CN114971268A

CN114971268A - Train performance evaluation method and device, storage medium and electronic equipment

Info

Publication number: CN114971268A
Application number: CN202210562014.7A
Authority: CN
Inventors: 刘勇; 李珊; 江平; 戴计生; 唐黎哲; 詹彦豪; 张红光; 刘子牛; 张士强; 卢青松
Original assignee: Zhuzhou CRRC Times Electric Co Ltd
Current assignee: Zhuzhou CRRC Times Electric Co Ltd
Priority date: 2022-05-23
Filing date: 2022-05-23
Publication date: 2022-08-30

Abstract

The invention provides a train performance evaluation method and device, a storage medium and electronic equipment, wherein the method comprises the following steps: determining real-time operation information corresponding to each preset evaluation object according to the current operation information of the target train, and determining historical operation information corresponding to each preset evaluation object according to the historical intersection operation information of the target train; determining the simultaneous train operation information corresponding to each preset evaluation object according to the current operation information of a plurality of running trains in the running state; determining the comprehensive performance index value of each preset evaluation object according to the real-time operation information, the historical operation information and the train operation information of the same time section corresponding to each preset evaluation object; and determining the performance state corresponding to each preset evaluation object according to each comprehensive performance index value, so as to realize performance evaluation on the target train. By applying the method, the unified and standard automatic train performance evaluation can be realized, and the accuracy of the performance evaluation can be improved.

Description

Train performance evaluation method and device, storage medium and electronic equipment

Technical Field

The invention relates to the technical field of rail transit, in particular to a train performance evaluation method and device, a storage medium and electronic equipment.

Background

With the development of rail transit technology, railway trains have become one of the important transportation means in people's daily life. In order to guarantee the safety and stability of train operation, the train operation performance needs to be evaluated in railway transportation work, so that a quick response mechanism with early fault discovery, early isolation and early processing is formed.

At present, the performance evaluation of trains is usually qualitative evaluation, that is, a worker analyzes the operation data of the train and artificially judges the performance state of the train according to experience, so as to realize the performance evaluation of the train.

In an actual railway transportation scene, experience differences exist among different workers, the train performance cannot be evaluated according to a unified standard based on the existing performance evaluation mode, the accuracy of performance evaluation is poor, and the safety and stability of train operation are not guaranteed.

Disclosure of Invention

In view of this, the embodiment of the invention provides a train performance evaluation method to solve the problem that the train performance cannot be evaluated by a unified standard and the evaluation accuracy is poor.

The embodiment of the invention also provides a train performance evaluation device, which is used for ensuring the actual realization and application of the method.

In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:

a train performance evaluation method, comprising:

when current operation information of a target train in a running state is received, determining real-time operation information corresponding to each preset evaluation object according to the current operation information of the target train, wherein the current operation information of the target train comprises signal data acquired by each vehicle-mounted sensor of the target train in the current operation state;

acquiring historical road crossing operation information of the target train, and determining the historical operation information corresponding to each preset evaluation object according to the historical road crossing operation information;

acquiring current operation information of a plurality of operation trains, wherein the operation trains are trains outside the target train and in a current running state, and the current operation information of each operation train comprises signal data acquired by each vehicle-mounted sensor of the operation train in the current running state;

determining the train operation information of the same section corresponding to each preset evaluation object according to the current operation information of the plurality of operating trains;

for each preset evaluation object, determining a comprehensive performance index value corresponding to the preset evaluation object according to the real-time operation information, the historical operation information and the train operation information of the same time segment corresponding to the preset evaluation object;

and determining the performance state corresponding to each preset evaluation object according to the comprehensive performance index value corresponding to each preset evaluation object, so as to realize performance evaluation on the target train.

Optionally, the determining, according to the real-time operation information, the historical operation information, and the train operation information of the simultaneous segment corresponding to the preset evaluation object, a comprehensive performance index value corresponding to the preset evaluation object includes:

determining a performance index set corresponding to the preset evaluation object, wherein the performance index set comprises at least one preset performance index;

for each preset performance index in the performance index set, determining a first deviation degree value and a second deviation degree value corresponding to the preset performance index according to real-time operation information, historical operation information and train operation information of a simultaneous section corresponding to the preset evaluation object, and determining a performance index value corresponding to the preset performance index according to the first deviation degree value and the second deviation degree value;

and determining a comprehensive performance index value corresponding to the preset evaluation object according to the performance index value corresponding to each preset performance index in the performance index set.

Optionally, the determining the first deviation degree value corresponding to the preset performance index includes:

determining multiple groups of historical operating data corresponding to the preset performance index according to operating data information of multiple historical intersections contained in the historical operating information corresponding to the preset evaluation object, wherein the multiple groups of historical operating data correspond to the multiple historical intersections one by one;

according to a plurality of preset statistical characteristics, performing statistical calculation on each group of historical operating data to obtain a statistic set corresponding to each group of historical operating data, wherein the statistic set corresponding to each group of historical operating data comprises a historical data statistical value corresponding to each statistical characteristic;

determining a first historical deviation value according to a statistic set corresponding to each group of historical operating data;

determining real-time operation data corresponding to the preset performance index according to the real-time operation information corresponding to the preset evaluation object;

according to the statistical characteristics, performing statistical calculation on the real-time operation data to obtain a statistic set corresponding to the real-time operation data, wherein the statistic set corresponding to the real-time operation data comprises a real-time data statistic value corresponding to each statistical characteristic;

determining a second historical deviation value according to the statistic set corresponding to each group of historical operating data and the statistic set corresponding to the real-time operating data;

and determining a first deviation degree value corresponding to the preset performance index according to the first historical deviation value and the second historical deviation value.

Optionally, the determining a first historical deviation value according to the statistic set corresponding to each group of historical operating data includes:

determining a historical sample standard deviation and a historical sample average value corresponding to each statistical feature according to a statistical quantity set corresponding to each group of historical operating data;

determining a historical offset characteristic value corresponding to each statistical characteristic according to a historical sample standard deviation and a historical sample average value corresponding to each statistical characteristic;

and calculating a first arithmetic mean value, and taking the first arithmetic mean value as the first historical deviation value, wherein the first arithmetic mean value is an arithmetic mean value corresponding to each historical deviation characteristic value.

