A train running state safety monitoring method based on data analysis

Abstract

The present application relates to the field of train safety monitoring, especially relates to a train running state safety monitoring method based on data analysis, comprising, under the condition of abnormal change analysis, determining the data analysis strategy of each change analysis system according to the trend change stability index and the change duration index; when performing loss feature analysis, determining the correlation change proportion based on the similar change coefficient and the position correlation coefficient of each change analysis system, and determining whether to perform change data processing on the loss analysis system according to the correlation change proportion to determine the key monitoring data; when performing data compression analysis, determining the compression analysis mode of each change analysis data of the compression analysis system according to the relevant monitoring data proportion to obtain the key monitoring data; under the condition of analysis completion, sending the key monitoring data to the user, the present application improves the effectiveness and timeliness of the abnormal monitoring result of the train door.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of train safety monitoring, and in particular to a train running state safety monitoring method based on data analysis. BACKGROUND

[0002] The monitoring result of the subway running state has important reference value for ensuring the overall operation efficiency and operation and maintenance optimization quality of the subway. With the gradual popularization of subway transportation, the opening and closing operation of subway train doors gradually increases. The reliability of the monitoring result of the abnormal state of the train door has a great influence on the safety and operation efficiency of the subway. However, the existing abnormal state monitoring of the subway train door is often based only on whether each item of data exists in the corresponding threshold range, without considering different abnormal factors corresponding to the change of each related data of the train door in the actual running process, thereby resulting in poor effectiveness and timeliness of the abnormal monitoring result of the train door, and being unable to effectively prevent the subway vehicle operation risk caused by the abnormal state of the train door. Therefore, how to determine a targeted data analysis process in combination with the change of each related data of the train door in the actual running process to improve the effectiveness and reliability of the data extracted for analyzing the abnormal reason is a problem to be solved by those skilled in the art.

[0003] Chinese Patent Application Publication No. CN114692904A discloses a health management system for urban subway train doors, comprising: a data acquisition module for acquiring and processing train door information of urban subway vehicles on each line; a user login module for user authentication; a monitoring management module for viewing train door information of urban subway vehicles on each line; an alarm management module for generating real-time alarm information of train doors on the entire line of the urban subway; an early warning management module for generating early warning information of train doors on the entire line of the urban subway; an operation and maintenance module for uploading, updating and displaying subway train door operation and maintenance information; and a configuration management module for system configuration management. However, the above-mentioned scheme has the following problems: it fails to determine a targeted data analysis process in combination with the change of each related data of the train door in the actual running process, resulting in low effectiveness and reliability of the data extracted for analyzing the abnormal reason, and thereby resulting in poor effectiveness and timeliness of the abnormal monitoring result of the train door. SUMMARY

[0004] Therefore, the present application provides a train running state safety monitoring method based on data analysis to overcome the problem in the prior art that the data analysis process is not determined in combination with the change of each related data of the train door in the actual running process, resulting in low effectiveness and reliability of the data extracted for analyzing the abnormal reason, and thereby resulting in poor effectiveness and timeliness of the abnormal monitoring result of the train door.

[0005] To achieve the above object, the application provides a train running state safety monitoring method based on data analysis, comprising:

[0006] Under the abnormal change analysis condition, the data analysis strategy of each change analysis system is determined according to the trend change stability index and the change duration index, and the change analysis system is subjected to loss feature analysis or data compression analysis;

[0007] When the loss feature analysis is performed, the associated change proportion is determined based on the similar change coefficient and the position correlation coefficient of each change analysis system, and whether the change data processing is performed on the loss analysis system is determined according to the associated change proportion, so as to determine the key monitoring data;

[0008] When the data compression analysis is performed, the compression analysis mode of each change analysis data of the compression analysis system is determined according to the relevant monitoring data proportion, so as to obtain the key monitoring data, and the compression analysis mode is that the data compression threshold of each monitoring data segment is set according to the stage coincidence index, or the data compression threshold is set based on the relevant monitoring data proportion;

[0009] Under the analysis completion condition, the key monitoring data is sent to the user, and the analysis completion condition is that the loss feature analysis or the data compression analysis of the change analysis system is completed.

[0010] Further, under the abnormal change analysis condition, the trend change stability index and the change duration index of each change analysis system are detected;

[0011] For a single change analysis system,

[0012] The trend change stability index is determined according to the change index of each change analysis data of the change analysis system in the change evaluation stage;

[0013] The change duration index is determined according to the change direction of the change index obtained each time in the change evaluation stage;

[0014] The abnormal change analysis condition is that the target monitoring train has a door system that needs to be subjected to change analysis, and the door system that needs to be subjected to change analysis is recorded as a change analysis system.

