CN103345207B - Mining analyzing and fault diagnosis system of rail transit monitoring data - Google Patents
Mining analyzing and fault diagnosis system of rail transit monitoring data Download PDFInfo
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Abstract
The invention discloses a mining analyzing and fault diagnosis system of rail transit monitoring data, and relates to the technical field of railway signals. The system comprises a signal monitoring system data processing unit, a data analyzing unit, a knowledge base unit and a fault diagnosis unit, wherein the signal monitoring system data processing unit is used for acquiring history railway signal monitoring data and real-time railway signal monitoring data from an on-site centralized signaling monitoring (CSM) device in each electric service workshop or work area. The data analyzing unit is used for analyzing the history railway signal monitoring data acquired by the signal monitoring system data processing unit, and generating fault diagnosis rules. The knowledge base unit is used for storing judging standards, and storing the fault diagnosis rules of the data analyzing unit, wherein the judging standards are formulated according to the work principle of each railway signal device and national and industry standards and specifications in the railway signal field and are used for fault diagnosis. The fault diagnosis unit is used for generating fault diagnosis results according to the fault diagnosis rules and the judging standards as for the real-time railway signal monitoring data acquired by the signal monitoring system data processing unit.
Description
Technical field
The present invention relates to railway signal technology field, particularly a kind of mining analysis of track traffic monitor data and fault diagnosis system.
Background technology
In order to improve the modernization maintenance level of China railways signal system equipment, from the nineties, the centralized signal supervision CSM system that successively independent development TJWX-I type and TJWX-2000 type etc. is constantly during upgrading.Current most of station all have employed computer monitoring system, achieve the Real-Time Monitoring to signaling at stations equipment state, and pass through the main running status of inspecting and recording signalling arrangement, grasp the current state of equipment for telecommunication and signaling branch and carry out crash analysis and provide basic foundation, having played vital role.Further, to Urban Rail Transit Signal equipment, Centralizing inspection CSM system is also widely deployed in the places such as city rail cluster/rolling stock section, for city rail O&M.
But, for the diagnosis aspect of a lot of complex apparatus fault and driving accident reason, this system is helpless, still need at present to rely on artificial experience analysis to judge, only just fault is found when there is significant problem in a lot of situation, when not only result in Artificial Diagnosis railway signal system fault, the technical matters such as large, the Fault monitoring and diagnosis inefficiency of workload, adds the danger of driving.
Summary of the invention
During in order to solve Artificial Diagnosis railway signal system fault in prior art, workload large, inefficiency, risk high-technology problem, the invention provides a kind of mining analysis and fault diagnosis system of track traffic monitor data.
The mining analysis of track traffic monitor data and a fault diagnosis system, comprising: signal monitoring system data processing unit, data analysis unit, repository unit, failure diagnosis unit and human-machine interface unit; Wherein,
Described signal monitoring system data processing unit, for gathering history monitor of the railway signal data and real-time monitor of the railway signal data in centralized signal supervision CSM equipment on-the-spot from each electricity business workshop or work area;
Described data analysis unit, for the history monitor of the railway signal data analysis gathered signal monitoring system data processing unit, generates Failure Diagnostic Code, and is sent to repository unit;
Described repository unit, for storing the criterion of fault diagnosis of principle of work according to each railway signals equipment, the country in railway signal field and industry standard, norm-setting, and stores the Failure Diagnostic Code of data analysis unit;
Described failure diagnosis unit, for the real-time monitor of the railway signal data gathered for signal monitoring system data processing unit, generates fault diagnosis result according to Failure Diagnostic Code and criterion;
Described human-machine interface unit, for showing user by fault diagnosis result.
Wherein, described data analysis unit comprises:
Data preparation module, analyzes data for selecting railway signal in the history monitor of the railway signal data from the collection of signal monitoring system data processing unit;
Data preprocessing module, the railway signal for selecting is analyzed data and is processed, and generates the data being suitable for excavating Failure Diagnostic Code;
Data-mining module, for adopting data mining algorithm to the data analysis of applicable excavation Failure Diagnostic Code, extracts data characteristics;
Pattern creation module, for according to the data characteristics extracted, generates Failure Diagnostic Code.