Optionally, the determining a second historical deviation value according to the statistical quantity set corresponding to each group of historical operating data and the statistical quantity set corresponding to the real-time operating data includes:

determining historical operating data to be replaced and a plurality of target historical operating data in each group of historical operating data, wherein the target historical operating data is historical operating data except the historical operating data to be replaced in each group of historical operating data;

determining a real-time sample standard deviation and a real-time sample average value corresponding to each statistical feature according to a statistical quantity set corresponding to each group of target historical operating data and a statistical quantity set corresponding to the real-time operating data;

determining a real-time offset characteristic value corresponding to each statistical characteristic according to a real-time sample standard deviation and a real-time sample average value corresponding to each statistical characteristic;

and calculating a second arithmetic mean value, and taking the second arithmetic mean value as the second historical deviation value, wherein the second arithmetic mean value is an arithmetic mean value corresponding to each real-time deviation characteristic value.

Optionally, the determining, according to the first historical deviation value and the second historical deviation value, a first deviation degree value corresponding to the preset performance index includes:

and performing difference operation on the second historical deviation value and the first historical deviation value, and taking an operation result as a first deviation degree value corresponding to the preset performance index.

Optionally, the determining a second deviation degree value corresponding to the preset performance index includes:

determining multiple groups of train operation data corresponding to the preset performance index according to operation data information of each operating train contained in the simultaneous train operation information corresponding to the preset evaluation object, wherein the multiple groups of train operation data correspond to the operating trains one by one;

according to the plurality of statistical characteristics, performing statistical calculation on each group of the train operation data to obtain a statistic set corresponding to each group of the train operation data, wherein the statistic set corresponding to each group of the train operation data comprises a train data statistical value corresponding to each statistical characteristic;

determining a first real-time deviation value according to a statistic set corresponding to each group of train operation data;

determining a second real-time deviation value according to the statistic set corresponding to each group of train operation data and the statistic set corresponding to the real-time operation data;

and determining a second deviation degree value corresponding to the preset performance index according to the first real-time deviation value and the second real-time deviation value.

Optionally, the determining, according to the first deviation degree value and the second deviation degree value, a performance index value corresponding to the preset performance index includes:

performing product operation on the first deviation degree value and a first preset weight to obtain a first product;

performing product operation on the second deviation degree value and a second preset weight to obtain a second product;

and performing sum operation on the first product and the second product, and taking an operation result as a performance index value corresponding to the preset performance index.

Optionally, in the method, the determining, according to the performance index value corresponding to each preset performance index in the performance index set, a comprehensive performance index value corresponding to the preset evaluation object includes:

judging whether the performance index set only contains one preset performance index;

if the performance index set does not only contain one preset performance index, determining the index weight corresponding to each preset performance index;

and according to the index weight corresponding to each preset performance index, performing weighting and operation on the performance index value corresponding to each preset performance index, and taking the operation result as the comprehensive performance index value corresponding to the preset evaluation object.

Optionally, the determining the index weight corresponding to each preset performance index includes:

determining the information entropy corresponding to each preset performance index according to the performance index value corresponding to each preset performance index;

and calculating the index weight corresponding to each preset performance index according to the information entropy corresponding to each preset performance index.

The method described above, optionally, further includes:

and if the performance index set only contains one preset performance index, taking the performance index value corresponding to the preset performance index in the performance index set as the comprehensive performance index value corresponding to the preset evaluation object.

Optionally, the determining, according to the comprehensive performance index value corresponding to each preset evaluation object, the performance state corresponding to each preset evaluation object includes:

for each preset evaluation object, determining a plurality of index value intervals corresponding to the preset evaluation object, wherein the index value intervals correspond to a plurality of preset performance states corresponding to the preset evaluation object one by one;

and for the comprehensive performance index value corresponding to each preset evaluation object, respectively matching the comprehensive performance index value with each index value interval corresponding to the preset evaluation object, determining the index value interval matched with the comprehensive performance index value as a target index value interval, and determining the preset performance state corresponding to the target index value interval as the performance state corresponding to the preset evaluation object.

A train performance evaluation device comprising:

the device comprises a first determining unit, a second determining unit and a judging unit, wherein the first determining unit is used for determining real-time operation information corresponding to each preset evaluation object according to the current operation information of a target train when the current operation information of the target train in a running state is received, and the current operation information of the target train comprises signal data acquired by each vehicle-mounted sensor of the target train in the current operation state;

the first acquisition unit is used for acquiring historical road crossing operation information of the target train and determining the historical operation information corresponding to each preset evaluation object according to the historical road crossing operation information;

the second acquisition unit is used for acquiring current operation information of a plurality of operation trains, wherein the operation trains are trains outside the target train and in a running state at present, and the current operation information of each operation train comprises signal data acquired by each vehicle-mounted sensor of the operation train in the current operation state;

the second determining unit is used for determining the train operation information of the same time section corresponding to each preset evaluation object according to the current operation information of the plurality of operating trains;

the third determining unit is used for determining a comprehensive performance index value corresponding to each preset evaluation object according to the real-time running information, the historical running information and the train running information of the same time section corresponding to the preset evaluation object;

and the evaluation unit is used for determining the performance state corresponding to each preset evaluation object according to the comprehensive performance index value corresponding to each preset evaluation object, so as to realize performance evaluation on the target train.

A storage medium comprising stored instructions, wherein the instructions, when executed, control a device on which the storage medium is located to perform the train performance evaluation method as described above.

An electronic device comprising a memory, and one or more instructions, wherein the one or more instructions are stored in the memory and configured to be executed by one or more processors to perform the train performance assessment method as described above.

The train performance evaluation method provided by the embodiment of the invention comprises the following steps: when current operation information of a target train in a running state is received, determining real-time operation information corresponding to each preset evaluation object according to the current operation information of the target train, and determining historical operation information corresponding to each preset evaluation object according to historical road crossing operation information of the target train; determining the simultaneous train operation information corresponding to each preset evaluation object according to the current operation information of a plurality of operating trains; for each preset evaluation object, determining a comprehensive performance index value corresponding to the preset evaluation object according to the real-time operation information, the historical operation information and the train operation information of the same time segment corresponding to the preset evaluation object; and determining the performance state corresponding to each preset evaluation object according to the comprehensive performance index value corresponding to each preset evaluation object, so as to realize performance evaluation on the target train. By applying the method provided by the embodiment of the invention, the performance state of each preset evaluation object corresponding to the target train can be evaluated by combining the current operation information of the target train, the historical road crossing operation information and the current operation information of other trains which operate simultaneously with the target train, the train performance can be automatically evaluated according to a unified standard, the accuracy of performance evaluation can be improved, and the safe and stable operation of the train can be ensured.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.