[0015] Further, if the change stability coefficient of a change analysis system is greater than a preset change stability coefficient, the loss feature analysis is performed on the change analysis system, comprising:

[0016] The change analysis system is recorded as a loss analysis system, and the associated change proportion of the loss analysis system is determined based on the similar change coefficient and the position correlation coefficient of each change analysis system in the associated evaluation range;

[0017] The change data processing is performed on the loss analysis system according to the correlation change proportion;

[0018] The change stability coefficient is determined according to the trend change stability index and the change duration index.

[0019] Further, for a single loss analysis system, the correlation change index of each change analysis system in the correlation evaluation range is determined according to the similarity change coefficient and the position correlation coefficient;

[0020] If the correlation change index of any change analysis system in the correlation evaluation range is greater than the preset correlation change index, the change analysis system is recorded as the correlation change system of the loss analysis system.

[0021] The similarity change coefficient is determined according to the number of coincident monitoring data of each change analysis system and the stability coefficient difference value, and the position correlation coefficient is determined according to the air pressure interference index of each change analysis system.

[0022] Further, if the correlation change proportion of the loss analysis system is greater than the preset correlation change proportion, the change data processing is performed on the loss analysis system to determine the key monitoring data of the loss analysis system.

[0023] When the change data processing is performed, the reference change trend index of each trend analysis stage is determined based on the coincident monitoring data of the loss analysis system and its correlation change system.

[0024] The change trend matching degree of each monitoring data is determined based on the reference change trend index of each trend analysis stage and the matching evaluation coefficient, and the key monitoring data of the loss analysis system is determined according to the change trend matching degree.

[0025] Further, it is determined whether to adjust the matching evaluation coefficient corresponding to each trend analysis stage according to the change difference coefficient.

[0026] If the change difference coefficient of a trend analysis stage is greater than the preset change difference coefficient, the matching evaluation coefficient is adjusted by decreasing according to the change difference coefficient.

[0027] The decreasing value of the matching evaluation coefficient and the change difference coefficient are in a positive correlation.

[0028] Further, if the change stability coefficient of a change analysis system is less than or equal to the preset change stability coefficient, data compression analysis is performed on the change analysis system, including:

[0029] The change analysis system is recorded as a compression analysis system, the compression analysis mode of each change analysis data of the compression analysis system is determined according to the relevant monitoring data proportion, and the compression processing is performed on each change analysis data to obtain the key monitoring data.

[0030] Further, for any change analysis data of the compression analysis system, if the relevant monitoring data proportion is greater than the preset relevant monitoring data proportion, the monitoring stage of the change analysis data is divided, and the data compression threshold of each monitoring data segment is set according to the stage coincidence index;

[0031] The data compression threshold and the stage coincidence index are in a negative correlation relationship.

[0032] Further, whether the data compression threshold of each monitoring data segment is adjusted again is determined according to the reference change index;

[0033] For a single monitoring data segment, if the reference change index is greater than the preset reference change index, the data compression threshold is adjusted by decreasing according to the reference change index;

[0034] The decreasing value of the data compression threshold and the reference change index are in a positive correlation relationship.

[0035] Further, for any change analysis data of the compression analysis system, if the relevant monitoring data proportion is less than or equal to the preset relevant monitoring data proportion, the data compression threshold is determined based on the relevant monitoring data proportion, and the change analysis data is compressed according to the data compression threshold;

[0036] The data compression threshold and the relevant monitoring data proportion are in a negative correlation relationship.

[0037] Compared with the prior art, the beneficial effects of the present application are that the data analysis strategy of each change analysis system is determined according to the trend change stability index and the change duration index, so as to determine the key monitoring data of each change analysis system, so that the analysis process of the change analysis system is more in line with the actual working condition, the effectiveness of the data extracted from the change analysis system for analyzing the abnormal reason is guaranteed, and the effectiveness and timeliness of the abnormal monitoring result of the train door are improved.

[0038] Further, in the present application, the change stability coefficient of each change analysis system is determined according to the trend change stability index and the change duration index, and then the specific data analysis strategy is determined according to the size relationship between the change stability coefficient and the preset value, the change stability coefficient is used to determine whether the data change of the change analysis system has a change in time sequence, and then it is determined whether the change of the monitoring data is related to the loss caused by the train operation, and the effectiveness of the data extracted from the change analysis system for analyzing the abnormal reason is improved.

