Locomotive operation evaluation method, device, equipment and medium
By extracting information, extracting features, and classifying historical locomotive operation data, and combining this with standard data analysis, the problems of automation and accuracy in locomotive operation status assessment in existing technologies have been solved, and automated and accurate assessment of locomotive operation status has been achieved.
Patent Information
- Application Number
- CN202511334378.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-18
- Publication Date
- 2025-12-12
AI Technical Summary
Existing technologies are insufficient for automating and accurately assessing locomotive operating status, resulting in low reliability of assessment results.
By acquiring historical operating data of locomotives, extracting driving information based on preset operating indicators, performing feature extraction and classification, and combining it with standard operating data for analysis, the operating analysis results are obtained, and finally the locomotive is evaluated.
It enables automated analysis of locomotive operation data, accurately obtains evaluation results, provides real changes in locomotive operating status, and improves the reliability of the evaluation.
Smart Images
Figure CN121117501A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data analysis technology, and in particular to a locomotive operation evaluation method, apparatus, equipment and medium. Background Technology
[0002] In the railway transportation sector, accurate assessment of locomotive operating status is crucial for ensuring transportation safety and improving efficiency. Currently, locomotive operation assessments largely rely on manual inspections and experience-based judgment, involving manual calculation and verification of collected data. However, this approach has many shortcomings.
[0003] Currently, most locomotive operation assessments utilize statistical analysis techniques to process locomotive operating data. By statistically analyzing large amounts of historical data, simple mathematical models are established to evaluate locomotive operating efficiency. However, because locomotive operating conditions are influenced by a variety of complex factors, this method struggles to reflect the true changes in locomotive operating conditions, resulting in low reliability of the assessment results.
[0004] Therefore, how to automatically analyze locomotive operation data and obtain accurate analysis results has become an urgent problem to be solved. Summary of the Invention
[0005] In view of this, embodiments of this application provide a locomotive operation evaluation method, apparatus, equipment, and medium to solve the problem of how to automatically analyze locomotive operation data to accurately obtain locomotive analysis results.
[0006] In a first aspect, embodiments of this application provide a locomotive operation evaluation method, including: The historical operating data of the locomotive to be evaluated is obtained, and information is extracted from the historical operating data according to the preset operating indicators to obtain the locomotive driving information; Feature extraction is performed on the locomotive driving information to obtain key locomotive parameters, and the key locomotive parameters are classified to obtain parameter types; Obtain preset standard operating data, extract parameter driving information corresponding to the parameter type from the locomotive driving information, analyze the parameter driving information based on the standard operating data, and obtain the operating analysis result corresponding to the parameter type; Based on the operational analysis results, the locomotive to be evaluated is evaluated, and the evaluation results are obtained.
[0007] Secondly, according to an embodiment of this application, a locomotive operation evaluation device includes: The data extraction module is used to acquire historical operating data of the locomotive to be evaluated, and extract information from the historical operating data according to preset operating indicators to obtain locomotive driving information. The parameter classification module is used to extract features from the locomotive driving information to obtain key locomotive parameters, and classify the key locomotive parameters to obtain parameter types; The information analysis module is used to acquire preset standard operating data, extract parameter driving information corresponding to the parameter type from the locomotive driving information, analyze the parameter driving information according to the standard operating data, and obtain the operating analysis result corresponding to the parameter type. The evaluation module is used to evaluate the locomotive to be evaluated based on the operational analysis results and obtain the evaluation results.
[0008] Thirdly, embodiments of this application provide a computer device, the computer device including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the locomotive operation evaluation method as described in the first aspect.
[0009] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the locomotive operation evaluation method as described in the first aspect.
