the types of the faults, the maintenance schemes corresponding to the faults and the probability of the faults in the diagnosis database, redistributes the weight of each fault, establishes a one-to-one correspondence relationship between the corresponding fault reasons and the maintenance schemes and the faults according to the feedback data, and avoids the influence on the accuracy of fault diagnosis caused by the occurrence of irrelevant faults or novel faults.
In the maintenance process of maintenance personnel, if the fault reason causing the occurrence of the top event is not in the bottom event list, the fault reason is added into the bottom event to update the fault tree model, and meanwhile, the weight of the bottom event is updated.
Similarly, in the maintenance process of the maintainer, if the top event is not in the fault tree model, the fault reason is added into the fault tree model to update the fault tree model, and meanwhile, the weight of the bottom event can also be updated.
Fig. 2-7 show embodiments of the present invention in which a door-closing failure is the top event. In this embodiment, the method for diagnosing and analyzing the fault of the platform door includes the following steps:
the method comprises the following steps: and collecting all data about the fault point of the platform door system, the fault reason corresponding to the fault, the maintenance scheme corresponding to the fault and the like, and establishing the fault tree model of the platform door system according to the modeling principle of the fault tree model.
The invention establishes a platform door system fault tree model by taking a door closing fault as a top event of a fault tree, and numbers and marks the fault tree from top to bottom as shown in fig. 2-7, wherein the top event is T1, the middle events are E1-E9, and the bottom events are X1-X21, and the fault tree model covers all contents related to the door closing fault of the platform door system. When the door closing fault occurs to the platform door, fault diagnosis can be performed according to the fault tree, the reason causing the door closing fault is found out, and a basis is provided for fault diagnosis of the system.
Step two: according to the fault diagnosis process shown in fig. 1, firstly, the fault diagnosis system polls stations, stores the collected operation data of the platform door system equipment of each station into a local database and analyzes the data, codes the fault to form a top event when the data related to the door closing fault is found in the data, and then performs fault tree diagnosis comparison through a door closing fault tree model to find out a bottom event X causing the faulti(i =1-21), finding out the fault reason according to the one-to-one correspondence relationship between the fault and the fault reason, and pushing the diagnosis result to a field maintenance worker, so that the field maintenance worker can rapidly and accurately process the fault.
Step three: after the fault is eliminated, according to the processing condition of the field fault, if the fault reason pushed by the diagnosis system or the place with an abnormal fault processing plan is found, maintenance personnel need to feed back maintenance information to the fault diagnosis system, the system can update the occurrence probability of the fault reason corresponding to the bottom event in the database, perform weight analysis on the fault reason again according to the occurrence probability of the fault reason, and update the fault reason corresponding to the fault and the fault processing plan in the diagnosis database at the same time, so that the accuracy of the fault diagnosis system is improved.
The failure weight analysis is the analysis method for determining the weight of each failure in diagnosis according to the probability of different failures. For example, the fault tree of the invention has two reasons for causing the sliding door resistance to be too large E1, and how to judge the fault is caused by X2 or X3E 1 needs to determine the occurrence probability of X2 and X3 in the diagnosis database, if P isx2>Px3The diagnostic system will preferentially push X2 as the cause of the fault E1, that is, X2 is at the top of the list of pushed fault causes, and simultaneously send all fault maintenance schemes corresponding to the bottom event X2 to the field maintenance personnel. When the system needs to feed back, the system updates the diagnosis system according to the need of feedback, when the need of feedback exists, the system updates the probability of all faults in the diagnosis database, redistributes the weight of each fault, establishes a one-to-one correspondence relationship between the corresponding fault reason and the maintenance scheme and the fault according to the feedback data, and avoids the influence on the accuracy of fault diagnosis caused by the occurrence of irrelevant faults or novel faults.
The fault diagnosis database is continuously accumulated and expanded along with the increase of the fault feedback information, and the larger the data volume of the database is, the higher the accuracy of fault diagnosis is. The maintenance personnel feed back the maintenance information to be fed back to the diagnosis system, so that the diagnosis database is in a continuously updated state, and the diagnosis blind spot and the error zone of the diagnosis system become smaller and smaller.
The invention has the following advantages:
(1) the fault diagnosis system adopts a platform door system fault tree model as a diagnosis basis, diagnoses fault reasons in a mode of comparing field fault numbers with a fault tree, pushes diagnosis results to maintenance personnel for fault maintenance, and feeds back and registers maintenance results.
(2) The weight analysis method solves the problem that a system cannot accurately diagnose the fault reason because one fault is caused by a plurality of bottom events together or any one of the bottom events can cause the same fault in fault diagnosis.
(3) And performing weight analysis on the fault maintenance information fed back by the maintenance personnel each time, inputting the analysis result into a station local database, and finally summarizing the fault data of different stations into a diagnosis database. Along with the continuous expansion of the data volume of the diagnosis database, the accuracy rate of fault diagnosis is improved.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims (4)