Fig. 1 is a flowchart of a method for evaluating train performance according to an embodiment of the present invention;

FIG. 2 is a diagram illustrating an exemplary train performance evaluation system according to an embodiment of the present invention;

FIG. 3 is a diagram illustrating a process for evaluating train performance according to an embodiment of the present invention;

FIG. 4 is a diagram illustrating a performance index calculation process according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of a train performance evaluation device according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In this application, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

As can be known from the background art, in the development process of railway transportation, the requirement on the safety and stability of train operation is higher and higher, and the importance of train performance evaluation work is also higher and higher. However, how to evaluate the train performance is still qualitative evaluation at present, and all parties perform performance evaluation work by experience without uniform specification, so that the accuracy of performance evaluation is poor, and the safety of train operation is not guaranteed.

Therefore, the embodiment of the invention provides a train performance evaluation method, which is used for analyzing the performance indexes of various evaluation objects by combining big data, realizing unified and standard automatic performance evaluation, and being beneficial to improving the evaluation accuracy and ensuring the train operation safety.

The embodiment of the invention provides a train performance evaluation method, which can be applied to a train performance evaluation system, wherein an execution subject of the method can be a server of the system, and a flow chart of the method is shown in figure 1 and comprises the following steps:

s101: when current operation information of a target train in a running state is received, determining real-time operation information corresponding to each preset evaluation object according to the current operation information of the target train, wherein the current operation information of the target train comprises signal data acquired by each vehicle-mounted sensor of the target train in the current operation state;

in the method provided by the embodiment of the invention, in the running process of the train, each vehicle-mounted sensor on the train can acquire relevant signal data in real time, for example, a motor temperature sensor can detect the temperature value of a motor in real time, a main air reservoir pressure sensor can detect the pressure value of a main air reservoir in real time, and the like. By setting, according to a preset time interval, signal data acquired by each vehicle-mounted sensor at the current time period are packaged to serve as current operation information, and the current operation information is sent to a server of a train performance evaluation system based on a wireless communication technology.

In the method provided by the embodiment of the invention, a plurality of evaluation objects can be preset, and the preset evaluation objects can be some key components or systems on the train, such as a braking system, a pantograph, a traction motor and the like. Meanwhile, a signal data type associated with each preset evaluation object is set, for example, the signal data type associated with the pantograph may be a pantograph lifting state signal, a pantograph main off state signal, or the like.

In the method provided by the embodiment of the invention, when the server receives the current operation information sent by the running target train, the signal data corresponding to each preset evaluation object can be acquired from the current operation information of the current train based on the signal data type corresponding to each preset evaluation object, and the signal data corresponding to each preset evaluation object is used as the real-time operation information corresponding to the preset evaluation object.

S102: acquiring historical road crossing operation information of the target train, and determining the historical operation information corresponding to each preset evaluation object according to the historical road crossing operation information;

in the method provided by the embodiment of the invention, the historical road-crossing operation information of the target train can be obtained in the database, wherein the historical road-crossing operation information comprises signal data acquired by each vehicle-mounted sensor in the running process of the current train on a plurality of historical road-crossings. The crossing refers to a train crossing, i.e. a fixed turnaround section where the train undertakes a transportation task, and the historical crossing can be understood as a travel section where the train undertakes a previous transportation task.

The signal data corresponding to each preset evaluation object can be acquired from the historical intersection operation information of the target train according to the signal data type corresponding to each preset evaluation object, and the acquired signal data are used as the historical operation information corresponding to each preset evaluation object.

S103: acquiring current operation information of a plurality of operating trains, wherein the operating trains are trains outside the target train and in a running state at present, and the current operation information of each operating train comprises signal data acquired by each vehicle-mounted sensor of the operating train in the current operation state;

in the method provided by the embodiment of the invention, in the running process of each train in the running state except the target train in the rail transit system, each vehicle-mounted sensor can also acquire signal data in real time, each train can regularly send the current running information of the train to the server, and the server can acquire the current running information of a plurality of running trains from each current running information received at the current time.

S104: determining the train operation information of the same section corresponding to each preset evaluation object according to the current operation information of the plurality of operating trains;

in the method provided by the embodiment of the invention, each signal data corresponding to each preset evaluation object can be acquired from the current operation information of each running train according to the signal data type corresponding to each preset evaluation object, and each signal data corresponding to each preset evaluation object, which is acquired from the current operation information of each running train, is taken as the simultaneous train operation information corresponding to the preset evaluation object.

S105: for each preset evaluation object, determining a comprehensive performance index value corresponding to the preset evaluation object according to the real-time operation information, the historical operation information and the train operation information of the same time segment corresponding to the preset evaluation object;

in the method provided by the embodiment of the present invention, the comprehensive performance index value corresponding to each preset evaluation object may be calculated according to the real-time operation information, the historical operation information and the train operation information of the same time segment corresponding to each preset evaluation object, and it may be understood that, by combining the current signal data of the target train associated with the preset evaluation object, the historical signal data of the target train and the current signal data of other running trains, the performance of the preset evaluation object is evaluated according to the preset performance index, and the corresponding comprehensive performance index value is determined.

S106: and determining the performance state corresponding to each preset evaluation object according to the comprehensive performance index value corresponding to each preset evaluation object, so as to realize performance evaluation on the target train.

In the method provided by the embodiment of the invention, for each preset evaluation object, the corresponding performance state is determined based on the corresponding comprehensive performance index value. And representing the performance evaluation result of the target train according to the performance state corresponding to each preset evaluation object. The performance state corresponding to the evaluation object is preset, and specifically can be a state such as health, early warning or alarm.

Based on the method provided by the embodiment of the invention, the real-time running information, the historical running information and the running information of the trains at the same time corresponding to each preset evaluation object are respectively determined according to the current running information, the historical intersection running information and the current running information of each running train of the target train. For each preset evaluation object, determining a comprehensive performance index value corresponding to the preset evaluation object according to the real-time operation information, the historical operation information and the train operation information of the same time segment corresponding to the preset evaluation object; and determining the performance state corresponding to each preset evaluation object according to the comprehensive performance index value corresponding to each preset evaluation object so as to evaluate the performance of the target train. By applying the method provided by the embodiment of the invention, the running data corresponding to the preset evaluation object can be combined under various driving scenes, the comprehensive performance index value corresponding to the preset evaluation object is calculated, the corresponding performance state is determined, and the performance evaluation result of the train is represented by the performance state of each preset evaluation object. The train performance can be automatically evaluated according to the unified standard, quantitative evaluation is realized, the accuracy of performance evaluation is favorably improved, and the safe and stable operation of the train is guaranteed. Secondly, the performance state is analyzed by applying big data, so that the accuracy of performance state evaluation can be further improved.