[0010] The beneficial effects of the embodiments in this application compared with the prior art are: This application acquires historical operating data of the locomotive to be evaluated, extracts information from the historical operating data according to preset operating indicators to obtain locomotive driving information, extracts features from the locomotive driving information to obtain key parameters of the locomotive, classifies the key parameters to obtain parameter types, acquires preset standard operating data, extracts parameter driving information corresponding to the parameter types from the locomotive driving information, analyzes the parameter driving information according to the standard operating data to obtain the corresponding parameter type's operating analysis results, and evaluates the locomotive to be evaluated based on the operating analysis results to obtain the evaluation results. By acquiring historical operating data of the locomotive to be evaluated and extracting locomotive driving information according to preset operating indicators, extracting key parameters and classifying them to obtain parameter types, acquiring preset standard operating data, extracting driving information corresponding to the parameter types for analysis to obtain operating analysis results, and finally evaluating the locomotive based on these results, an evaluation result is obtained. Therefore, automating the analysis of locomotive operating data to accurately obtain locomotive analysis results is an urgent problem to be solved. Attached Figure Description
[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0012] Figure 1 This is a schematic diagram of an application environment for a locomotive operation evaluation method provided in Embodiment 1 of this application; Figure 2 This is a flowchart illustrating a locomotive operation evaluation method provided in Embodiment 2 of this application; Figure 3 This is a flowchart illustrating a locomotive operation evaluation method provided in Embodiment 3 of this application; Figure 4 This is a flowchart illustrating a locomotive operation evaluation method provided in Embodiment 4 of this application; Figure 5 This is a flowchart illustrating a locomotive operation evaluation method provided in Embodiment 5 of this application; Figure 6 This is a schematic diagram of the structure of a locomotive operation evaluation device provided in Embodiment Six of this application; Figure 7 This is a schematic diagram of the structure of a computer device provided in Embodiment 7 of this application. Detailed Implementation
[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.
[0014] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.
[0015] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.
[0016] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."
[0017] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0018] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.
[0019] It should be understood that the sequence number of each step in the following embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0020] To illustrate the technical solution of this application, specific embodiments are described below.
[0021] The locomotive operation evaluation method provided in Embodiment 1 of this application can be applied to, for example, Figure 1 In this application environment, the client and server communicate with each other. Users can provide conditions, requirements, and operational instructions for locomotive operation evaluation through the client. The server generates control instructions for the locomotive operation evaluation method based on the content sent by the client. The client includes, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a standalone server or a server cluster consisting of multiple servers.
[0022] See Figure 2 This is a flowchart illustrating a locomotive operation evaluation method provided in Embodiment 2 of this application. The locomotive operation evaluation method described above can be applied to...Figure 1 The server-side component.
[0023] like Figure 2 As shown, the locomotive operation evaluation method may include the following steps: Step S201: Obtain historical operating data of the locomotive to be evaluated; extract information from the historical operating data according to preset operating indicators to obtain locomotive driving information. Optionally, after extracting information from the historical operating data according to preset operating indicators to obtain locomotive driving information, the following steps may also be included: The locomotive driving information is processed according to a preset data standard to obtain processed data; The collected data is analyzed to obtain missing data, and the missing data is imputed to obtain integrated data.
[0024] Historical operational data refers to the operational records stored in the train operation monitoring and recording device. Operational indicators include locomotive attributes, train formation information, key point data, section running time, section length, locomotive signals, locomotive start and stop times, station track information, and temporary slow-moving information. Information is extracted from historical data according to these operational indicators to obtain locomotive operation information.
[0025] The preset data standards are designed to make the extracted locomotive driving information more standardized. These standards include data format, data range, and data encoding. By using these standards, the data is structured and processed to obtain organized data. The organized data is then analyzed, and missing data at non-critical points is appropriately imputed using methods such as averages and medians to obtain integrated data.
[0026] Step S202: Extract features from the locomotive driving information to obtain key locomotive parameters, and classify the key locomotive parameters to obtain parameter types; Feature extraction involves filtering from a large amount of raw data to extract the essential features that best represent locomotive operating information. This involves extracting features from the locomotive's operating information to obtain key locomotive parameters containing specific values such as speed, travel time, and dwell time. These key locomotive parameters are then analyzed... The classification process yields the parameter types corresponding to the key locomotive parameters, such as speed parameter types, slow-moving parameter types, and deceleration parameter types.