Wherein, described failure diagnosis unit comprises:
Characteristic extracting module, for the real-time monitor of the railway signal data analysis gathered for signal monitoring system data processing unit, and extracts data characteristics;
Diagnosis determination module, for mating the data characteristics that characteristic extracting module is extracted according to Failure Diagnostic Code and criterion, draws fault diagnosis result.
In preferred version, this system also comprises data warehouse unit;
Data analysis unit, also for the history monitor of the railway signal data of collection are sent to data warehouse unit; Correspondingly, this data warehouse unit, for storing described history monitor of the railway signal data.
By adopting by the monitor of the railway signal data acquisition on existing railway system centralized signal supervision CSM equipment out in the system that the present embodiment provides, history monitor of the railway signal data analysis according to gathering is out of order diagnostic rule, in conjunction with existing railway territory standard, diagnose for real-time monitor of the railway signal data, determine the technological means of railway signal system whether fault, solve in prior art, during Artificial Diagnosis railway signal system fault, workload is large, inefficiency, risk high-technology problem, and then obtain automatic diagnosis railway signal system fault, increase work efficiency, reduce artificial workload, find system problem as early as possible, reduce the technique effect of railway operation risk.
Accompanying drawing explanation
Accompanying drawing is used to provide a further understanding of the present invention, and forms a part for instructions, together with embodiments of the present invention for explaining the present invention, is not construed as limiting the invention.In the accompanying drawings:
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
A kind of mining analysis of track traffic monitor data that Fig. 1 provides for the embodiment of the present invention 1 and the structural representation of fault diagnosis system;
The another kind of mining analysis of track traffic monitor data that Fig. 2 provides for the embodiment of the present invention 1 and the structural representation of fault diagnosis system.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.Further, following embodiment is possibility of the present invention, embodiment put in order and the numbering of embodiment and its order preferably performed have nothing to do.
Embodiment 1
The present embodiment provides a kind of mining analysis and fault diagnosis system of track traffic monitor data, as shown in Figure 1, this system comprises: this signal monitoring system data processing unit of signal monitoring system data processing unit 11(can provide for existing CSM system, also can provide for any railway signal monitoring system later occurred), data analysis unit 12, repository unit 13, failure diagnosis unit 14 and human-machine interface unit 15; Wherein,
Signal monitoring system data processing unit 11, for gathering history monitor of the railway signal data and real-time monitor of the railway signal data in centralized signal supervision CSM equipment on-the-spot from each electricity business workshop or work area, and the history monitor of the railway signal data these collected and real-time monitor of the railway signal data are reported to data analysis unit 12.
In the present embodiment, history monitor of the railway signal data are the same with the content of real-time monitor of the railway signal data, include interlocking, obturation, row control, hump, TDCS(dispatch control management system)/CTC(dispatching concentration control system) and the status data of the signalling arrangement such as power supply panel.Unlike: history monitor of the railway signal data are monitor of the railway signal data in the past that signalling arrangement is preserved, the status data under known device state status is included in these data, such as determine that signalling arrangement state is fault, and the status data of this signalling arrangement under this malfunction; Real-time monitor of the railway signal data to be signalling arrangement equipment states be at that time unknown when status data, such as: the status data that signalling arrangement has just produced, also this signalling arrangement unknown whether fault or normal etc.
Data analysis unit 12, for the history monitor of the railway signal data analysis gathered signal monitoring system data processing unit 11, generates Failure Diagnostic Code, and Failure Diagnostic Code is sent to repository unit 13.
Repository unit 13, for storing the criterion of fault diagnosis of principle of work according to each railway signals equipment, the country in railway signal field and industry standard, norm-setting, and stores the Failure Diagnostic Code of data analysis unit 12;
Failure diagnosis unit 14, for the real-time monitor of the railway signal data gathered for signal monitoring system data processing unit 11, generate fault diagnosis result according to the Failure Diagnostic Code in repository unit and criterion, this fault diagnosis result can think a kind of fault diagnosis result of real time data;
Human-machine interface unit 15, for showing user by fault diagnosis result.