Further, on the basis of the method shown in fig. 1, in the method provided in the embodiment of the present invention, the step S105 of determining the comprehensive performance index value corresponding to the preset evaluation object according to the real-time operation information, the historical operation information, and the train operation information of the simultaneous segment corresponding to the preset evaluation object includes:

in the method provided by the embodiment of the present invention, for a current preset evaluation object, a corresponding performance index set may be determined based on preconfigured information, where the performance index set includes preset performance indexes used for evaluating the preset evaluation object, and there may be only one or multiple preset performance indexes in the performance index set, and the number of the preset performance indexes is determined by requirement setting in an actual application process, and the method implementation function provided by the embodiment of the present invention is not affected.

according to the method provided by the embodiment of the invention, a first deviation degree value corresponding to each preset performance index and a second deviation degree value corresponding to each preset performance index are determined according to real-time operation information, historical operation information and train operation information of a simultaneous section corresponding to a current preset evaluation object, and a performance index value corresponding to each preset performance index is calculated according to the first deviation degree value and the second deviation degree value corresponding to each preset performance index. A first deviation degree value corresponding to the preset performance index may be determined based on the real-time operation information and the historical operation information corresponding to the preset evaluation object, where the first deviation degree value represents a difference degree between the real-time operation data and the historical operation data of the target train associated with the preset performance index. The second deviation degree value corresponding to the preset performance index may be determined based on the real-time operation information corresponding to the preset evaluation object and the operation information of the train in the same time segment, and represents a difference degree between the real-time operation data of the target train associated with the preset performance index and the real-time operation data of other operating trains.

In the method provided by the embodiment of the invention, the comprehensive performance index value corresponding to the preset evaluation object can be calculated by combining the performance index values corresponding to the preset performance indexes based on the preset integration strategy.

Further, on the basis of the method provided in the foregoing embodiment, in the method provided in an embodiment of the present invention, the determining the first deviation degree value corresponding to the preset performance index includes:

in the method provided by the embodiment of the present invention, the historical operation information corresponding to the preset evaluation object includes operation data information of a plurality of historical traffic routes, the operation data corresponding to the preset performance index (i.e., the signal data associated with the preset performance index in the operation data information) can be obtained from the operation data information of each historical traffic route according to the data type corresponding to the preset performance index, a plurality of sets of historical operation data corresponding to the preset performance index are obtained, and each operation data obtained from the operation data information of one historical traffic route forms one set of historical operation data, so that one set of historical operation data corresponds to one historical traffic route. Each set of historical operating data includes a plurality of operating data values.

Performing statistical calculation on each group of historical operating data according to a plurality of preset statistical characteristics to obtain a statistic set corresponding to each group of historical operating data, wherein the statistic set corresponding to each group of historical operating data comprises a historical data statistical value corresponding to each statistical characteristic;

in the method provided by the embodiment of the present invention, a plurality of statistical characteristics, such as a maximum value, a minimum value, a mean value, and the like, for describing the operating data characteristics may be preset. And performing statistical calculation on each group of historical operating data according to each statistical characteristic to obtain a statistical set corresponding to each group of historical operating data, namely calculating the statistical values of each type of statistical characteristics such as the maximum value, the minimum value, the mean value and the like of each operating data for each group of historical operating data, wherein the calculated statistical values are called historical data statistical values, and the statistical values of each group of historical data calculated according to each statistical characteristic form a statistical quantity set.

in the method provided by the embodiment of the invention, a first historical deviation value can be calculated based on the statistic set corresponding to each group of historical operating data according to a preset deviation estimation strategy, and the first historical deviation value represents the deviation degree between the statistic values of each historical data in the statistic set corresponding to each group of historical operating data.

in the method provided by the embodiment of the present invention, the real-time operation data corresponding to the preset performance index may be acquired according to the data type corresponding to the preset performance index from each real-time operation data included in the real-time operation information corresponding to the preset evaluation object. The real-time operational data includes a plurality of operational data values.

According to the statistical characteristics, performing statistical calculation on the real-time operation data to obtain a statistic set corresponding to the real-time operation data, wherein the statistic set corresponding to the real-time operation data comprises a real-time data statistical value corresponding to each statistical characteristic;

in the method provided by the embodiment of the present invention, the real-time operation data may be statistically calculated based on each statistical characteristic, so as to obtain a statistical set corresponding to the real-time operation data, and the calculation principle of the statistical set is the same as that of the statistical calculation performed on each group of historical operation data in the above process, which is referred to in the above description and is not described herein again.

in the method provided by the embodiment of the invention, the second historical deviation value can be calculated based on the statistical quantity set corresponding to each group of historical operating data and the statistical quantity set corresponding to the real-time operating data according to a preset deviation estimation strategy. The second historical deviation value represents the deviation degree between each historical data statistic and each real-time data statistic.

In the method provided by the embodiment of the present invention, the first deviation degree value corresponding to the current preset performance index may be obtained through calculation by combining the first historical deviation degree and the second historical deviation degree, that is, the first deviation degree value corresponding to the preset performance index is determined according to the deviation degree between the statistical characteristics of each historical operating data and the statistical characteristics of the real-time operating data.

Further, on the basis of the method provided in the foregoing embodiment, in the method provided in an embodiment of the present invention, the determining a first historical deviation value according to a statistic set corresponding to each group of the historical operating data includes:

in the method provided by the embodiment of the invention, for each statistical characteristic, a historical data statistical value corresponding to the statistical characteristic is obtained from a statistical quantity set corresponding to each group of historical operating data, a sample standard deviation and a sample average value are calculated based on each historical data statistical value corresponding to the statistical characteristic, a calculation result of the sample standard deviation is used as a historical sample standard deviation corresponding to the statistical characteristic, and a calculation result of the sample standard deviation is used as a historical sample average value corresponding to the statistical characteristic.

in the method provided by the embodiment of the invention, for each statistical characteristic, the corresponding historical offset characteristic value can be calculated and obtained based on the corresponding historical sample standard deviation and the corresponding historical sample average value, specifically, the historical sample standard deviation and the historical sample average value can be divided, and the operation result is used as the historical offset characteristic value.

In the method provided by the embodiment of the invention, the arithmetic mean is calculated for the historical deviation characteristic values corresponding to the statistical characteristics to obtain a first arithmetic mean value, and the first arithmetic mean value is used as a first historical deviation value.