[0027] Step S203: Obtain preset standard operating data, extract parameter driving information corresponding to the parameter type from the locomotive driving information, analyze the parameter driving information according to the standard operating data, and obtain the operating analysis result corresponding to the parameter type; The standard operating data includes key point speeds, speed limits, locomotive status operating data, section length, section running time, locomotive signals, station stops, locomotive attributes, and train formation information.
[0028] The parameter driving information corresponding to the parameter type in the locomotive driving information is the specific data corresponding to each parameter type. By combining the parameter driving information with the standard operating data, the information difference between the parameter driving information and the standard operating data is analyzed, and the difference analysis result is the operation analysis result of the corresponding parameter type.
[0029] Step S204: Based on the operational analysis results, evaluate the locomotive to be evaluated to obtain the evaluation results.
[0030] Optionally, the step of evaluating the locomotive to be evaluated based on the operational analysis results to obtain the evaluation result may include the following steps: The operational analysis results were analyzed to identify the factors contributing to the abnormal operation. Based on the abnormal operation factors, the responsibility factors of the locomotive to be evaluated are obtained; The assessment results are obtained based on the aforementioned responsibility factors.
[0031] Optionally, after evaluating the locomotive to be evaluated based on the operational analysis results and obtaining the evaluation results, the process may further include the following steps: An evaluation report will be generated based on the evaluation results. Based on the evaluation report, the strategy for generating and adjusting the locomotive to be evaluated is adopted.
[0032] The process involves comprehensively evaluating the entire locomotive based on the operational analysis results obtained in step S203, resulting in an overall assessment. These results cover the locomotive's performance in multiple areas, including power, safety, and economic performance. Analyzing the operational results identifies the specific operational factors causing the locomotive's abnormal operation, clarifying which specific operational behaviors affected its normal operation—that is, determining the responsibility factors for the locomotive under evaluation. After comprehensively considering these responsibility factors, their severity is assessed, leading to the final assessment result.
[0033] The final assessment results will present the locomotive's operating status, existing problems, and responsible factors in a standardized and detailed report. Based on the content of the assessment report, corresponding adjustment strategies will be formulated to address the problems existing in the locomotive.
[0034] This application acquires historical operating data of the locomotive to be evaluated, extracts information from the historical operating data according to preset operating indicators to obtain locomotive driving information, extracts features from the locomotive driving information to obtain key parameters of the locomotive, classifies the key parameters to obtain parameter types, acquires preset standard operating data, extracts parameter driving information corresponding to the parameter types from the locomotive driving information, analyzes the parameter driving information according to the standard operating data to obtain the corresponding parameter type's operating analysis results, and evaluates the locomotive to be evaluated based on the operating analysis results to obtain the evaluation results. By acquiring historical operating data of the locomotive to be evaluated and extracting locomotive driving information according to preset operating indicators, extracting key parameters and classifying them to obtain parameter types, acquiring preset standard operating data, extracting driving information corresponding to the parameter types for analysis to obtain operating analysis results, and finally evaluating the locomotive based on these results, an evaluation result is obtained. Therefore, automating the analysis of locomotive operating data to accurately obtain locomotive analysis results is an urgent problem to be solved.
[0035] See Figure 3 This is a flowchart illustrating a locomotive operation evaluation method provided in Embodiment 3 of this application. Figure 3 As shown, the parameter types include speed parameter types, slow-moving parameter types, and deceleration parameter types. Step S203, which involves extracting the parameter driving information corresponding to the parameter type from the locomotive driving information and analyzing the parameter driving information based on the standard operating data to obtain the operating analysis result corresponding to the parameter type, may include the following steps: Step S301: Obtain a preset driving node and extract the node standard speed corresponding to the driving node from the standard operating data.
