Report information generation method and device, equipment and medium

Abstract

The invention relates to the technical field of equipment management, and provides a report information generation method and device, equipment and a medium. The method comprises the following steps: in response to a report information generation instruction, determining a plurality of target devices corresponding to the report information generation instruction; obtaining health information and fault information of each target device in the plurality of target devices in a target time range; according to the health information and the fault information of each target device in the target time range, a target ranking result is determined, and the target ranking result is used for representing the ranking condition of the target devices; and generating report information according to the target ranking result. Based on the scheme of the invention, the reliability of report information can be improved.

Description

Technical Field

[0001] This invention relates to the field of equipment management technology, and in particular to a method, apparatus, equipment and medium for generating report information. Background Technology

[0002] In scenarios such as rail transit, there are numerous pieces of equipment requiring maintenance and management. Obtaining the necessary reports for equipment maintenance and management in advance helps relevant personnel formulate maintenance strategies and optimize resource allocation. However, due to the complex and ever-changing nature of equipment operating conditions, if the final report information fails to present sufficiently comprehensive and effective content, it will be difficult to accurately reflect the overall condition of the equipment and potential risks, thus failing to provide a reliable basis for equipment maintenance and management decisions. Therefore, how to improve the reliability of the report information required for equipment maintenance and management has become an urgent technical problem to be solved. Summary of the Invention

[0003] This application provides a report information generation method, apparatus, device, and medium to solve the technical problem of how to improve the reliability of report information required for equipment maintenance and management.

[0004] In a first aspect, embodiments of this application provide a method for generating report information, including: In response to a report information generation command, identify multiple target devices corresponding to the report information generation command; Acquire health and fault information for each of multiple target devices within a target time range; Based on the health and fault information of each target device within the target time range, the target ranking result is determined, and the target ranking result is used to characterize the ranking of the target devices. Generate report information based on the target ranking results.

[0005] In conjunction with the first aspect, in some possible implementations, in response to a report information generation instruction, multiple target devices corresponding to the report information generation instruction are determined, including: In response to a report information generation instruction, the filtering criteria are determined based on the report information generation instruction. The filtering criteria include at least one of location information, subsystem information, and time information. From the preset device library, select multiple devices that meet the filtering criteria as the target devices corresponding to the report information generation instruction.

[0006] Combining the first aspect and the above implementation methods, in some possible implementation methods, the health information and fault information of each of the multiple target devices within a target time range are obtained, including: Obtain the average health level and health level fluctuation of each target device within the target time range; The health information of each target device is determined based on its average health level and the degree of health level fluctuation within the target time range. Obtain the average number of failures and the degree of fluctuation in the number of failures for each target device within the target time range; The fault information of each target device is determined based on the average number of faults and the degree of fluctuation of the number of faults within the target time range.

[0007] Combining the first aspect and the above implementation methods, in some possible implementation methods, the average health level and health level fluctuation of each target device within the target time range are obtained, including: Obtain the health status of each target device at each unit of time within the target time range; The average health of each target device within the target time range is determined by averaging its health status at each unit of time within the target time range. The fluctuation of the health status of each target device within the target time range is calculated based on the health status of each target device per unit time and the average health status within the target time range. Obtain the average number of failures and the degree of fluctuation in the number of failures for each target device within the target time range, including: Obtain the number of faults for each target device per unit time within the target time range; The average number of failures for each target device within the target time range is determined by averaging the number of failures per unit time within the target time range. The fluctuation of the number of faults of each target device within the target time range is calculated based on the number of faults per unit time and the average number of faults within the target time range.

[0008] Combining the first aspect and the above implementation methods, in some possible implementation methods, the target ranking result is determined based on the health information and fault information of each target device within the target time range, including: The first health ranking result is determined based on the health information of each target device within the target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices. The first fault ranking result is determined based on the fault information of each target device within the target time range. The first fault ranking result is used to characterize the fault ranking of each target device among multiple target devices. The target ranking result is determined based on the first health ranking result and the first failure ranking result.