On the basis of the method provided in the foregoing embodiment, in the method provided in the embodiment of the present invention, the determining a second historical deviation value according to the statistical quantity set corresponding to each group of historical operating data and the statistical quantity set corresponding to the real-time operating data includes:

in the method provided by the embodiment of the invention, one group of historical operating data is selected as the historical operating data to be replaced in each group of historical operating data, specifically, the historical operating data to be replaced can be randomly selected, or a selection rule can be preset, and the historical operating data to be replaced is selected according to the rule. And taking each group of historical operating data except the historical operating data to be replaced in each group of historical operating data as target historical operating data.

in the method provided by the embodiment of the invention, for each statistical characteristic, each historical data statistical value corresponding to the statistical characteristic is obtained from a statistical set corresponding to each group of target historical operating data, a real-time data statistical value corresponding to the statistical characteristic is obtained from a statistical quantity set corresponding to real-time operating data, the calculation of the sample standard deviation and the sample average value is carried out based on each obtained historical data statistical value and real-time data statistical value, the calculation result of the sample standard deviation is used as the real-time sample standard deviation corresponding to the statistical characteristic, and the calculation result of the sample average value is used as the real-time sample average value corresponding to the statistical characteristic.

in the method provided by the embodiment of the present invention, the real-time sample standard deviation corresponding to each statistical characteristic and the corresponding real-time sample average value thereof may be subjected to division operation, and the operation result is used as the real-time offset characteristic value corresponding to the statistical characteristic.

In the method provided by the embodiment of the invention, the arithmetic mean is calculated for the real-time offset characteristic values corresponding to the statistical characteristics to obtain a second arithmetic mean value, and the second arithmetic mean value is used as a second historical deviation value.

On the basis of the method provided in the foregoing embodiment, in the method provided in an embodiment of the present invention, the determining a first deviation degree value corresponding to the preset performance index according to the first historical deviation value and the second historical deviation value includes:

In the method provided by the embodiment of the invention, the difference value between the second historical deviation value and the first historical deviation value is used as the first deviation degree value.

On the basis of the method provided in the foregoing embodiment, in the method provided in an embodiment of the present invention, the determining the second deviation degree value corresponding to the preset performance index includes:

determining multiple groups of train operation data corresponding to the preset performance index according to operation data information of each operation train contained in the simultaneous train operation information corresponding to the preset evaluation object, wherein the multiple groups of train operation data correspond to the operation trains one by one;

in the method provided by the embodiment of the invention, the operation data information of a plurality of operating trains is contained in the operation information of the train at the same time corresponding to the preset evaluation object, the operation data corresponding to the preset performance index can be obtained from the operation data information of each operating train according to the data type corresponding to the current preset performance index, a plurality of groups of train operation data are obtained, and each operation data obtained from the operation data information of one operating train forms a group of train operation data, namely, one group of train operation data corresponds to one operating train. Each set of train operation data includes a plurality of operation data values.

According to the statistical characteristics, performing statistical calculation on each group of the train operation data to obtain a statistic set corresponding to each group of the train operation data, wherein the statistic set corresponding to each group of the train operation data comprises a train data statistical value corresponding to each statistical characteristic;

in the method provided by the embodiment of the invention, each group of train operation data is subjected to statistical calculation according to each statistical characteristic respectively to obtain a statistical quantity set corresponding to the group of train operation data, wherein the statistical quantity set comprises a train data statistical value corresponding to each statistical characteristic, and the train data statistical value is a statistical value obtained by performing statistical calculation according to the corresponding statistical characteristic.

in the method provided by the embodiment of the invention, a first real-time deviation value can be calculated based on the statistic set corresponding to each group of train operation data according to a preset deviation estimation strategy, and the first real-time deviation value represents the deviation degree between the train data statistic values in the statistic set corresponding to each group of train operation data. The calculation principle of the first real-time deviation value is the same as that of the first historical deviation value in the foregoing embodiment, and specific reference may be made to the description of the determination process of the first historical deviation value in the foregoing embodiment, which is not described herein again.

in the method provided by the embodiment of the invention, according to a preset deviation estimation strategy, a second real-time deviation value is calculated based on the statistical quantity set corresponding to each group of train operation data and the statistical quantity set corresponding to the real-time operation data, and the second real-time deviation value represents the deviation degree between each train data statistical value and each real-time data statistical value.

In the method provided by the embodiment of the present invention, the calculation principle of the second real-time deviation value is similar to the calculation principle of the second historical deviation value in the foregoing embodiment, and reference may be made to the description of the determination process of the second historical deviation value in the foregoing embodiment, which is not described herein again. It should be noted that, in the method provided by the embodiment of the present invention, the determination of the set of statistics involved in the second real-time deviation value may be different from the determination of the set of statistics involved in the second historical deviation value. Specifically, in the determining process of the second real-time deviation value, the calculation may be directly performed according to the statistical quantity set corresponding to each group of train operation data and the statistical quantity set corresponding to the real-time operation data, but not according to the combination of each target historical operation data in each group of historical operation data and the real-time operation data in the determining process of the second historical deviation value.

In the method provided by the embodiment of the invention, the first real-time deviation value and the second real-time deviation value can be combined to calculate and obtain the second deviation degree value corresponding to the current preset performance index, namely, the second deviation degree value is determined according to the deviation degree between the statistical characteristics of the running data of each train and the statistical characteristics of the real-time running data. The specific calculation principle may be the same as the calculation principle of the first deviation degree value, and reference may be made to the description of the first deviation degree value determination process in the above embodiments, which is not described herein again.

Further, on the basis of the method provided in the foregoing embodiment, in the method provided in an embodiment of the present invention, the determining the performance index value corresponding to the preset performance index according to the first deviation degree value and the second deviation degree value includes:

In the method provided by the embodiment of the present invention, a first preset weight and a second preset weight may be preset according to actual requirements, and are used for performing weighted sum operation on the two types of deviation degree values, where the sum of the first preset weight and the second preset weight is one. And weighting and calculating the first deviation degree value and the second deviation degree value based on the first preset weight and the second preset weight, and taking the calculation result as a performance index value corresponding to the current preset performance index.

Further, on the basis of the method provided in the foregoing embodiment, the determining, according to the performance index value corresponding to each preset performance index in the performance index set, a comprehensive performance index value corresponding to the preset evaluation object includes:

in the method provided by the embodiment of the present invention, the number of preset performance indexes included in a performance index set corresponding to a current preset evaluation object may be determined, so as to determine whether the number of the preset performance indexes included in the performance index set is one, that is, whether only one preset performance index is included.

in the method provided by the embodiment of the present invention, if the number of the preset performance indexes included in the performance index set is multiple, the index weight corresponding to each preset performance index in the performance index set is determined according to a preset weight calculation strategy.

In the method provided by the embodiment of the invention, based on the index weight of each preset performance index in the performance index set, the performance index value corresponding to each preset performance index is weighted and calculated, and the comprehensive performance index value corresponding to the current preset evaluation object is obtained.