1. A platform door fault diagnosis and analysis method based on weight is characterized in that:
establishing a fault tree model of a platform door system, wherein the fault tree model comprises a top event, a middle event and a bottom event;
when a platform door system has a fault, inquiring all bottom events causing the fault through a fault tree model, sequencing all the bottom events from high to low according to the weight, and sending the bottom events to maintenance personnel;
the maintainer searches the fault reason and maintains according to the received sorted bottom event list;
and after the maintenance personnel finish the treatment, updating the weight of the bottom event according to the fault reason corresponding to the adopted fault.
2. The method of claim 1, wherein the method further comprises:
the weight of the bottom event is as follows:
and when the fault corresponding to the top event occurs N times, the probability that the occurrence frequency N of the fault reason corresponding to each bottom event occurs in the N faults.
3. The method of claim 1, wherein the method further comprises:
and each bottom event is simultaneously associated with a fault maintenance scheme of the fault event, and after receiving the sorted bottom event list, maintenance personnel search the bottom events according to the sorting and fault reasons corresponding to the bottom events until the bottom event causing the top event is found, and maintain the bottom events according to the fault maintenance schemes corresponding to the bottom events.
4. The method of claim 1, wherein the method further comprises:
in the maintenance process of maintenance personnel, if the fault reason causing the occurrence of the top event is not in the bottom event list, the fault reason is added into the bottom event to update the fault tree model, and meanwhile, the weight of the bottom event is updated.
CN201911393602.7A 2019-12-30 2019-12-30 Platform door fault diagnosis and analysis method based on weight Pending CN111160579A (en)

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112000750A (en) * 2020-08-07 2020-11-27 河北工业大学 T-S fault tree establishment method based on relational database
CN112084375A (en) * 2020-08-21 2020-12-15 华人运通(江苏)技术有限公司 Vehicle fault diagnosis method and device, terminal equipment and storage medium
CN112926824A (en) * 2021-01-20 2021-06-08 中国科学院微电子研究所 Fault diagnosis method for laser processing equipment
CN113283603A (en) * 2021-06-08 2021-08-20 华能(浙江)能源开发有限公司清洁能源分公司 Refined closed-loop fan fault diagnosis method and system
CN114358339A (en) * 2021-12-31 2022-04-15 卡斯柯信号(郑州)有限公司 Professional collaborative analysis method for urban rail transit platform door span
CN114594750A (en) * 2022-02-28 2022-06-07 杨少伟 Fault tree-based high-speed rail sliding plug door fault diagnosis method
CN115140102A (en) * 2022-05-18 2022-10-04 卡斯柯信号有限公司 Urban rail transit platform door linkage control fault detection method and device
CN115511136A (en) * 2022-11-01 2022-12-23 北京磁浮有限公司 Equipment fault auxiliary diagnosis method and system based on hierarchical analysis and fault tree
CN116501015A (en) * 2023-04-28 2023-07-28 中国人民解放军海军大连舰艇学院 Carrier-borne dragging electronic equipment carrier-based fault diagnosis method based on fault tree