[0039] Further, in the present application, the loss characteristic analysis is carried out on the change analysis system with large change stability coefficient, the associated change system of the change analysis system is determined through the similar change coefficient and the position correlation coefficient, and then whether to carry out change data processing on the change analysis system is determined according to the associated change proportion, when the associated change proportion is large, it is indicated that there are more other vehicle door systems that can be used for cooperative analysis of the vehicle door loss in the change analysis system, and cooperative analysis is carried out to determine the reference change trend index of different trend analysis stages, and then the monitoring data of the fitting curve that can be used to analyze the loss of the change analysis system is further determined, and the effectiveness of the abnormal monitoring result of the train door is improved.

[0040] Further, in the present application, in the process of determining the key monitoring data of the loss analysis system, the matching evaluation coefficient of each trend analysis stage is determined through the running load condition of the target monitoring train, and whether the matching evaluation coefficient needs to be compensated and adjusted is determined according to the change difference coefficient, so as to ensure the accuracy of the determination result of the key monitoring data, and the effectiveness of the abnormal monitoring result of the train door is improved.

[0041] Further, in the present application, data compression analysis is carried out on the change analysis system with small change stability coefficient, the compression analysis mode of each change analysis data is determined through the proportion of related monitoring data, so that the compression process of each change analysis data is more in line with the actual data condition, and the reconstruction precision of the compressed data is ensured to be in line with the key degree of the data under the condition of ensuring the compression quality requirement, the effectiveness and transmission execution efficiency of the determination result of the key data are improved, and the effectiveness and timeliness of the abnormal monitoring result of the train door are improved. BRIEF DESCRIPTION OF DRAWINGS

[0042] Fig. 1 It is a schematic diagram of the train running state safety monitoring method based on data analysis of the present application;

[0043] Fig. 2 It is a flow chart of determining the data analysis strategy of each change analysis system according to the trend change stability index and the change duration index of the present application;

[0044] Fig. 3 It is a flow chart of determining whether to carry out change data processing on the loss analysis system according to the associated change proportion of the present application;

[0045] Fig. 4 It is a flow chart of determining whether to adjust the matching evaluation coefficient corresponding to each trend analysis stage according to the change difference coefficient of the present application. DETAILED DESCRIPTION

[0046] In order to make the objects, technical schemes and advantages of the present application clearer, the following further describes the present application with reference to the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0047] The preferred embodiments of the present application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and are not used to limit the protection scope of the present application.

[0048] It should be noted that, in the description of the present application, the terms indicating the direction or positional relationship such as "upper", "lower", "left", "right", "inner", "outer" and the like are based on the direction or positional relationship shown in the drawings, which is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application.

[0049] In addition, it should be noted that, in the description of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connection" should be understood broadly, for example, it can be fixed connection, or detachable connection, or integral connection; it can be mechanical connection, or electrical connection; it can be direct connection, or indirect connection through an intermediate medium, or internal communication of two elements. Those skilled in the art can understand the specific meaning of the above terms in the present application according to the specific circumstances.

[0050] Please refer to Figs. 1 to 4 As shown in the drawings, the present application provides a train running state safety monitoring method based on data analysis, comprising:

[0051] Under the abnormal change analysis condition, the change characteristic analysis strategy of each change analysis system is determined according to the trend change stability index and the change duration index, which is loss characteristic analysis or feature mining analysis for the change analysis system;

[0052] Under the abnormal change analysis condition, the data analysis strategy of each change analysis system is determined according to the trend change stability index and the change duration index, which is loss characteristic analysis or data compression analysis for the change analysis system;

[0053] When performing loss characteristic analysis, the associated change proportion is determined based on the similar change coefficient and the position correlation coefficient of each change analysis system, and whether to perform change data processing for the loss analysis system is determined according to the associated change proportion, so as to determine the key monitoring data;

[0054] When performing data compression analysis, the compression analysis method of each change analysis data in the compression analysis system is determined according to the proportion of relevant monitoring data in order to obtain key monitoring data. The compression analysis method is to set the data compression threshold for each monitoring data segment according to the stage overlap index, or to set the data compression threshold based on the proportion of relevant monitoring data.

[0055] Upon completion of the analysis, key monitoring data is sent to the user. The completion of the analysis is indicated by the system completing either loss characteristic analysis or data compression analysis.

[0056] This invention is used for operational monitoring of the door system of subway trains. The subway train being monitored is designated as the target monitoring train. In this invention, each train door and the motors and other components used to control the opening and closing of the corresponding train doors are collectively referred to as the door system. The monitoring data includes data corresponding to different stages during the execution of the door opening and closing and door locking tasks. The monitoring data in this invention includes, but is not limited to: the speed and acceleration changes of the doors during the execution of the door opening and closing and door locking tasks, the vibration frequency and amplitude of the doors during the execution of the door opening and closing and door locking tasks, and the voltage, current and temperature of the motors during the execution of the door opening and closing and door locking tasks.