[0036] Step S302: Based on the driving node, extract the parameter node speed corresponding to the driving node from the parameter driving information.
[0037] Step S303: Based on the standard speed of the node, retrieve the speed of the parameter node to obtain the speed difference value, analyze the speed difference value, and obtain the operation analysis result of the speed parameter type.
[0038] Among them, the travel node refers to a set of specific locations determined in advance based on the characteristics of the locomotive's operating line and the requirements of the task. The standard speed of these travel nodes can be extracted from the standard operating data. Travel nodes may include the standard speed at key points such as the speed when passing through a phase transition, the speed when passing through a gradient, the speed that should be maintained in a section, the speed when passing through a test brake point, and the speed when passing through a turnout.
[0039] Based on the previously determined travel nodes, the actual speeds reached by the locomotive at these corresponding travel nodes are retrieved from the parameter travel information. The parameter node speed for each travel node is calculated and compared with the corresponding standard node speed. The difference is calculated to obtain the speed difference value. If the speed difference value is within a pre-set reasonable error range, it indicates that the locomotive is operating well according to the speed method and can maintain an appropriate speed at each travel node as required by the standard. When the speed difference value exceeds the reasonable range, it may affect transportation efficiency.
[0040] In this embodiment of the application, by analyzing the speed difference values at each travel node, the locomotive's operating status in terms of speed parameter type can be comprehensively evaluated, providing a basis for the overall operation evaluation of the locomotive.
[0041] See Figure 4 This is a flowchart illustrating a locomotive operation evaluation method provided in Embodiment 4 of this application. Figure 4 As shown, step S203, which involves extracting the parameter driving information corresponding to the parameter type from the locomotive driving information and analyzing the parameter driving information based on the standard operating data to obtain the operating analysis result corresponding to the parameter type, may include the following steps: Step S401: Based on the preset driving range, extract the standard range driving time corresponding to the driving range from the standard driving data; Step S402: Extract the actual interval running time from the parameter driving information. If the actual interval running time exceeds the standard interval running time, calculate the actual interval running time to obtain the interval running efficiency.
[0042] Step S403: Analyze the operating efficiency of the interval to obtain the operating analysis results of the type of operation delay parameter.
[0043] The running section is mainly calculated based on parameters such as locomotive speed limit, temporary slow-moving in the section, reduction of locomotive start and stop time, and reduction of station track running time. The running time of the running section is compared and analyzed with the running time in the standard running data to determine whether the running section has slowed down.
[0044] If the actual interval travel time exceeds the standard interval travel time, a judgment is made based on the standard interval travel time. There are four scenarios for the actual interval travel time: The first scenario is that the train passes through the preceding station and the following station in the same section. In this case, the section running time = the time of the central event of the terminal station passing through the station - the time of the central event of the originating station passing through the station.
[0045] The second scenario is that the train passes through the station before the end of the section and stops at the station after the end. In this case, the section running time = running time (the time difference between the passing center of the starting station and the in-station parking record of the ending station) + additional parking time.
[0046] The third scenario is where the train stops at the station before the station and passes through the station after the station. In this case, the running time of the section = additional time for departure + running time (time difference between the departure event at the starting station and the passing event at the ending station).
[0047] The fourth scenario is where the train stops at the station before and after the station in the section. In this case, the section running time = additional time for departure + running time (time difference between departure events at the starting station and stopping events at the ending station) + additional time for stopping.
[0048] The deceleration rate of the operating section = (section running time - standard running time of the section) / standard running time of the section, which is used for statistical report output.
[0049] Based on the comprehensive analysis of the section operation efficiency, specific operational analysis results regarding the types of operation and slowdown parameters were obtained, providing an important basis for locomotive operation management. Measures have been taken in a timely manner to improve the locomotive's operating condition.