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008094299A (en) * 2006-10-13 2008-04-24 Mitsubishi Electric Corp Platform door operation abnormality detection system
JP2015162090A (en) * 2014-02-27 2015-09-07 三菱日立パワーシステムズ株式会社 Fault diagnosis method and fault diagnosis apparatus
CN106050580A (en) * 2016-08-17 2016-10-26 国电联合动力技术有限公司 Method and system for diagnosing transmission chain fault of wind generating set
CN106528723A (en) * 2016-10-27 2017-03-22 重庆大学 Fault tree-based numerical control machine tool fault removal scheme judgment indication method
CN107807597A (en) * 2017-11-22 2018-03-16 广州新科佳都科技有限公司 A kind of cross-line road trans-regional new gate management method and system
CN108268023A (en) * 2016-12-30 2018-07-10 上海嘉成轨道交通安全保障系统股份公司 A kind of rail traffic platform door remote fault diagnosis method and system
CN110221198A (en) * 2019-05-31 2019-09-10 天地（常州）自动化股份有限公司 Underground coal mine stacked switch method for diagnosing faults based on fault tree

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008094299A (en) * 2006-10-13 2008-04-24 Mitsubishi Electric Corp Platform door operation abnormality detection system
JP2015162090A (en) * 2014-02-27 2015-09-07 三菱日立パワーシステムズ株式会社 Fault diagnosis method and fault diagnosis apparatus
CN106050580A (en) * 2016-08-17 2016-10-26 国电联合动力技术有限公司 Method and system for diagnosing transmission chain fault of wind generating set
CN106528723A (en) * 2016-10-27 2017-03-22 重庆大学 Fault tree-based numerical control machine tool fault removal scheme judgment indication method
CN108268023A (en) * 2016-12-30 2018-07-10 上海嘉成轨道交通安全保障系统股份公司 A kind of rail traffic platform door remote fault diagnosis method and system
CN107807597A (en) * 2017-11-22 2018-03-16 广州新科佳都科技有限公司 A kind of cross-line road trans-regional new gate management method and system
CN110221198A (en) * 2019-05-31 2019-09-10 天地（常州）自动化股份有限公司 Underground coal mine stacked switch method for diagnosing faults based on fault tree

Cited By (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112000750A (en) * 2020-08-07 2020-11-27 河北工业大学 T-S fault tree establishment method based on relational database
CN112084375B (en) * 2020-08-21 2023-06-16 华人运通(江苏)技术有限公司 Vehicle fault diagnosis method and device, terminal equipment and storage medium
CN112084375A (en) * 2020-08-21 2020-12-15 华人运通(江苏)技术有限公司 Vehicle fault diagnosis method and device, terminal equipment and storage medium
CN112926824A (en) * 2021-01-20 2021-06-08 中国科学院微电子研究所 Fault diagnosis method for laser processing equipment
CN113283603A (en) * 2021-06-08 2021-08-20 华能(浙江)能源开发有限公司清洁能源分公司 Refined closed-loop fan fault diagnosis method and system
CN114358339A (en) * 2021-12-31 2022-04-15 卡斯柯信号(郑州)有限公司 Professional collaborative analysis method for urban rail transit platform door span
CN114594750A (en) * 2022-02-28 2022-06-07 杨少伟 Fault tree-based high-speed rail sliding plug door fault diagnosis method
CN114594750B (en) * 2022-02-28 2024-05-31 杨少伟 High-speed rail sliding plug door fault diagnosis method based on fault tree
CN115140102A (en) * 2022-05-18 2022-10-04 卡斯柯信号有限公司 Urban rail transit platform door linkage control fault detection method and device
CN115140102B (en) * 2022-05-18 2024-03-29 卡斯柯信号有限公司 Urban rail transit platform door linkage control fault detection method and device
CN115511136B (en) * 2022-11-01 2023-06-30 北京磁浮有限公司 Equipment fault auxiliary diagnosis method and system based on analytic hierarchy process and fault tree
CN115511136A (en) * 2022-11-01 2022-12-23 北京磁浮有限公司 Equipment fault auxiliary diagnosis method and system based on hierarchical analysis and fault tree
CN116501015A (en) * 2023-04-28 2023-07-28 中国人民解放军海军大连舰艇学院 Carrier-borne dragging electronic equipment carrier-based fault diagnosis method based on fault tree
CN116501015B (en) * 2023-04-28 2024-01-30 中国人民解放军海军大连舰艇学院 Carrier-borne dragging electronic equipment carrier-based fault diagnosis method based on fault tree

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Application publication date: 20200515