[0057] In this invention, each door system must complete the door opening and closing task and the door locking task. For a single door system, the start time of the door opening and closing task is the time when the door system receives the door opening command, and the end time of the door opening and closing task is the time when the door system completes the opening of the train door. The start time of the door locking task is the time when the door system receives the door closing command, and the end time of the door locking task is the time when the door system completes the closing of the train door.

[0058] This invention utilizes several operational monitoring records. Each operational monitoring record records at least one instance of abnormal monitoring of the various door systems of the target monitoring train, including the change index, change stability coefficient, associated change index, associated change percentage, change trend matching degree, change difference coefficient, and the percentage of relevant monitoring data. Furthermore, each operational monitoring record has a corresponding qualified mark, which records whether the timeliness and accuracy of the monitoring results for the door system meet the user's requirements.

[0059] Specifically, under abnormal change analysis conditions, the trend change stability index and change persistence index of each change analysis system are detected;

[0060] For a single change analysis system,

[0061] The trend change stability index is determined according to the change index of each change analysis data of the change analysis system in the change evaluation stage;

[0062] The change persistence index is determined according to the change direction of the change index acquired by the change analysis system in the change evaluation stage;

[0063] The abnormal change analysis condition is that the target monitored train has a door system that needs to be subjected to change analysis, and the door system that needs to be subjected to change analysis is recorded as a change analysis system.

[0064] The monitoring data of each door system when performing the door opening / closing task or the door locking task is acquired, and it is determined whether each door system needs to be subjected to change analysis. For any monitoring data of a single door system, the change index = |the value of the currently acquired monitoring data - the value of the monitoring data acquired at the time closest to the current acquisition time| / the value of the monitoring data acquired at the time closest to the current acquisition time. If the change index of the monitoring data is greater than a preset change index, the monitoring data is recorded as change analysis data.

[0065] The preset change index can be determined by the user according to the actual working scene. For example, the user can set it according to the operation monitoring record. The higher the user's requirement for the timeliness and accuracy of the monitoring result of the door system, the smaller the value of the preset change index. A method for determining the value of the preset change index is provided. The minimum value of the change index of the change analysis data in the operation monitoring record that meets the user's requirement for the timeliness and accuracy of the monitoring result of the door system is recorded as the preset change index.

[0066] For a single door system, if any monitoring data of the door system is change analysis data, it is determined that the door system needs to be subjected to change analysis. If any door system of the target monitored train needs to be subjected to change analysis, it is determined that the target monitored train is in an abnormal change analysis condition. In the abnormal change analysis condition, the trend change stability index and the change persistence index of each change analysis system are detected. For any door system, the end time of the change evaluation stage is the time when the door system is determined to be a change analysis system. The duration of the change evaluation stage and the number of change analysis data of the change analysis system are in a positive correlation relationship. The trend change stability index = 1 / the maximum value of the trend change index of each change analysis data in the change analysis system. The trend change index of each change analysis data is determined according to the change index acquired by the change analysis data in the change evaluation stage. For a single change analysis data, the trend change index n is the number of door opening and closing tasks completed by the vehicle door system in the change evaluation stage, qi is the change index of the change analysis data obtained when the ith door opening and closing task is completed in the change evaluation stage, q0 is the average value of the change index of the change analysis data obtained when each door opening and closing task is completed in the change evaluation stage, and the completion of the door closing task after the completion of the door opening task is completed once, the change stability coefficient is the average value of the change direction matching degree of each change analysis data in the change analysis system, for a single change analysis data, the change direction matching degree = the number of times that the change direction of the change index of the change analysis data obtained in the change analysis stage is consistent with the stage change direction / the number of times that the change index of the change analysis data obtained in the change evaluation stage, the stage change value is the difference between the value of the change analysis data obtained last time in the change evaluation stage and the value of the change analysis data obtained first time, for a single determined change index, if the difference between the value of the change analysis data obtained later and the value of the change analysis data obtained previously is greater than 0 or less than 0 at the same time as the stage change value, it is determined that the change direction of the determined change index is consistent with the stage change direction.

[0067] Specifically, if the change stability coefficient of a change analysis system is greater than a preset change stability coefficient, the wear characteristic analysis is performed on the change analysis system, including:

[0068] The change analysis system is recorded as a wear analysis system, and the associated change proportion of the wear analysis system is determined based on the similar change coefficient and the position correlation coefficient of each change analysis system in the associated evaluation range;

[0069] According to the associated change proportion, it is determined whether to perform change data processing on the wear analysis system;

[0070] The change stability coefficient is determined according to the trend change stability index and the change persistence index.