This system that the present embodiment provides works in coordination with the assembly with O&M information system (patent No. is the application documents of 201310190664.4) as track traffic synthetic monitoring and dispatching, device level, system-level and application layer can be run on, complete signal data analysis at different levels and fault diagnosis.Device level can utilize the device level data of collection, carry out real-time analysis and the fault diagnosis of device signal.According to the relation between equipment on system-level, package signal data, carries out fault diagnosis.Application layer obtains device level and system-level data from data warehouse, carries out data mining analysis and fault diagnosis, and carries out the issue of diagnostic result.
Further in preferred version, the system that the present embodiment provides can also comprise: data warehouse unit 16.
Data analysis unit 12, also for the history monitor of the railway signal data of collection are sent to data warehouse unit 16; Data warehouse unit 16, for storing described history monitor of the railway signal data.
Data analysis unit 12, also for real-time monitor of the railway signal data are sent to data warehouse unit 16; Correspondingly, data warehouse unit 16, also for real-time monitor of the railway signal data penetration transmission that data analysis unit 12 is sent to failure diagnosis unit 14, data warehouse unit 16 is also by backup this real-time monitor of the railway signal data and then storage simultaneously.
Failure diagnosis unit 14, also for for the history monitor of the railway signal data stored in data warehouse unit 16, generates fault diagnosis result according to Failure Diagnostic Code and criterion.This fault diagnosis result also can think a kind of fault diagnosis result of historical data.
Data warehouse unit 16 effect is in the present embodiment mainly used in that each electricity business workshop or the Monitoring Data of preserving separately break are concentrated on upper strata and saves, for fault diagnosis or follow-up otherwise application.
Lower mask body introduces the function of above-mentioned each unit in the system that the present embodiment provides.
1, signal monitoring system data processing unit 11, specifically for the mode by collector of switching value, intelligent sensor and loop line in centralized signal supervision CSM equipment on-the-spot from each electricity business workshop or work area, obtain switching value and analog data from needing relay, the module of monitoring; Those are had to equipment or the system of unified interface, as automatic block system, intelligent power supply panel, computer interlock etc., by bus mode, directly gather from unified interface the monitor of the railway signal data specified Ministry of Railways's interface specification.
2, data analysis unit comprises 12:
Data preparation module 121, analyzes data for selecting suitable railway signal in the history monitor of the railway signal data from the collection of signal monitoring system data processing unit.
Above-mentioned suitable railway signal analysis data refer to the status data under known device state status.Equipment state at that time in history monitor of the railway signal data can be gone forward side by side the data of line item as the status data under known device state status through artificial judgment.
Data preprocessing module 122, processing for analyzing data to the railway signal selected, generating the data being suitable for excavating Failure Diagnostic Code.
Data preprocessing module 122 is mainly used in analyzing data to railway signal and carries out pre-service, and pretreated analysis data are the data being suitable for excavating fault diagnosis fault.This pre-service mainly comprises: data scrubbing and integrated, remove noise data, non-data available, original railway signal is analyzed data normalization, standardization multiple data source being combined, be applicable type by data type conversion again, define new data attribute, reduce data dimension and size.
Data scrubbing (Data Cleaning) is by filling in vacancy value, smooth noise data, identifies, deletes isolated point, and solve inconsistence problems to realize " cleaning " data.Solve because dirty data can make mining process fall into chaos, cause insecure output.
Data integration (Data Integration) often needs the data coming from multiple data source to be carried out merging and stores when being and considering and excavate Failure Diagnostic Code, data sometimes also may be needed to convert to the form being suitable for excavating.
Remove noise data, non-data available, original railway signal is analyzed data normalization, standardization multiple data source combined and refer to data regularization (Data Reduction).Such as by large data collection compression expression, make the data set after reduction excavates and more effectively, and the Result of identical (or almost identical) will be produced.Mainly comprise eigenwert reduction, feature reduction and sample reduction.
Data-mining module 123, for adopting data mining algorithm to the data analysis of applicable excavation Failure Diagnostic Code, extracts data characteristics.
Data mining algorithm in the present embodiment comprises: data are classified, isolated point, association rule mining, time series analysis, the method such as Algorithm for Attribute Reduction.
1) sorting technique: fault detect is will by analytic signal data, determine that whether equipment work is normal, namely data to be divided into normal and abnormal two classes, so fault diagnosis can be regarded as classification problem, carry out fault detect with the sorting technique in data mining.