[0009] Combining the first aspect and the above implementation methods, in some possible implementation methods, the target ranking result is determined based on the health information and fault information of each target device within the target time range, including: Obtain the grouping information for each target device, which includes at least one of the device type and device batch. Multiple target devices are grouped according to the grouping information to obtain multiple device groups. Each device group includes at least one target device. The first health ranking result and the second health ranking result are determined based on the health information of each target device within the target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices, and the second health ranking result is used to characterize the health ranking of each device group among multiple device groups. The first fault ranking result and the second fault ranking result are determined based on the fault information of each target device within the target time range. The first fault ranking result is used to characterize the fault ranking of each target device among multiple target devices, and the second fault ranking result is used to characterize the fault ranking of each device group among multiple device groups. The target ranking result is determined based on the first health ranking result, the second health ranking result, the first fault ranking result, and the second fault ranking result.

[0010] Combining the first aspect and the above implementation methods, in some possible implementation methods, report information is generated based on the target ranking results, including: Acquire fault records for each target device within the target time range; Based on the fault records of each target device within the target time range, determine multiple fault causes, and the total number of faults for each fault cause among the multiple fault causes. Based on the total number of faults for each fault cause, the fault cause ranking result is determined. The fault cause ranking result is used to characterize the ranking of each fault cause among multiple fault causes. The report information is generated based on the target ranking results and the fault cause ranking results.

[0011] Secondly, embodiments of this application provide a report information generation apparatus, including: The first determining module is used to determine multiple target devices corresponding to the report information generation instruction in response to the report information generation instruction; The acquisition module is used to acquire health and fault information of each of the multiple target devices within a target time range. The second determining module is used to determine the target ranking result based on the health information and fault information of each target device within the target time range. The target ranking result is used to characterize the ranking of the target devices. The generation module is used to generate report information based on the target ranking results.

[0012] Thirdly, embodiments of this application provide an electronic device, including a processor and a memory storing a computer program, wherein the processor executes the program to implement the steps of the report information generation method of the first aspect.

[0013] Fourthly, embodiments of this application provide a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the first aspect of the report information generation method.

[0014] Fifthly, embodiments of this application provide a computer program product, including a computer program, which, when executed by a processor, implements the steps of the first aspect report information generation method.

[0015] The report information generation method, apparatus, device, and medium provided in this application first respond to a report information generation instruction and determine multiple target devices corresponding to the instruction; then, they acquire health and fault information of each target device within a target time range; next, based on the health and fault information of each target device within the target time range, they determine a target ranking result, which characterizes the ranking of the target devices; finally, they generate report information based on the target ranking result. These steps, by integrating device screening, data acquisition, multi-dimensional ranking, and report generation, achieve automated processing from instruction to report, avoiding the subjectivity and inefficiency of manual data screening and organization. Simultaneously, through comprehensive analysis and ranking of health and fault information, the relative advantages and disadvantages and potential risks of device operating status can be revealed, providing a basis for decision-making in device maintenance and management, thereby improving the reliability of the final generated report information. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the report information generation method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the process for determining the target device provided in an embodiment of this application; Figure 3 This is a schematic diagram of the process for obtaining health information and fault information provided in an embodiment of this application; Figure 4 This is a schematic diagram of the process for obtaining average information and fluctuation level provided in an embodiment of this application; Figure 5 This is a flowchart illustrating a method for determining a target ranking result provided in an embodiment of this application; Figure 6 This is another flowchart illustrating the process of determining the target ranking result provided in an embodiment of this application; Figure 7 This is a schematic diagram of the process for generating report information provided in an embodiment of this application; Figure 8 This is a schematic diagram of the overall process of the report information generation method provided in the embodiments of this application; Figure 9 This is a schematic diagram of the structure of the report information generation device provided in the embodiments of this application; Figure 10 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0019] In scenarios such as rail transit, there are numerous pieces of equipment requiring maintenance and management. Obtaining the necessary reports for equipment maintenance and management in advance helps relevant personnel develop maintenance strategies and optimize resource allocation. For example, signaling equipment, as a critical component of the rail transit system, directly impacts train safety and efficiency with its operational status.

[0020] However, due to the complex and ever-changing nature of equipment operation, if the final report information fails to present sufficiently comprehensive and effective content, it will be difficult to accurately reflect the overall condition and potential risks of the equipment, and will not be able to provide a reliable basis for equipment maintenance and management decisions.

[0021] In some related technologies, a method for generating equipment status reports based on a single type of operating parameter (such as equipment temperature only or equipment current only) has been proposed for rail transit scenarios. This method collects specific types of operating parameters and compares them with preset thresholds to determine whether there is an abnormality in the equipment, and uses the judgment result as report information.