[0050] This application enhances the security of the execution instruction generation process by verifying the host communication public key. Only authorized execution hosts can receive valid execution instructions, ensuring that the execution of scheduled tasks takes place in a secure and reliable environment. This is crucial for protecting sensitive system data and critical business operations. See Figure 5 This is a flowchart illustrating a locomotive operation evaluation method provided in Embodiment 5 of this application. Figure 5 As shown, step S203, which involves extracting the parameter driving information corresponding to the parameter type from the locomotive driving information and analyzing the parameter driving information based on the standard operating data to obtain the operating analysis result corresponding to the parameter type, may include the following steps: Step S501: Obtain the preset driving position and extract the standard position speed corresponding to the driving position from the standard operating data; Step S502: Extract the actual position speed corresponding to the driving position from the parameter driving information, and analyze the speed difference between the actual position speed and the standard position speed.
[0051] Step S503: Analyze the slow-moving parameter type based on the speed difference to obtain the slow-moving analysis result corresponding to the slow-moving parameter type.
[0052] The preset travel position is a location pre-selected on the locomotive's travel route, determined based on the characteristics of the line, safety requirements, or operational management needs.
[0053] The actual speed reached by the locomotive at the preset driving position is extracted from the locomotive's driving information; this is the actual position speed. The actual position speed is compared with the standard position speed to obtain the speed difference. When the actual speed is continuously lower than the standard speed value exceeding the set deviation threshold, and the duration reaches the minimum continuous duration, it is determined to be a continuous slow-moving state. Combining the temporal changes in signal status and locomotive operating conditions in the parameter driving information, the existence of liability-exempt scenarios such as temporary speed limit commands, stop or deceleration signal responses, or emergency braking triggers is checked to determine the attribution of responsibility.
[0054] In this embodiment of the application, by analyzing the speed at the travel position, problems in locomotive operation can be detected in a timely manner, and corresponding measures can be taken to ensure the normal operation of the locomotive and transportation efficiency.
[0055] Corresponding to the locomotive operation evaluation method in the above embodiments, Figure 6 This paper shows a structural block diagram of the locomotive operation evaluation device provided in Embodiment Six of this application. The locomotive operation evaluation device can be applied to... Figure 1 The server-side component is shown. For ease of explanation, only the parts relevant to the embodiments of this application are shown.
[0056] See Figure 6 The locomotive operation evaluation device includes: The data extraction module 61 is used to acquire the historical operating data of the locomotive to be evaluated, and extract information from the historical operating data according to the preset operating indicators to obtain the locomotive driving information. The parameter classification module 62 is used to extract features from the locomotive driving information to obtain key locomotive parameters, and classify the key locomotive parameters to obtain parameter types. The information analysis module 63 is used to acquire preset standard operating data, extract parameter driving information corresponding to the parameter type from the locomotive driving information, analyze the parameter driving information according to the standard operating data, and obtain the operating analysis result corresponding to the parameter type. The evaluation module 64 is used to evaluate the locomotive to be evaluated based on the operation analysis results and obtain the evaluation results.
[0057] Optionally, the locomotive operation evaluation device includes: The data processing module is used to extract information from the historical operating data according to preset operating indicators, obtain locomotive driving information, and then process the locomotive driving information according to preset data standards to obtain processed data. The data interpolation module is used to analyze the organized data, obtain missing data, and perform data interpolation on the missing data to obtain integrated data.
[0058] Optionally, the information analysis module 63 includes: The node speed extraction unit is used to obtain a preset driving node and extract the node standard speed corresponding to the driving node from the standard operating data. The parameter node speed extraction unit is used to extract the parameter node speed corresponding to the driving node from the parameter driving information based on the driving node.
[0059] The speed difference analysis unit is used to retrieve the speed of the parameter node based on the standard speed of the node, obtain the speed difference value, analyze the speed difference value, and obtain the operation analysis result of the speed parameter type.