2) isolated charged body: when equipment operation irregularity, corresponding signal data is inconsistent with signal data when normally working, namely the relative normal data of fault data is isolated point, so the isolated charged body method in data mining can be adopted to carry out fault detect.
3) association rule mining: Association Rules Technology lays particular emphasis on the contact determined in data not between same area, finds out the dependence met between given support and multiple territories of confidence threshold value.Association analysis finds correlation rule, and these rules show that " attribute-value " concentrates the condition occurred together continually at data-oriented.By association analysis, the incidence relation between possible discovering device fault mode and the potential incidence relation between discovering device different operating parameter.
4) time series analysis: monitoring of equipment data are time dependent time series datas, adopt the data digging method of time series analysis, comprise trend analysis, similarity searching, excavate with the sequence pattern of time relevant data and cyclic pattern, and dynamic time warping and temporal signatures extraction.
Data-mining module effect is exactly briefly selected from large quantities of data with the relevant data of a certain fault by data mining algorithm, and these data is extracted as data characteristics.Therefore, data-mining module extract data characteristics can characterize fault exactly, or a part of data associate with fault phase or pass through convert after data representation.Concrete mining process is with reference to lower example.
Such as: utilize Algorithm for Attribute Reduction to carry out fault signature extraction
Algorithm is as follows:
Input: decision table S=(U, C ∪ D) and user important attribute Y, wherein C is conditional attribute collection (i.e. bug list collection), and comprise n conditional attribute, D is decision attribute (i.e. fault category), and Y is user's reserved property.
Export: Attribute Reduction Set R.
Basic ideas: from single-row C1, calculating can correctly to decision attribute D(and fault type according to it) the classification number distinguished | POS
c1(D) | (namely C1 is to classification number in the positive territory of D), calculating can correctly to the classification number that D distinguishes according to two row again ... until obtain m row, arrange (m<=n) according to this m and have identical separating capacity (namely arranging the classification number of correctly classifying to D according to this m identical with the classification number of classifying according to C) to D and whole conditional attribute collection C, this m row are exactly the set after yojan.
Following table one be from signal monitoring system acquisition to partial history monitor of the railway signal data fault sample collection:
Table one
Wherein, decision attribute is fault code name, and conditional attribute a-g is each attribute corresponding to fault, and be Property Name in bracket, be sensing station label, the value in form is that each measurement value sensor is by the value after a certain scope sliding-model control.
It can be used as input decision table, after program, obtaining attribute a, d, e is attribute after one group of yojan, thus can obtain the decision table after yojan, as following table two:
Table two
Wherein, conditional attribute can as the data characteristics extracted.
Pattern creation module 124, for according to the data characteristics extracted, generates Failure Diagnostic Code.
Diagnosis rule is exactly the judgment expression of one group of fault, is generally the form of If< condition >Then< conclusion >, its represent under current condition, institute may correspondence fault.
Such as: association rule digging carries out Failure Diagnostic Code, and to set up algorithm as follows:
Input: Mishap Database (FDB), minimum support threshold value (min_sup), Minimum support4 threshold value (min_conf)
Export: diagnosis rule storehouse, obtains the rule of correspondence of fault signature and failure modes.