[0022] In some related technologies, a method for statistical analysis of equipment status based on a fixed period has been proposed. This method summarizes the running time or number of on / off cycles of the equipment at preset time intervals (e.g., weekly or monthly) and uses the summary results as report information.

[0023] It is evident that the aforementioned technologies typically focus on a single dimension or static indicator of equipment operating status, lacking comprehensive analysis of multi-dimensional dynamic changes in equipment operating status. This results in generated reports that fail to fully and accurately reflect the overall condition and potential risks of the equipment. Therefore, improving the reliability of reports required for equipment maintenance and management has become an urgent technical problem to be solved.

[0024] To address the aforementioned issues, the solution provided in this application mainly includes: first, responding to a report information generation instruction, identifying multiple target devices corresponding to the instruction; then, acquiring the health and fault information of each target device within a target time range; next, determining a target ranking result based on the health and fault information of each target device within the target time range, whereby the target ranking result characterizes the ranking of the target devices; and finally, generating report information based on the target ranking result. These steps, by integrating device screening, data acquisition, multi-dimensional ranking, and report generation, achieve automated processing from instruction to report, avoiding the subjectivity and inefficiency of manual data screening and organization. Simultaneously, through comprehensive analysis and ranking of health and fault information, the relative advantages and disadvantages of device operating status and potential risks can be revealed, providing a basis for decision-making in device maintenance and management, thereby improving the reliability of the final generated report information.

[0025] More specifically, for rail transit scenarios, by responding to report information generation instructions and identifying multiple target devices corresponding to those instructions, precise analysis of signaling equipment on specific lines or stations can be performed. Health and fault information for each target device within a target time range can be obtained, reflecting changes in the device's status during continuous operation. Based on this information, a target ranking result can be determined, identifying critical equipment with low health or high failure rates. Finally, a report is generated based on the target ranking result, providing data support for preventative maintenance and resource allocation of rail transit equipment, thereby helping to improve the reliability of the signaling system and train safety.

[0026] The report information generation method provided in the embodiments of this application will be described in detail below.

[0027] Please see Figure 1 , Figure 1 This is a flowchart illustrating a report information generation method provided in an embodiment of this application. Figure 1 As shown, the method in this application embodiment may include the following steps S101-S104.

[0028] S101, in response to the report information generation command, determines the multiple target devices corresponding to the report information generation command.

[0029] Specifically, considering that equipment management decisions need to be analyzed for a specific range or type of equipment, this embodiment proposes a method for triggering and determining the target set of equipment through instructions.

[0030] First, in response to the report information generation command, multiple target devices corresponding to the report information generation command are identified. The report information generation command refers to a command triggered by the user through the operation interface or automatically initiated by the system at a preset cycle to start the report generation process; the target devices refer to the set of devices specified by the report information generation command that will be used as objects for subsequent data analysis. Regarding the generation of report information commands, in some possible implementations, the command can be triggered by the user selecting filter criteria through a graphical user interface and clicking the generate button. In other possible implementations, the command can be automatically generated by the system according to a preset schedule.

[0031] Regarding the steps for determining multiple target devices corresponding to the report information generation instruction, in some possible implementations, devices matching the filtering criteria carried in the report information generation instruction can be queried from a device database and identified as target devices. In other possible implementations, a device identifier list sent by an external system can be received, and the devices in the list can be identified as target devices.

[0032] S102, acquire the health information and fault information of each of the multiple target devices within the target time range.

[0033] Specifically, to comprehensively assess the operational status of the target devices, it is necessary to acquire the health and fault information of each of the multiple target devices within a target time range. The target time range refers to the time interval upon which data statistics and analysis are based. In some cases, the target time range is determined based on report generation instructions, such as those including user-specified start and end times. In other cases, the target time range is preset, such as the system default setting to the most recent month or quarter. Furthermore, the health information of the target devices within the target time range refers to quantitative or qualitative data characterizing the reliability and performance status of the target devices within that range. The fault information of the target devices within the target time range refers to data characterizing abnormal or failure events that occurred within the target devices during that range.

[0034] Regarding this step, in some possible implementations, the raw operating data records of each target device within the target time range can be read from a preset historical database or real-time monitoring database, and these raw operating data records can be processed to obtain health and fault information. In some possible implementations, a dedicated data acquisition service interface can be called to directly obtain the pre-processed health and fault information of each target device within the target time range.

[0035] S103, based on the health information and fault information of each target device within the target time range, determine the target ranking result, which is used to characterize the ranking of the target devices.