[0071] In the present application, a cycle analysis monitoring period is applied, the length of the analysis monitoring period can be determined by the user, the higher the user's requirement for the timeliness and accuracy of the monitoring result of the vehicle door system, the shorter the length of the analysis monitoring period, a length of the analysis monitoring period is provided, and the length of the analysis monitoring period is 10 days, at the end of each analysis monitoring period, the change stability coefficient of each change analysis system is determined according to the trend change stability index and the change persistence index, and the change characteristic analysis strategy of each change analysis system is determined according to the change stability coefficient;

[0072] The change stability coefficient of the single change analysis system is equal to the trend change stability index and the change persistence index. The preset change stability coefficient value can be determined by the user according to the actual working scene. For example, the user can set the value according to the operation monitoring record. A preset change stability coefficient value is provided. The operation monitoring record of the change analysis system for loss feature analysis is recorded as an analysis reference record. The average value of the change stability coefficient of the change analysis system in the analysis reference record that meets the timeliness and accuracy requirements of the user for the monitoring result of the vehicle door system is recorded as the preset change stability coefficient.

[0073] Specifically, for a single loss analysis system, the correlation change index of each change analysis system in the target monitoring train is determined according to the similar change coefficient and the position correlation coefficient.

[0074] If the correlation change index of any change analysis system is greater than the preset correlation change index, the change analysis system is recorded as the correlation change system of the loss analysis system.

[0075] The similar change coefficient is determined according to the number of coincident monitoring data and the stability coefficient difference value of each change analysis system. The position correlation coefficient is determined according to the air pressure interference index of each change analysis system.

[0076] For a single change analysis system, the change analysis system is recorded as a loss analysis system when loss feature analysis is performed. For any change analysis system in the target monitoring train except the loss analysis system, the correlation change index is the product of the similar change coefficient and the position correlation index of the change analysis system. The similar change coefficient is equal to ln(number of coincident monitoring data / stability coefficient difference value). The stability coefficient difference value is the absolute value of the difference between the change stability coefficients of the change analysis system and the target analysis system. For any target monitoring data, if the target monitoring data is used as change analysis data of the target analysis system and the change analysis system at the same time, the target monitoring data is recorded as coincident monitoring data. The position correlation index is the absolute value of the difference between the air pressure interference index of the change analysis system and the air pressure interference index of the loss analysis system. For a single change analysis system, the air pressure interference index is equal to system interference distance / distance between the head and tail of the target monitoring train. The system interference distance is the minimum value of the distance between the change analysis system and the head and tail of the target monitoring train.

[0077] For a single loss analysis system, the correlation change index of each change analysis system in the target monitoring train is determined according to the similar change coefficient and the position correlation coefficient. If the correlation change index of any change analysis system is greater than the preset correlation change index, the change analysis system with the correlation change index greater than the preset correlation change index is recorded as the correlation change system of the loss analysis system. The value of the preset correlation change index can be determined by the user according to the actual working scene. For example, the user can set it according to the operation monitoring record. The higher the user's requirement for the timeliness and accuracy of the monitoring result of the door system, the greater the value of the preset correlation change index. A method for determining the value of the preset correlation change index is provided. The average value of the correlation change index of the correlation change system in the operation monitoring record that meets the user's requirement for the timeliness and accuracy of the monitoring result of the door system is recorded as the preset correlation change index.

[0078] Specifically, if the correlation change proportion of the loss analysis system is greater than the preset correlation change proportion, change data processing is performed on the loss analysis system to determine the key monitoring data of the loss analysis system.

[0079] During change data processing, the reference change trend index of each trend analysis stage is determined based on the coincident monitoring data of the loss analysis system and its correlation change system.

[0080] Based on the reference change trend index of each trend analysis stage and the matching evaluation coefficient, the change trend matching degree of each monitoring data is determined, and the key monitoring data of the loss analysis system is determined according to the change trend matching degree.

[0081] The correlation change proportion of the loss analysis system is the number of correlation change systems of the loss analysis system / the number of change analysis systems of the target monitoring train. The value of the preset correlation change proportion can be determined by the user according to the actual working scene. For example, the user can set it according to the operation monitoring record. The higher the user's requirement for the timeliness and accuracy of the monitoring result of the door system, the greater the value of the preset correlation change proportion. A method for determining the value of the preset correlation change proportion is provided. The operation monitoring record that is processed for change data is recorded as the correlation reference record. The minimum value of the correlation change proportion of the loss analysis system in the correlation reference record that meets the user's requirement for the timeliness and accuracy of the monitoring result of the door system is recorded as the preset correlation change proportion.