[0060] Optionally, the information analysis module 63 includes: The standard interval time extraction unit is used to extract the standard interval running time corresponding to the driving interval from the standard running data according to the preset driving interval. The operating efficiency calculation unit is used to extract the actual interval running time from the parameter driving information. If the actual interval running time exceeds the standard interval running time, the actual interval running time is calculated to obtain the interval running efficiency. The operation efficiency analysis unit is used to analyze the operation efficiency of the interval and obtain the operation analysis results of the operation slowdown parameter type.
[0061] Optionally, the information analysis module 63 includes: A standard position and velocity extraction unit is used to obtain a preset driving position and extract the standard position and velocity corresponding to the driving position from the standard operating data. The speed analysis unit is used to extract the actual position speed corresponding to the driving position from the parameter driving information, and analyze the speed difference between the actual position speed and the standard position speed. The slow-moving analysis unit is used to analyze the slow-moving parameter type based on the speed difference and obtain the slow-moving analysis result corresponding to the slow-moving parameter type.
[0062] Optionally, the evaluation module 64 includes: An anomaly analysis unit is used to analyze the operational analysis results to obtain the factors causing the abnormal operation. An abnormal operation analysis unit is used to obtain the responsibility factors of the locomotive to be evaluated based on the abnormal operation factors. The evaluation result acquisition unit is used to obtain the evaluation result based on the responsibility factors.
[0063] Optionally, the locomotive operation evaluation device includes: The analysis result evaluation module is used to evaluate the locomotive to be evaluated based on the operation analysis results, and after obtaining the evaluation results, generate an evaluation report based on the evaluation results. The strategy generation module is used to generate adjustment strategies for the locomotive to be evaluated based on the evaluation report.
[0064] It should be noted that the information interaction and execution process between the above modules, units, and sub-units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.
[0065] Figure 7 This is a schematic diagram of the structure of a computer device provided in Embodiment Seven of this application. Figure 7 As shown, the computer device of this embodiment includes: at least one processor ( Figure 7 Only one is shown in the diagram), a memory, and a computer program stored in the memory and executable on at least one processor. When the processor executes the computer program, it implements the steps of any of the above locomotive operation evaluation methods or locomotive operation evaluation method embodiments.
[0066] This computer device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that... Figure 7 The examples of computer devices are merely examples and do not constitute a limitation on computer devices. Computer devices may include more or fewer components than shown in the illustration, or combinations of certain components, or different components, such as network interfaces, displays, and input devices.
[0067] The processor referred to can be a CPU, but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.
[0068] Memory includes readable storage media, internal memory, etc., wherein internal memory can be the RAM of a computer device, providing an environment for the operation of the operating system and computer-readable instructions stored in the readable storage media. The readable storage media can be the hard drive of a computer device, or in other embodiments, it can be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, memory can include both internal storage units and external storage devices of the computer device. Memory is used to store the operating system, applications, bootloader, data, and other programs, such as program code for computer programs. Memory can also be used to temporarily store data that has been output or will be output.
[0069] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above device can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium can include at least: any entity or device capable of carrying computer program code, a recording medium, a computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.
[0070] The implementation of all or part of the processes in the methods of the above embodiments can also be accomplished by a computer program product. When the computer program product is run on a computer device, it enables the computer device to execute the steps in the above method embodiments.
[0071] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0072] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0073] In the embodiments provided in this application, it should be understood that the disclosed apparatus / computer devices and methods can be implemented in other ways. For example, the apparatus / computer device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.
[0074] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0075] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A locomotive operation evaluation method, characterized in that, include: The historical operating data of the locomotive to be evaluated is obtained, and information is extracted from the historical operating data according to the preset operating indicators to obtain the locomotive driving information; Feature extraction is performed on the locomotive driving information to obtain key locomotive parameters, and the key locomotive parameters are classified to obtain parameter types; Obtain preset standard operating data, extract parameter driving information corresponding to the parameter type from the locomotive driving information, analyze the parameter driving information based on the standard operating data, and obtain the operating analysis result corresponding to the parameter type; Based on the operational analysis results, the locomotive to be evaluated is evaluated, and the evaluation results are obtained.