[0036] Specifically, in order to identify the devices requiring focused attention or priority from among numerous target devices, it is necessary to determine the target ranking results based on the health and fault information of each target device within the target time range. The target ranking results characterize the ranking of the target devices. Specifically, the target ranking results characterize the ranking of the target devices by sequentially arranging them according to the quality or risk level reflected by their health and fault information using a sorting algorithm.

[0037] Regarding this step, some possible implementations involve generating independent ranking sequences based on health information and fault information separately, then combining or weighting these ranking sequences, and using the result of the combination or weighting calculation as the target ranking result. Other possible implementations involve first normalizing the health information and fault information, then performing a comprehensive score based on the normalized values, and finally determining the target ranking result based on the comprehensive score.

[0038] S104: Generate report information based on the target ranking results.

[0039] Specifically, in order to present the analysis results to users in a readable format, it is necessary to generate report information based on the target ranking results. This report information refers to a structured document or data set that contains the target ranking results and is used to assist in equipment management decisions.

[0040] Regarding this step, some possible implementations involve directly populating a predefined document template with the target ranking results to generate a report containing text and tables. Other possible implementations include adding charts or textual analysis conclusions to the target ranking results to generate a report with charts and conclusive descriptions.

[0041] In this embodiment, firstly, in response to a report information generation command, multiple target devices corresponding to the command are identified; then, health and fault information of each target device within a target time range are acquired; next, based on the health and fault information of each target device within the target time range, a target ranking result is determined, which characterizes the ranking of the target devices; finally, a report is generated based on the target ranking result. These steps, by integrating device screening, data acquisition, multi-dimensional ranking, and report generation, achieve automated processing from command to report, avoiding the subjectivity and inefficiency of manual data screening and organization. Simultaneously, through comprehensive analysis and ranking of health and fault information, the relative advantages and disadvantages of device operating status and potential risks can be revealed, providing a basis for decision-making in device maintenance and management, thereby improving the reliability of the final generated report information.

[0042] Please see Figure 2 This application provides a flowchart for determining a target device, as shown in the following embodiment. Figure 2 As shown, the method of this application embodiment may include the following steps S201-S202. Steps S201-S202 can be used as a further refinement of the above-mentioned step of "determining multiple target devices corresponding to the report information generation instruction in response to the report information generation instruction".

[0043] S201, in response to the report information generation instruction, determine the filtering conditions according to the report information generation instruction, the filtering conditions including at least one of location information, subsystem information and time information; S202: From the preset device library, determine multiple devices that meet the filtering conditions as the target devices corresponding to the report information generation instruction.

[0044] Specifically, considering that equipment management decisions usually require analysis of equipment in specific geographical locations, specific functional modules, or specific time periods, this embodiment proposes a method for accurately determining the target equipment set through screening conditions.

[0045] First, in response to the report information generation instruction, the filtering conditions are determined according to the instruction. The filtering conditions include at least one of location information, subsystem information, and time information. Here, filtering conditions refer to a set of parameters used to limit the scope of the equipment; these can be user-input queries or system-preset default conditions. Location information refers to data used to identify the physical installation location of the equipment, such as line or station identifiers. Subsystem information refers to data used to identify the functional module to which the equipment belongs. Time information refers to time period data used to limit the scope of data statistics. Regarding this step, in some possible implementations, the parameters carried in the report information generation command can be parsed, and the parsed parameters can be used as filtering conditions. In other possible implementations, predefined parameters can be read from the configuration file associated with the report information generation command, and the read parameters can be used as filtering conditions.

[0046] Furthermore, from a pre-defined device library, multiple devices that meet the filtering criteria are identified as the target devices corresponding to the report information generation instruction. The device library refers to a database that stores the basic attribute information of all managed devices.

[0047] Regarding this step, in some possible implementations, a database query operation can be performed to retrieve device identifiers from the device database that match the location information, subsystem information, and time information in the filtering criteria, and then the devices corresponding to the retrieved device identifiers can be identified as devices that meet the filtering criteria.

[0048] In this embodiment, the filtering conditions are determined by parsing instructions or reading configuration, and the target devices are queried from the device library based on the filtering conditions. This achieves automated and accurate determination of the target device range, providing an accurate data foundation for subsequent data analysis.

[0049] Please see Figure 3 This application provides a flowchart illustrating the process of obtaining health information and fault information, as shown in the embodiments of this application. Figure 3 As shown, the method of this application embodiment may include the following steps S301-S304, which can be used as a further refinement of the above-mentioned step of "obtaining health information and fault information of each of the multiple target devices within a target time range".