On the basis of the method provided in the foregoing embodiment, in the method provided in the embodiment of the present invention, the process of determining the index weight corresponding to each preset performance index includes:

in the method provided by the embodiment of the present invention, for each preset performance index in the performance index set, based on the performance index value corresponding to each preset performance index in the performance index set, the information entropy corresponding to the preset performance index is calculated. Specifically, the calculation formula of the information entropy corresponding to each preset performance index may be as follows:

wherein E is _i Expressing the information entropy of the ith preset performance index, k expressing the number of statistical features corresponding to the preset performance index, p _d And expressing the probability corresponding to the d-th statistical characteristic corresponding to the preset performance index, wherein the probability represents the proportion of the d-th statistical characteristic in the k statistical characteristics, and is a value obtained by normalizing the characteristic value of the d-th statistical characteristic.

In the method provided by the embodiment of the invention, for each preset performance index, the corresponding index weight can be calculated based on the corresponding information entropy. Specifically, the calculation formula of the index weight may be as follows:

wherein, W _i And the index weight corresponding to the ith preset performance index is represented, and n represents the number of the preset performance indexes in the performance index set.

Further, on the basis of the method provided by the above embodiment, the method provided by the embodiment of the present invention further includes:

In the method provided by the embodiment of the present invention, if it is determined that there is only one preset performance index in the performance index set, the performance index value corresponding to the preset performance index is used as the comprehensive performance index value corresponding to the current preset evaluation object.

Based on the method shown in fig. 1, in the method provided in the embodiment of the present invention, the step S106 of determining the performance state corresponding to each of the preset evaluation objects according to the comprehensive performance index value corresponding to each of the preset evaluation objects includes:

in the method provided by the embodiment of the invention, multiple preset performance states corresponding to each preset evaluation object and an index value interval corresponding to each preset performance state corresponding to each preset evaluation object can be preset according to actual requirements. And determining a plurality of index value intervals corresponding to each preset evaluation object based on the preset configuration information.

In the method provided by the embodiment of the present invention, the comprehensive performance index value corresponding to each preset evaluation object may be matched with each index value interval corresponding to the preset evaluation object to determine in which index value interval the comprehensive performance index value is located, the index value interval in which the comprehensive performance index value is located (i.e., the index value interval matched with the comprehensive performance index value) is used as a target index value interval, and the preset performance state corresponding to the target index value interval is determined as the performance state corresponding to the preset evaluation object.

In order to better illustrate the method provided by the embodiment of the present invention, next, in combination with a specific application scenario, the embodiment of the present invention provides another train performance evaluation method, the method provided by the embodiment of the present invention is applicable to a train performance evaluation system, the train performance evaluation system is an instantiation of the method shown in fig. 1, a schematic structural diagram of the train performance evaluation system can be shown in fig. 2, and the train performance evaluation system is mainly deployed on a ground server and includes a data processing module, a key performance evaluation model and a result display module. The key performance evaluation model comprises a performance evaluation module and an operation performance comprehensive analysis module which correspond to each preset evaluation object, wherein each performance evaluation module comprises a brake system performance evaluation module, a pantograph performance evaluation module, a low-voltage apparatus performance evaluation module, a traction motor performance evaluation module, a walking part performance evaluation module and the like. The braking system, the pantograph, the low-voltage apparatus, the traction motor, the running gear and other systems and components are preset evaluation objects in the embodiment of the invention.

The train performance evaluation system comprises a train, a data processing module and a data processing module, wherein the train comprises a motor temperature sensor, a main air reservoir pressure sensor and other vehicle-mounted sensors in the train, the vehicle-mounted sensors can acquire signal variable data in real time, and the acquired signal variable data can be sent to the data processing module of a ground server through a Wireless Local Area Network (WLAN) so as to evaluate the train performance.

It should be noted that the structure shown in fig. 2 is only to better illustrate a specific embodiment provided by the method provided by the present invention, and in a specific implementation process, the system architecture is not limited to the specific content shown in fig. 2, for example, other performance evaluation modules may be adopted, and is also not limited to WLAN transmission, and other communication methods may be adopted to transmit data, such as 5G, etc., without affecting the implementation function of the method provided by the embodiment of the present invention.

Based on the performance evaluation model shown in fig. 2, the train performance evaluation process provided by the embodiment of the invention mainly includes: the method comprises the processes of signal variable data acquisition, train operation data transmission, train operation data processing, key performance evaluation model evaluation, result display and the like.

Acquiring signal variable data;

in the method provided by the embodiment of the invention, the train obtains the environmental variable data of the key components through the vehicle-mounted sensors, such as the motor temperature sensor and the total air cylinder pressure sensor, and the environmental variable data also can comprise a voltage sensor, a current sensor and the like.

Transmitting train operation data;

according to the method provided by the embodiment of the invention, signal variable data such as voltage, current and the like are acquired through the vehicle-mounted sensor, and data such as train operation information, whole-train equipment state information and the like are packaged according to a set message format and then transmitted to the ground server through the WLAN.

Processing train operation data;

in the method provided by the embodiment of the invention, after the ground server receives the transmitted data packet, the data processing module stores the data on one hand, analyzes the data according to the set message format on the other hand, and sends the data to each performance evaluation module in the specified format according to the requirement.

Evaluating a key performance evaluation model;

in the method provided by the embodiment of the invention, a key performance evaluation model is established on the basis of historical operation data and in combination with real-time operation data. The model mainly comprises two parts: the first is each performance evaluation module, which is used to obtain the key performance index (i.e. performance index value) of each preset evaluation object. And the operation performance comprehensive analysis module is used for comprehensively evaluating the performance state of the key components (namely the preset evaluation objects) of the train. And each performance evaluation module receives corresponding variable data to calculate key performance indexes. And after each performance evaluation module completes the calculation, the obtained key performance indexes are sent to the running performance comprehensive analysis module. And after key performance indexes of all parts are obtained, evaluating the running performance of the train by adopting a comprehensive analysis method, and sending the result to a result display module.

Displaying the result;

in the method provided by the embodiment of the invention, the result display module receives the output result of the key performance evaluation model and then displays the output result in a visual mode such as a chart and the like.

The evaluation process of the key performance evaluation model provided by the embodiment of the invention is further explained below.

In the method provided by the embodiment of the invention, after the ground server receives the train signal variable data, the performance of each key component in the running process of the train is quantitatively described by using the key performance evaluation model, and a specific schematic diagram of the train performance evaluation process can be shown in fig. 3.