2. The locomotive operation evaluation method according to claim 1, characterized in that, After extracting information from the historical operating data according to preset operating indicators to obtain locomotive driving information, the method further includes: The locomotive driving information is processed according to a preset data standard to obtain processed data; The collected data is analyzed to obtain missing data, and the missing data is imputed to obtain integrated data.
3. The locomotive operation evaluation method according to claim 1, characterized in that, The parameter types include speed parameter types, slow-moving parameter types, and slow-moving parameter types; The step of extracting parameter driving information corresponding to the parameter type from the locomotive driving information, and analyzing the parameter driving information according to the standard operating data to obtain the operating analysis result corresponding to the parameter type includes: Obtain a preset driving node and extract the node standard speed corresponding to the driving node from the standard operating data; Based on the driving node, extract the parameter node speed corresponding to the driving node from the parameter driving information; Based on the standard speed of the node, the speed of the parameter node is retrieved to obtain the speed difference value. The speed difference value is then analyzed to obtain the operation analysis result of the speed parameter type.
4. The locomotive operation evaluation method according to claim 3, characterized in that, The step of extracting parameter driving information corresponding to the parameter type from the locomotive driving information, and analyzing the parameter driving information according to the standard operating data to obtain the operating analysis result corresponding to the parameter type includes: Based on the preset driving range, extract the standard range driving time corresponding to the driving range from the standard driving data; Extract the actual interval travel time from the parameter travel information. If the actual interval travel time exceeds the standard interval travel time, calculate the actual interval travel time to obtain the interval travel efficiency. The operational efficiency of the aforementioned interval is analyzed to obtain the operational analysis results for the aforementioned operational delay parameter type.
5. The locomotive operation evaluation method according to claim 3, characterized in that, The step of extracting parameter driving information corresponding to the parameter type from the locomotive driving information, and analyzing the parameter driving information according to the standard operating data to obtain the operating analysis result corresponding to the parameter type includes: Obtain a preset driving position and extract the standard position speed corresponding to the driving position from the standard operating data; Extract the actual position speed corresponding to the driving position from the parameter driving information, and analyze the speed difference between the actual position speed and the standard position speed; Based on the speed difference, the slow-moving parameter type is analyzed to obtain the slow-moving analysis result corresponding to the slow-moving parameter type.
6. The locomotive operation evaluation method according to claim 1, characterized in that, The step of evaluating the locomotive to be evaluated based on the operational analysis results to obtain evaluation results includes: The operational analysis results were analyzed to identify the factors contributing to the abnormal operation. Based on the abnormal operation factors, the responsibility factors of the locomotive to be evaluated are obtained; The assessment results are obtained based on the aforementioned responsibility factors.
7. The locomotive operation evaluation method according to claim 1, characterized in that, After evaluating the locomotive to be evaluated based on the operational analysis results and obtaining the evaluation results, the process further includes: An evaluation report will be generated based on the evaluation results. Based on the evaluation report, the strategy for generating and adjusting the locomotive to be evaluated is adopted.
8. A locomotive operation evaluation device, characterized in that, include: The data extraction module is used to acquire historical operating data of the locomotive to be evaluated, and extract information from the historical operating data according to preset operating indicators to obtain locomotive driving information. The parameter classification module is used to extract features from the locomotive driving information to obtain key locomotive parameters, and classify the key locomotive parameters to obtain parameter types; The information analysis module is used to acquire preset standard operating data, extract parameter driving information corresponding to the parameter type from the locomotive driving information, analyze the parameter driving information according to the standard operating data, and obtain the operating analysis result corresponding to the parameter type. The evaluation module is used to evaluate the locomotive to be evaluated based on the operational analysis results and obtain the evaluation results.
9. A computer device, characterized in that, The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the locomotive operation evaluation method as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the locomotive operation evaluation method as described in any one of claims 1 to 7.