[0050] S301, Obtain the average health level and health level fluctuation of each target device within the target time range; S302, determine the health information of each target device based on the average health level and the degree of health level fluctuation of each target device within the target time range; S303, obtain the average number of faults and the degree of fluctuation in the number of faults for each target device within the target time range; S304. Determine the fault information of each target device based on the average number of faults and the degree of fluctuation of the number of faults within the target time range.

[0051] Specifically, considering that the health status of a device is reflected not only in its average performance level but also in the stability of its performance, this embodiment proposes a method to comprehensively characterize device health information and fault information by combining the average level and the degree of fluctuation.

[0052] To quantitatively assess the overall health level and stability of each target device within the target time range, it is necessary to obtain the average health level and the degree of health fluctuation for each target device within the target time range. The average health level of the target device within the target time range refers to a statistically calculated value representing the average health status of the target device within the target time range; the degree of health fluctuation of the target device within the target time range refers to a statistically calculated value representing the magnitude of change in the health status of the target device within the target time range.

[0053] Regarding this step, in some possible implementations, the health status sample values ​​of each target device at multiple time points within the target time range can be obtained, and the arithmetic mean of these health status sample values ​​can be calculated. The result can be used as the average health status of the target device within the target time range. At the same time, the variance or standard deviation of these health status sample values ​​can be calculated, and the variance or standard deviation can be used as the degree of health status fluctuation of the target device within the target time range.

[0054] In order to form a comprehensive description of the health status of each target device, it is necessary to determine the health information of each target device based on its average health level and the degree of health level fluctuation within the target time range.

[0055] Regarding this step, in some possible implementations, the average health level and the degree of health level fluctuation of each target device within the target time range can be combined into a data structure containing multiple fields, and this data structure can be used as the health information of the target device.

[0056] To quantitatively assess the failure frequency and fluctuation of each target device within a target time period, it is necessary to obtain the average number of failures and the degree of fluctuation in the number of failures for each target device within the target time period. The average number of failures for each target device within the target time period refers to a statistically calculated value representing the average level of failure frequency for that target device within the target time period; the degree of fluctuation in the number of failures for each target device within the target time period refers to a statistically calculated value representing the magnitude of change in the failure frequency for that target device within the target time period.

[0057] Regarding this step, in some possible implementations, the number of failures of each target device in multiple sub-time periods within the target time range can be counted, and the arithmetic mean of these failure numbers can be calculated. The result can be used as the average number of failures of the target device within the target time range. At the same time, the variance or standard deviation can be calculated based on the number of failures in these sub-time periods, and the variance or standard deviation can be used as the degree of fluctuation of the number of failures of the target device within the target time range.

[0058] In order to form a comprehensive description of the fault status of each target device, it is necessary to determine the fault information of each target device based on the average number of faults and the degree of fluctuation of the number of faults within the target time range.

[0059] Regarding this step, in some possible implementations, the average number of faults and the degree of fluctuation of the number of faults for each target device within the target time range can be combined into a data structure containing multiple fields, and this data structure can be used as the fault information of the target device.

[0060] In this embodiment, by acquiring and combining the average health level and the degree of health level fluctuation, and the average number of faults and the degree of fault number fluctuation, the operating status of the equipment can be more comprehensively depicted from both static and dynamic dimensions, laying the foundation for generating more information-deep target ranking results in the future.

[0061] Please see Figure 4 This application provides a flowchart illustrating the process of obtaining average information and fluctuation levels in an embodiment of the present application. Figure 4 As shown, the method of this application embodiment may include the following steps S401-S406. Steps S401-S403 can be used as a further refinement of the above-mentioned step of "obtaining the average health status and the degree of health status fluctuation of each target device within the target time range". Steps S404-S406 can be used as a further refinement of the above-mentioned step of "obtaining the average number of faults and the degree of fault number fluctuation of each target device within the target time range".

[0062] S401, obtain the health status of each target device at each unit of time within the target time range; S402, calculate the average health of each target device within the target time range by averaging the health of each target device within each unit of time within the target time range; S403, calculate the fluctuation of the health status of each target device within the target time range based on the health status of each target device per unit time and the average health status within the target time range, and obtain the degree of health status fluctuation of each target device within the target time range. S404, obtain the number of faults of each target device per unit time within the target time range; S405, calculate the average number of failures of each target device within the target time range by averaging the number of failures per unit time within the target time range. S406, calculate the fluctuation of the number of faults of each target device within the target time range based on the number of faults per unit time and the average number of faults within the target time range, and obtain the degree of fluctuation of the number of faults of each target device within the target time range.