Each performance evaluation module calculates a key performance index based on the corresponding variable data to obtain a performance index value, and as shown in fig. 3, calculates the key performance index based on variable data such as brake system variable data, pantograph variable data, low-voltage apparatus variable data, traction motor variable data, and running gear variable data, respectively. The performance evaluation module may calculate a plurality of key performance indicators, or only one key performance indicator.

And the operation performance comprehensive analysis module is used for comprehensively analyzing the key performance indexes calculated by each performance evaluation module. And if only one key performance index is calculated by the performance evaluation module, determining the performance state of the corresponding component or system of the performance evaluation module based on the index value of the key performance index. If the performance evaluation module calculates a plurality of key performance indexes, the index value of the component corresponding to the performance evaluation module needs to be adjusted, specifically, normalization processing can be performed on each key performance index calculated by the performance evaluation module, the information entropy corresponding to each key performance index is calculated, each key performance index is integrated based on the information entropy corresponding to each key performance index, the index value of the component or the system is adjusted based on the integration result, and the performance state of the corresponding component or the system is determined based on the adjusted index value. As shown in fig. 3, the performance states of the components or systems, such as the performance state of the brake system, the performance state of the pantograph, the performance state of the low-voltage apparatus, the performance state of the traction motor, the performance state of the running gear, and the like, can be obtained through comprehensive analysis to represent the performance states of the train.

Next, the calculation of the key performance index and the comprehensive analysis of the operation performance in the method provided by the embodiment of the present invention are further described.

In the method provided in the embodiment of the present invention, an example process diagram of calculating a certain key performance index of a certain component or system (a preset evaluation object) is shown in fig. 4, and the method mainly includes the following steps:

calculating the same-vehicle deviation degree SE ₁ The running data of the latest n times of road crossing of the vehicle is analyzed, and the current signal variable data is combined to obtain the same vehicle deviation degree SE of the current road crossing ₁ ；

Calculating the deviation degree SE of other vehicle performance ₂ The running data of the m trains in the same time section is analyzed, and the current signal variable data is combined to obtain the deviation degree SE of other trains of the current intersection ₂ ；

Binding SE ₁ And SE ₂ Calculating a key performance index SE.

In the method provided by the embodiment of the invention, the same-vehicle deviation degree SE ₁ The calculation process mainly comprises the following steps:

analyzing the operation data of the latest n times of crossing of the train currently evaluated, calculating statistics such as the maximum value, the minimum value, the mean value and the like of the operation data by taking one time of crossing as a unit, and forming a characteristic vector V as [ V ═ V [ ₁ ,v ₂ ,...,v _k ]And then obtaining a feature matrix R ₁ ＝[V ₁ ,V ₂ ,...,V _n ]。

R can be calculated according to the following formula ₁ Degree of deviation of (i.e. SE) ₁ ：

Wherein, the first and the second end of the pipe are connected with each other,

wherein i represents the ith statistical characteristic, k represents the number of the statistical characteristics, j represents the jth intersection, and n represents the number of the intersections. v. of _ij And the statistical value of the ith statistical characteristic representing the jth intersection.

In the method provided by the embodiment of the invention, the same-vehicle deviation degree SE ₂ The calculation process mainly comprises the following steps:

analyzing the running data of m trains in the same time segment, calculating statistics such as maximum value, minimum value and mean value of the running data by taking one train in the same time segment as a unit, and forming a characteristic vector V ═ V ₁ ,v ₂ ,...,v _k ]To obtain a feature matrix R ₂ ＝[V' ₁ ,V' ₂ ,...,V' _m ]。

R can be calculated according to the following formula ₂ Degree of deviation, i.e. SE ₂ ：

Wherein the content of the first and second substances,

wherein i represents the ith statistical characteristic, k represents the number of the statistical characteristics, j represents the jth train, and m represents the number of the trains in the same time period. v. of _ij A statistical value representing an ith statistical characteristic of a jth train.

In the method provided by the embodiment of the invention, the calculation process of the key performance index mainly comprises the following steps:

calculating statistics such as maximum value, minimum value and mean value of the current operation data of the current estimated train to form a characteristic vector V ═ V ₁ ,v ₂ ,...,v _k ]。

For the feature matrix R ₁ Replacing R by a feature vector V ₁ V in ₁ Then, calculation is performed based on equation 3 to obtain SE ₁ '. the first deviation degree value DeltaSE can be calculated according to the following formula ₁ ：

ΔSE ₁ ＝SE ₁ '-SE ₁ (formula 5)

For the feature matrix R ₂ Adding the feature vector V to R ₂ Then, SE is calculated based on the following formula ₂ ’：

Wherein the content of the first and second substances,

wherein the meaning of each parameter is the same as that of the parameter in formula 4, see the above description.

Calculating a second deviation metric Δ SE according to the following formula ₂ ：

ΔSE ₂ ＝SE ₂ '-SE ₂ (equation 7)

The key performance indicator SE may be calculated based on the following formula:

SE＝w ₁ ΔSE ₁ +w ₂ ΔSE ₂ (formula 8)

Wherein, w ₁ +w ₂ ＝1。w ₁ And w ₂ Is a weight preset according to the requirement.

In the method provided by the embodiment of the invention, the process of comprehensively analyzing the train running performance mainly comprises the following steps:

for each component or system, each key performance index corresponding to the component or system is normalized, the respective information entropy of each key performance index can be calculated according to a formula of the information entropy (namely formula 1), and the weight of each key performance index can be calculated according to formula 2. For the component or system, the final index value Z may be calculated according to the following formula:

wherein SE _i SE, W as the ith key performance indicator _i The weight of the ith key performance index is obtained, and n is the number of the key performance indexes.

The performance state of the component or system is determined according to the following rules:

if Z < r _alarm The performance status is healthy if r _alarm ≤Z＜r _warning The performance state is early warning, if Z is more than or equal to r _warning The performance state is an alarm state. r is _alarm And r _warning And can be preset according to requirements.

According to the method provided by the embodiment of the invention, the vehicle-mounted signal variable data is transmitted to the ground server through the data transmission module, and then the train operation data is processed and analyzed through the data processing module, the key performance evaluation module of each component and the operation performance comprehensive analysis module on the server, so that an intelligent, accurate and rapid train key performance evaluation system is formed, and the method has the function of evaluating the performance states of key components such as a train braking system, a pantograph, a low-voltage electric appliance, a traction motor, a running gear and the like.

According to the method provided by the embodiment of the invention, the key performance indexes of each part are extracted by using the historical data of the same train and other train operation data, the comprehensive analysis of the train operation performance is realized through an information entropy theory, and the state evaluation of the operation performance of each key part (such as a braking system, a pantograph, a low-voltage apparatus, a traction motor, a running gear and the like) of the train is realized.