Association rule mining algorithms carries out the foundation in Failure Diagnostic Code storehouse, works as min_sup=20%, and during min_conf=80%, its result is as following table three:
| B2 | A2 | E6 | E1 | A1 | E10 | D1 | E5 | FaultNum |
| 0 | <NULL> | <NULL> | <NULL> | <NULL> | <NULL> | <NULL> | <NULL> | 4 |
| <NULL> | <NULL> | <NULL> | 1 | <NULL> | <NULL> | <NULL> | <NULL> | 3 |
| <NULL> | <NULL> | <NULL> | <NULL> | 0 | <NULL> | <NULL> | <NULL> | 3 |
| <NULL> | <NULL> | <NULL> | <NULL> | <NULL> | 1 | <NULL> | <NULL> | 2 |
| <NULL> | 0 | <NULL> | <NULL> | <NULL> | <NULL> | 0 | <NULL> | 3 |
| <NULL> | <NULL> | 1 | 0 | <NULL> | <NULL> | <NULL> | <NULL> | 2 |
| <NULL> | <NULL> | 1 | <NULL> | <NULL> | <NULL> | <NULL> | 0 | 3 |
| <NULL> | <NULL> | 1 | <NULL> | <NULL> | <NULL> | <NULL> | 1 | 2 |
| <NULL> | <NULL> | <NULL> | <NULL> | <NULL> | <NULL> | 0 | 1 | 3 |
| <NULL> | <NULL> | <NULL> | <NULL> | <NULL> | <NULL> | 1 | 0 | 3 |
| 1 | 0 | 1 | <NULL> | <NULL> | <NULL> | <NULL> | <NULL> | 1 |
| <NULL> | 1 | 0 | 0 | <NULL> | <NULL> | 1 | <NULL> | 4 |
| <NULL> | 1 | 0 | 0 | <NULL> | <NULL> | <NULL> | 1 | 4 |
Table three
As can be seen from Table III, under the condition with high confidence and support, the rule obtained also cover all failure modess, so just obtains the diagnosis rule storehouse (i.e. the set of Failure Diagnostic Code) comparatively having directiveness.
Rule Expression in diagnosis rule storehouse is as follows:
rule：
If ZQJ1-4is has electricity
Then conclude fault is ZQJ1-4 breaks
rule：
If ZQJ1-4is is without electricity
And if ZQJ1is is without KF
Then conclude fault is ZQJ4 ~ KF intermittent line
rule：
If ZQJ1-4is is without electricity
And if ZQJ1is is without KZ
And combined side end 05-5is has KZ
Then conclude fault is05-5 ~ ZQJ1 intermittent line
……
3, failure diagnosis unit 14 comprises:
Characteristic extracting module 141, for the real-time monitor of the railway signal data analysis gathered for signal monitoring system data processing unit, and extracts data characteristics.
Characteristic extracting module 141 in the present embodiment is identical with the process of above-mentioned data-mining module to the data analysis of applicable excavation Failure Diagnostic Code to the process of real-time monitor of the railway signal data analysis, and the data characteristics that characteristic extracting module is extracted is also identical with the data characteristics that above-mentioned data-mining module extracts.Difference is, the data characteristics that data-mining module extracts is used for generating Failure Diagnostic Code, and the data characteristics that characteristic extracting module is extracted is used for diagnostic signal equipment whether fault.
Diagnosis determination module 142, mates for the data characteristics of carrying out according to Failure Diagnostic Code and criterion characteristic extracting module is extracted, draws preliminary fault diagnosis result.
From above-mentioned table three, diagnosis determination module 142 can with the rule in diagnosis rule storehouse for condition be mated the data characteristics that characteristic extracting module is extracted one by one in conjunction with criterion, if the Condition Matching of a certain fault in the data characteristics extracted and diagnosis rule storehouse can tentative diagnosis be then fault.
Explain decision-making module 143, for the reasoning that makes an explanation to fault, determine failure cause.
This module with reference to the information content stored in existing expert system, can make an explanation to fault.
Signal monitoring system data processing unit 11, data analysis unit 12, repository unit 13, failure diagnosis unit 14, human-machine interface unit 15 and data warehouse unit 16 that the present embodiment provides can be the application documents of 201310190664.4 to the patent No. as one group of plug-in unit, denomination of invention is that a kind of track traffic synthetic monitoring and scheduling is collaborative with O&M information system, realizes systemic-function level schematic diagram as shown in Figure 4 in this system.Specifically, each unit that the present embodiment provides can be inserted into track traffic synthetic monitoring and dispatching as fault diagnosis assembly and work in coordination with the application support layer with O&M informatization platform, also can be divided into the device level be inserted into the form of assembly in the monitor layer that above-mentioned patent document mentions, system-level, application layer etc.It is strong that the system provided due to the present embodiment has transplantability, the features such as diversification of forms, therefore both can be connected with existing railway electrical CSM system and realize corresponding function, the track traffic monitoring systems such as CSM system that also can be new with the following railway system are connected, realize the continuity of native system, system is possessed follow the migration transfer ability of railway system's device upgrade.