[0063] Specifically, considering that the operating status of equipment changes dynamically over time, relying solely on data from a single moment or simple total statistics is insufficient to accurately reflect the overall performance and stability of the equipment within a target time range. This embodiment proposes a method to quantify the equipment status by calculating the average value and fluctuation level of data at a unit time granularity.

[0064] On the one hand, in order to obtain fine-grained data for calculating the average health level and the degree of health level fluctuation, it is necessary to obtain the health level of each target device for each unit of time within the target time range. Here, unit of time refers to the minimum time interval used for data statistics and calculation, which can be expressed as a calendar day, an hour, or other preset time period; the health level of the target device for each unit of time within the target time range refers to the quantitative value obtained through data collection and processing, which is used to characterize the operational reliability and performance status of the target device within the corresponding unit of time.

[0065] Regarding this step, in some possible implementations, the health record of each target device corresponding to each unit of time within the target time range can be read sequentially from a pre-set time-series database. In other possible implementations, a real-time data interface can be called to obtain the raw operating data stream of each target device within the target time range, and the raw operating data stream can be aggregated and calculated on a unit-time basis. The value obtained from the aggregated calculation can then be used as the health of the target device for each unit of time within the target time range.

[0066] Furthermore, the average health of each target device within the target time range is determined by averaging the health of each target device per unit time within the target time range.

[0067] Regarding this step, in some possible implementations, the health values ​​of each target device over all unit times within the target time range can be summed, and the summation result can be divided by the total number of unit times. The calculated quotient is then used as the average health value of each target device within the target time range.

[0068] Furthermore, based on the health status and average health status of each target device within the target time range for each unit of time, fluctuation calculations are performed to obtain the degree of health fluctuation of each target device within the target time range. Here, fluctuation calculation refers to the mathematical operation process used to quantify the degree of dispersion of a set of data relative to its central value (such as the average value).

[0069] Regarding this step, in some possible implementations, the sum of squared differences between the health status of each target device per unit time within the target time range and the average health status of that target device within the target time range can be calculated. This sum of squared differences can then be divided by the total number of units of time, and the quotient obtained is determined as the health status fluctuation (i.e., variance) of each target device within the target time range. In some possible implementations, the square root of the calculated health status fluctuation (variance) can be taken, and the result of the square root operation is determined as another form of health status fluctuation (i.e., standard deviation).

[0070] On the other hand, in order to obtain fine-grained data for calculating the average number of failures and the degree of fluctuation in the number of failures, it is necessary to obtain the number of failures of each target device per unit time within the target time range. Here, the number of failures of the target device per unit time within the target time range refers to the total number of abnormal or failure events that occur in the target device within the corresponding unit time, obtained through statistics.

[0071] Regarding this step, some possible implementations include querying the fault event log database to count the number of fault events recorded by each target device within each unit of time within the target time range, and using the counted number of fault events as the number of faults of the target device within each unit of time within the target time range. Another possible implementation involves receiving real-time alarm streams from the device monitoring system, grouping and counting these alarm streams by target device and unit of time, and using the grouped counts as the number of faults of the target device within each unit of time within the target time range.

[0072] Furthermore, the average number of failures for each target device within the target time range is determined by averaging the number of failures per unit time for each target device within the target time range.

[0073] Regarding this step, in some possible implementations, the number of faults for each target device within the target time range can be summed, and the summation result can be divided by the total number of faults per unit time. The calculated quotient is then determined as the average number of faults for each target device within the target time range.

[0074] Furthermore, based on the number of failures and the average number of failures for each target device within the target time range, fluctuation calculations are performed to obtain the degree of fluctuation in the number of failures for each target device within the target time range.

[0075] Regarding this step, in some possible implementations, the sum of squared differences between the number of failures per unit time for each target device within the target time range and the average number of failures for that target device within the target time range can be calculated. This sum of squared differences can then be divided by the total number of failures per unit time, and the resulting quotient can be used to determine the degree of fluctuation (i.e., variance) in the number of failures for each target device within the target time range. In some possible implementations, the square root of the calculated degree of fluctuation (variance) can be taken, and the result of the square root operation can be used to determine another form of degree of fluctuation (i.e., standard deviation).