Based on the method provided by the embodiment of the invention, a quantitative evaluation rule can be established for the train operation data, and the quantitative analysis of the train operation performance is realized. The dynamic change of the operation data can be captured in advance, prior knowledge is provided for fault diagnosis, and a data analysis basis is provided for forming a quick response mechanism with early discovery, early isolation and early processing. Powerful data support can be provided for establishing a train performance evaluation system, and a solid foundation is laid for intelligent operation of railways.

Corresponding to the train performance evaluation method shown in fig. 1, an embodiment of the present invention further provides a train performance evaluation apparatus, which is used for implementing the method shown in fig. 1, and a schematic structural diagram of the apparatus is shown in fig. 5, and includes:

the first determining unit 201 is configured to determine, when current operation information of a target train in a running state is received, real-time operation information corresponding to each preset evaluation object according to the current operation information of the target train, where the current operation information of the target train includes signal data acquired by each vehicle-mounted sensor of the target train in the current operation state;

a first obtaining unit 202, configured to obtain historical intersection operation information of the target train, and determine historical operation information corresponding to each preset evaluation object according to the historical intersection operation information;

a second obtaining unit 203, configured to obtain current operation information of multiple operating trains, where the operating trains are trains outside the target train and currently in a running state, and the current operation information of each operating train includes signal data acquired by each vehicle-mounted sensor of the operating train in the current operating state;

a second determining unit 204, configured to determine, according to the current operation information of the multiple operating trains, simultaneous train operation information corresponding to each preset evaluation object;

a third determining unit 205, configured to determine, for each preset evaluation object, a comprehensive performance index value corresponding to the preset evaluation object according to the real-time operation information, the historical operation information, and the train operation information of the same time segment corresponding to the preset evaluation object;

and the evaluation unit 206 is configured to determine a performance state corresponding to each preset evaluation object according to the comprehensive performance index value corresponding to each preset evaluation object, so as to implement performance evaluation on the target train.

Based on the device provided by the embodiment of the invention, the real-time running information, the historical running information and the running information of the trains at the same time corresponding to each preset evaluation object are respectively determined according to the current running information, the historical intersection running information and the current running information of each running train of the target train. For each preset evaluation object, determining a comprehensive performance index value corresponding to the preset evaluation object according to the real-time operation information, the historical operation information and the train operation information of the same time segment corresponding to the preset evaluation object; and determining the performance state corresponding to each preset evaluation object according to the comprehensive performance index value corresponding to each preset evaluation object so as to evaluate the performance of the target train. By applying the device provided by the embodiment of the invention, the running data corresponding to the preset evaluation object can be combined under various driving scenes, the comprehensive performance index value corresponding to the preset evaluation object is calculated, the corresponding performance state is determined, and the performance evaluation result of the train is represented by the performance state of each preset evaluation object. The train performance can be automatically evaluated according to the unified standard, quantitative evaluation is realized, the accuracy of performance evaluation is improved, and the safe and stable operation of the train is guaranteed. Secondly, the performance state is analyzed by applying big data, so that the accuracy of performance state evaluation can be further improved.

On the basis of the device shown in fig. 5, the device provided in the embodiment of the present invention may further include other units, and specific unit functions may refer to the above train performance evaluation method, and are not described in detail herein.

The embodiment of the invention also provides a storage medium, which comprises a stored instruction, wherein when the instruction runs, the equipment where the storage medium is located is controlled to execute the train performance evaluation method.

An electronic device is provided in an embodiment of the present invention, and the structural diagram of the electronic device is shown in fig. 6, which specifically includes a memory 301 and one or more instructions 302, where the one or more instructions 302 are stored in the memory 301 and configured to be executed by one or more processors 303 to perform the following operations of the one or more instructions 302:

acquiring current operation information of a plurality of operating trains, wherein the operating trains are trains outside the target train and in a running state at present, and the current operation information of each operating train comprises signal data acquired by each vehicle-mounted sensor of the operating train in the current operation state;

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described system and system embodiments are only illustrative, wherein the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A train performance evaluation method, comprising:

2. The method according to claim 1, wherein the determining of the comprehensive performance index value corresponding to the preset evaluation object according to the real-time operation information, the historical operation information and the train operation information of the same time segment corresponding to the preset evaluation object comprises:

and determining the comprehensive performance index value corresponding to the preset evaluation object according to the performance index value corresponding to each preset performance index in the performance index set.

3. The method of claim 2, wherein determining the first deviation metric corresponding to the predetermined performance metric comprises:

4. The method of claim 3, wherein determining a first historical deviation value based on a set of statistics corresponding to each set of historical operating data comprises:

and calculating a first arithmetic mean value, and taking the first arithmetic mean value as the first history deviation value, wherein the first arithmetic mean value is an arithmetic mean value corresponding to each history deviation characteristic value.

5. The method of claim 3, wherein determining a second historical deviation value based on the set of statistics for each of the sets of historical operating data and the set of statistics for the real-time operating data comprises:

6. The method of claim 3, wherein determining the first deviation metric corresponding to the predetermined performance metric based on the first historical deviation value and the second historical deviation value comprises:

7. The method of claim 3, wherein determining the second deviation metric corresponding to the predetermined performance metric comprises:

8. The method of claim 2, wherein determining the performance index value corresponding to the predetermined performance index according to the first deviation degree value and the second deviation degree value comprises:

9. The method of claim 2, wherein the determining the comprehensive performance index value corresponding to the preset evaluation object according to the performance index value corresponding to each preset performance index in the performance index set comprises:

10. The method according to claim 9, wherein the determining the index weight corresponding to each preset performance index comprises:

11. The method of claim 9, further comprising:

12. The method according to claim 1, wherein the determining the performance status of each of the predetermined evaluation objects according to the composite performance index value corresponding to each of the predetermined evaluation objects comprises:

13. A train performance evaluation device characterized by comprising:

the system comprises a first determining unit, a second determining unit and a judging unit, wherein the first determining unit is used for determining real-time running information corresponding to each preset evaluation object according to the current running information of a target train when the current running information of the target train in a running state is received, and the current running information of the target train comprises signal data acquired by each vehicle-mounted sensor of the target train in the current running state;

14. A storage medium comprising stored instructions, wherein the instructions, when executed, control a device on which the storage medium is located to perform the train performance evaluation method according to any one of claims 1 to 12.

15. An electronic device comprising a memory, and one or more instructions stored in the memory and configured to be executed by the one or more processors to perform the train performance assessment method of any one of claims 1-12.