[0082] For the change data processing of the single loss analysis system, the loss analysis system and its associated change system are recorded as a change analysis set, the values of each coincident monitoring data of each vehicle door system in the change analysis set during each completion of the vehicle door opening and closing task and the vehicle door closing task in the associated change analysis stage are obtained, the end time of the associated change analysis stage is the time for determining the change data processing of the loss analysis system, the value of the length of the associated change analysis stage is determined by the user according to the actual working scene, for example, the user can set it according to the operation monitoring record, the higher the requirement of the user for the timeliness and accuracy of the monitoring result of the vehicle door system, the greater the value of the length of the associated change analysis stage, a value of the length of the associated change analysis stage is provided, which is 200 days;

[0083] The associated change analysis stage of the associated change analysis stage is divided into several trend analysis stages with the same length, the higher the requirement of the user for the timeliness and accuracy of the monitoring result of the vehicle door system, the more the number of trend analysis stages obtained by division, the reference data change index of each coincident monitoring data of the loss analysis system and its associated change system in each trend analysis stage is detected, for a single coincident monitoring data, the reference trend change index of any trend analysis stage is the average value of the trend change index of each vehicle door system in the change analysis set, for a single vehicle door system, the trend change index = (the value of the coincident monitoring data obtained for the first time in the trend analysis stage-the value of the coincident monitoring data obtained for the last time in the trend analysis stage) / the value of the coincident monitoring data obtained for the first time in the trend analysis stage;

[0084] For a single monitoring data of the loss analysis system, the value of the monitoring data during each completion of the vehicle door opening and closing task and the vehicle door closing task in the associated change analysis stage is obtained, the evaluation change index of each trend analysis stage is detected, for a single trend analysis stage, the evaluation change index = (the value of the monitoring data obtained for the first time in the trend analysis stage-the value of the monitoring data obtained for the last time in the trend analysis stage) / the value of the monitoring data obtained for the first time in the trend analysis stage, the change trend matching degree is the sum of the products of the trend difference index of each trend analysis stage and the corresponding matching evaluation coefficient, for a single trend analysis stage, the trend difference index is the absolute value of the difference between the evaluation change index and the reference change trend index of the trend analysis stage, if the change trend matching degree of the monitoring data is greater than the preset change trend matching degree, the monitoring data is recorded as the key monitoring data of the loss analysis system, and the loss curve fitting of the loss analysis system is carried out according to the key monitoring data and the change analysis data, which is easily understood by those skilled in the art and is not described here;

[0085] The preset change trend matching degree value can be determined by the user according to the actual working scene. For example, the user can set it according to the operation monitoring record. The higher the user's requirement for the timeliness and accuracy of the monitoring result of the door system, the larger the preset change trend matching degree value. A method for providing the preset change trend matching degree value is provided. The minimum value of the change trend matching degree of the key monitoring data of the associated reference record that meets the user's requirement for the timeliness and accuracy of the monitoring result of the door system is recorded as the preset change trend matching degree.

[0086] Specifically, whether to adjust the matching evaluation coefficient corresponding to each trend analysis stage is determined according to the change difference coefficient;

[0087] If the change difference coefficient of a trend analysis stage is greater than the preset change difference coefficient, the matching evaluation coefficient is adjusted by decreasing according to the change difference coefficient;

[0088] The decreasing value of the matching evaluation coefficient is positively correlated with the change difference coefficient.

[0089] Among them, for any trend analysis stage of a single loss analysis system, the initial matching evaluation coefficient is determined according to the operation load parameter of the target monitoring train in the trend analysis stage. The initial matching evaluation coefficient is positively correlated with the operation load parameter. The operation load parameter = ln (the maximum value of the driving distance of the target monitoring train in the trend analysis stage and the driving speed of the target monitoring train in the trend analysis stage). The change difference coefficient is the standard deviation of the trend change index of each door system in the change analysis set in the trend analysis stage.

[0090] The preset change difference coefficient value can be determined by the user according to the actual working scene. For example, the user can set it according to the operation monitoring record. The higher the user's requirement for the timeliness and accuracy of the monitoring result of the door system, the larger the preset change difference coefficient value. A method for providing the preset change difference coefficient is provided. The operation monitoring record that adjusts the matching evaluation coefficient according to the change difference coefficient is recorded as the adjustment reference record. The average value of the change difference coefficient of each trend analysis stage of the adjustment reference record that meets the user's requirement for the timeliness and accuracy of the monitoring result of the door system is recorded as the preset change difference coefficient.