By adopting by the monitor of the railway signal data acquisition on existing railway system centralized signal supervision CSM equipment out in the system that the present embodiment provides, history monitor of the railway signal data analysis according to gathering is out of order diagnostic rule, in conjunction with existing railway territory standard, diagnose for real-time monitor of the railway signal data, the technological means of the duty determining railway signal system whether fault, solve in prior art, during Artificial Diagnosis railway signal system fault, workload is large, inefficiency, risk high-technology problem, and then obtain automatic diagnosis railway signal system fault, increase work efficiency, reduce artificial workload, find system problem as early as possible, reduce the technique effect of railway operation risk.
The above, be only the specific embodiment of the present invention, but the present invention can have multiple multi-form embodiment, by reference to the accompanying drawings the present invention is illustrated above, this does not also mean that the embodiment that the present invention applies can only be confined in these specific embodiments, those skilled in the art should understand, embodiment provided above is some examples in multiple preferred implementation, and the embodiment of any embodiment the claims in the present invention all should within the claims in the present invention scope required for protection; Those skilled in the art can modify to technical scheme described in each embodiment above, or carries out equivalent replacement to wherein portion of techniques feature.Within the spirit and principles in the present invention all, any amendment done, equivalent to replace or improvement etc., within the protection domain that all should be included in the claims in the present invention.
Claims (7)
1. the mining analysis of track traffic monitor data and a fault diagnosis system, is characterized in that, comprising: signal monitoring system data processing unit, data analysis unit, repository unit, failure diagnosis unit and human-machine interface unit; Wherein,
Described signal monitoring system data processing unit, for gathering history monitor of the railway signal data and real-time monitor of the railway signal data in centralized signal supervision CSM equipment on-the-spot from each electricity business workshop or work area;
Described data analysis unit, for the history monitor of the railway signal data analysis gathered signal monitoring system data processing unit, generates Failure Diagnostic Code, and this Failure Diagnostic Code is sent to repository unit;
Described repository unit, for storing the criterion of fault diagnosis of principle of work according to each railway signals equipment, the country in railway signal field and industry standard, norm-setting, and stores the Failure Diagnostic Code of data analysis unit;
Described failure diagnosis unit, for the real-time monitor of the railway signal data gathered for signal monitoring system data processing unit, generates fault diagnosis result according to Failure Diagnostic Code and criterion;
Described human-machine interface unit, for showing user by fault diagnosis result.
2. system according to claim 1, is characterized in that, described data analysis unit comprises:
Data preparation module, analyzes data for selecting railway signal in the history monitor of the railway signal data from the collection of signal monitoring system data processing unit;
Data preprocessing module, the railway signal for selecting is analyzed data and is processed, and generates the data being suitable for excavating Failure Diagnostic Code;
Data-mining module, for adopting data mining algorithm to the data analysis of the Failure Diagnostic Code that is applicable to finishing, extracts data characteristics;
Pattern creation module, for according to the data characteristics extracted, generates Failure Diagnostic Code.
3. system according to claim 1 and 2, is characterized in that, described failure diagnosis unit comprises:
Characteristic extracting module, for the real-time monitor of the railway signal data analysis gathered for signal monitoring system data processing unit, and extracts data characteristics;
Diagnosis determination module, for mating the data characteristics that characteristic extracting module is extracted according to Failure Diagnostic Code and criterion, draws fault diagnosis result.
4. system according to claim 3, is characterized in that, failure diagnosis unit also comprises:
Explain decision-making module, for the reasoning that makes an explanation to fault, determine failure cause.
5. system according to claim 1, is characterized in that, this system also comprises data warehouse unit;
Described data analysis unit, also for the history monitor of the railway signal data of collection are sent to data warehouse unit;
Described data warehouse unit, for storing described history monitor of the railway signal data.
6. system according to claim 5, is characterized in that,
Described data analysis unit, also for real-time monitor of the railway signal data are sent to data warehouse unit;
Described data warehouse unit, the real-time monitor of the railway signal data penetration transmission also come for data analysis unit being sent is to failure diagnosis unit.
7. system according to claim 5, is characterized in that,
Described failure diagnosis unit, also for for the history monitor of the railway signal data stored in data warehouse unit, generates fault diagnosis result according to Failure Diagnostic Code and criterion.
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