[0091] Specifically, if the change stability coefficient of a change analysis system is less than or equal to the preset change stability coefficient, data compression analysis is performed on the change analysis system, including:

[0092] The change analysis system is recorded as a compression analysis system, a compression analysis mode of each change analysis data of the compression analysis system is determined according to the relevant monitoring data proportion, compression processing is performed on each change analysis data, and key monitoring data is obtained.

[0093] Specifically, for any change analysis data of the compression analysis system, if the relevant monitoring data proportion is greater than the preset relevant monitoring data proportion, the monitoring stage of the change analysis data is divided, and the data compression threshold of each monitoring data segment is set according to the stage coincidence index;

[0094] The data compression threshold and the stage coincidence index are in a negative correlation relationship.

[0095] Specifically, whether the data compression threshold of each monitoring data segment is adjusted twice is determined according to the reference change index;

[0096] For a single monitoring data segment, if the reference change index is greater than the preset reference change index, the data compression threshold is adjusted by decreasing according to the reference change index;

[0097] The decreasing value of the data compression threshold and the reference change index are in a positive correlation relationship.

[0098] Wherein, for any change analysis data of a single compression analysis system, the relevant monitoring data proportion = the number of relevant monitoring data of the change analysis data / the number of monitoring data of the compression analysis system, the relevant monitoring data is other change analysis data whose monitoring stage overlaps with the monitoring stage of the change analysis data, for a single monitoring data, the start time of the monitoring stage is the time when the monitoring data is started to be acquired, and the end time of the monitoring stage is the time when the monitoring data is stopped to be acquired, the value of the preset relevant monitoring data proportion can be determined by the user according to the actual working scene, for example, the user can set it according to the running monitoring record, the higher the user's requirement for the timeliness and accuracy of the monitoring result of the door system, the smaller the value of the preset relevant monitoring data proportion, a method for determining the value of the preset relevant monitoring data proportion is provided, the running monitoring record based on which the data compression threshold is determined is recorded as a compression reference record, and the maximum value of the relevant monitoring data proportion in the compression reference record meeting the user's requirement for the timeliness and accuracy of the monitoring result of the door system is recorded as the preset relevant monitoring data proportion;

[0099] For the single-item change analysis data, the monitoring stage of the change analysis data is divided into several monitoring data segments with the same time length, for a single monitoring data segment, the stage coincidence index is the number of relevant monitoring data in which the monitoring stage exists, the reference change index is the average value of the change indexes of each relevant monitoring data in which the monitoring stage exists in the monitoring data segment, and the change analysis data is compressed according to the data compression threshold of the monitoring data segment. The change analysis data after compression is recorded as key monitoring data. How to segment and compress the change analysis data according to the data compression threshold of each monitoring data segment is easy for those skilled in the art to understand and will not be described here.

[0100] The value of the preset reference change index can be determined by the user according to the actual working scene. For example, the user can set it according to the running monitoring record. The higher the user's requirement for the timeliness and accuracy of the monitoring result of the door system, the smaller the value of the preset reference change index. A method for determining the value of the preset reference change index is provided. The running monitoring record in which the reference change index is adjusted according to the data compression threshold is recorded as a threshold adjustment record. The minimum value of the reference change index in the threshold adjustment record that meets the user's requirement for the timeliness and accuracy of the monitoring result of the door system is recorded as the preset reference change index.

[0101] Specifically, for any change analysis data of the compression analysis system, if the relevant monitoring data proportion is less than or equal to the preset relevant monitoring data proportion, the data compression threshold is determined based on the relevant monitoring data proportion, and the change analysis data is compressed according to the data compression threshold.

[0102] The data compression threshold and the relevant monitoring data proportion are in a negative correlation relationship.

[0103] The determined data compression threshold is recorded as a global compression threshold, and the change analysis data is compressed according to the global compression threshold. The change analysis data after compression is recorded as key monitoring data. How to compress data according to the global compression threshold is easy for those skilled in the art to understand and will not be described here.

[0104] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application. The technical solutions after the changes or replacements will fall within the protection scope of the present application.

[0105] The above merely illustrates the preferred embodiments of the present application, and is not used to limit the present application; for those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A data analysis-based train running state safety monitoring method, characterized in that, Comprise: Under the condition of abnormal change analysis, the data analysis strategy of each change analysis system is determined according to the trend change stability index and the change duration index, so as to analyze the loss characteristics or perform data compression analysis on the change analysis system; When performing loss characteristic analysis, the correlation change proportion of each change analysis system is determined based on the similar change coefficient and the position correlation coefficient, and whether to perform change data processing on the loss analysis system is determined according to the correlation change proportion, so as to determine the key monitoring data; When performing data compression analysis, the compression analysis mode of each change analysis data of the compression analysis system is determined according to the relevant monitoring data proportion, so as to obtain the key monitoring data, and the compression analysis mode is to set the data compression threshold for each monitoring data segment according to the stage coincidence index, or to set the data compression threshold based on the relevant monitoring data proportion; Under the condition of analysis completion, the key monitoring data is sent to the user, and the analysis completion condition is that the change analysis system completes the loss characteristic analysis or the data compression analysis; Under the condition of abnormal change analysis, the trend change stability index and the change duration index of each change analysis system are detected; For a single change analysis system, The trend change stability index is determined according to the change index of each change analysis data of the change analysis system in the change evaluation stage; The change duration index is determined according to the change direction of the change index obtained each time in the change evaluation stage; The abnormal change analysis condition is that the target monitoring train has a door system that needs to be analyzed, and the door system that needs to be analyzed is recorded as a change analysis system; If the change stability coefficient of a change analysis system is greater than a preset change stability coefficient, loss characteristic analysis is performed on the change analysis system, including: The change analysis system is recorded as a loss analysis system, and the correlation change proportion of the loss analysis system is determined based on the similar change coefficient and the position correlation coefficient of each change analysis system in the correlation evaluation range; Whether to perform change data processing on the loss analysis system is determined according to the correlation change proportion; The change stability coefficient is determined according to the trend change stability index and the change duration index; If the change stability coefficient of a change analysis system is less than or equal to a preset change stability coefficient, data compression analysis is performed on the change analysis system, including: The change analysis system is recorded as a compression analysis system, and the compression analysis mode of each change analysis data of the compression analysis system is determined according to the relevant monitoring data proportion, so as to perform compression processing on each change analysis data and obtain the key monitoring data.

2. The data analysis based train running state safety monitoring method according to claim 1, characterized in that, For a single loss analysis system, the correlation change index of each change analysis system in the correlation evaluation range is determined according to the similar change coefficient and the position correlation coefficient; If the correlation change index of any change analysis system in the correlation evaluation range is greater than a preset correlation change index, the change analysis system is recorded as the correlation change system of the loss analysis system; The similar change coefficient is determined according to the number of coincident monitoring data and the stability coefficient difference value of each change analysis system, and the position correlation coefficient is determined according to the air pressure interference index of each change analysis system; For a single change analysis system, the air pressure interference index = system interference distance / distance between the head and tail of the target monitoring train, and the system interference distance is the minimum distance between the change analysis system and the head and tail of the target monitoring train.

3. The data analysis based train running state safety monitoring method according to claim 2, characterized in that, If the associated change proportion of the loss analysis system is greater than the preset associated change proportion, change data processing is performed on the loss analysis system to determine the key monitoring data of the loss analysis system. During change data processing, the reference change trend index of each trend analysis stage is determined based on the overlapping monitoring data of the loss analysis system and its associated change system. Based on the reference change trend index of each trend analysis stage and the matching evaluation coefficient, the change trend matching degree of each monitoring data is determined, and the key monitoring data of the loss analysis system is determined according to the change trend matching degree.

4. The data analysis based train running state safety monitoring method according to claim 3, characterized in that, According to the change difference coefficient, it is determined whether to adjust the matching evaluation coefficient corresponding to each trend analysis stage. If the change difference coefficient of a trend analysis stage is greater than the preset change difference coefficient, the matching evaluation coefficient is adjusted according to the change difference coefficient. The decrease value of the matching evaluation coefficient and the change difference coefficient are in a positive correlation.

5. The data analysis based train running state safety monitoring method according to claim 1, characterized in that, For any change analysis data of the compression analysis system, if the relevant monitoring data proportion is greater than the preset relevant monitoring data proportion, the monitoring stage of the change analysis data is divided, and the data compression threshold of each monitoring data segment is set according to the stage overlap index. The data compression threshold and the stage overlap index are in a negative correlation.

6. The data analysis based train running state safety monitoring method according to claim 5, characterized in that, According to the reference change index, it is determined whether to perform secondary adjustment on the data compression threshold of each monitoring data segment. For a single monitoring data segment, if the reference change index is greater than the preset reference change index, the data compression threshold is adjusted according to the reference change index. The decrease value of the data compression threshold and the reference change index are in a positive correlation.

7. The data analysis based train running state safety monitoring method according to claim 6, characterized in that, For any change analysis data of the compression analysis system, if the relevant monitoring data proportion is less than or equal to the preset relevant monitoring data proportion, the data compression threshold is determined based on the relevant monitoring data proportion, and the change analysis data is compressed according to the data compression threshold. The data compression threshold and the relevant monitoring data proportion are in a negative correlation.

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