[0076] For example, the calculation of the degree of health fluctuation and the degree of fluctuation of the number of failures can be based on the variance formula. Specifically, the formula for calculating the degree of health fluctuation is: ; in, This indicates the degree of fluctuation in the stated health status. This indicates that the target device is within the target time range. Health status per unit of time, This represents the average health status of the target device within the target time range. This represents the total number of unit times within the target time range. Similarly, the formula for calculating the degree of fluctuation in the number of faults is: ; in, This indicates the degree of fluctuation in the number of faults. This indicates that the target device is within the target time range. Number of faults per unit time This represents the average number of failures of the target device within the target time range. This represents the total number of unit times within the target time range. The larger the fluctuation value calculated by the above formula, the more drastic the fluctuation in the status or failure of the corresponding equipment within the target time range.

[0077] In this embodiment, by obtaining the health status and number of faults at the unit time granularity, and calculating the average value and fluctuation level accordingly, the operating status of the equipment within the target time range can be more accurately quantified from the two dimensions of central tendency and dispersion, providing a reliable data foundation for subsequent accurate equipment ranking.

[0078] Please see Figure 5 This application provides a flowchart illustrating the process of determining a target ranking result, as shown in the embodiments below. Figure 5As shown, the method of this application embodiment may include the following steps S501-S503, which can be used as a further refinement of the above-mentioned step of "determining the target ranking result based on the health information and fault information of each target device within the target time range".

[0079] S501, determine the first health ranking result based on the health information of each target device within the target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices. S502, determine the first fault ranking result based on the fault information of each target device within the target time range. The first fault ranking result is used to characterize the fault ranking of each target device among multiple target devices. S503, determine the target ranking result based on the first health ranking result and the first fault ranking result.

[0080] Specifically, considering that the assessment of equipment operating status requires a comprehensive consideration of its health status and fault conditions, this embodiment proposes a method for ranking based on health information and fault information respectively, and then combining them to obtain the final target ranking result.

[0081] On the one hand, in order to evaluate the relative performance of each target device among multiple target devices from the perspective of health status, it is necessary to determine a first health ranking result based on the health information of each target device within a target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices. Specifically, the first health ranking result can be represented as an ordered list, in which the target devices are sorted according to the quality of their health status as reflected by their health information.

[0082] Regarding this step, in some possible implementations, the average health value of each target device in the health information within the target time range can be extracted, and all target devices can be sorted according to the magnitude of the average health value. The sorted ordered list can then be used as the first health ranking result.

[0083] On the other hand, in order to evaluate the relative performance of each target device among multiple target devices from the perspective of fault conditions, it is necessary to determine a first fault ranking result based on the fault information of each target device within the target time range. The first fault ranking result is used to characterize the fault ranking of each target device among multiple target devices. The first fault ranking result can be represented as an ordered list, in which the target devices are sorted according to the frequency of fault occurrence reflected by their fault information.

[0084] Regarding this step, in some possible implementations, the average number of faults in the fault information of each target device within the target time range can be extracted, and all target devices can be sorted according to the magnitude of the average number of faults. The sorted list can then be used as the first fault ranking result.

[0085] Finally, the target ranking result is determined based on the first health ranking result and the first failure ranking result.

[0086] Regarding this step, in some possible implementations, the first health ranking result and the first fault ranking result can be directly combined into the target ranking result. In some possible implementations, the ranking number of each target device in the first health ranking result and the ranking number of the corresponding target device in the first fault ranking result can be weighted and summed. Based on the comprehensive score obtained by the weighted summation, all target devices are re-sorted, and the ordered list obtained after re-sorting is used as the target ranking result.

[0087] Understandably, since the target ranking result is a combination of the first health ranking result and the first fault ranking result, the target ranking result can reflect the comprehensive performance of the target equipment in both health status and fault status.

[0088] In this embodiment, by determining the first health ranking result and the first fault ranking result respectively, and then comprehensively determining the target ranking result based on these results, the operating status of the target device can be relatively evaluated from multiple dimensions. This helps to identify target devices with excellent overall performance or potential risks, thereby enhancing the comprehensiveness and decision support value of the target ranking result.

[0089] Please see Figure 6 This document provides a flowchart illustrating the target ranking result in an embodiment of this application. Figure 6 As shown, the method of this application embodiment may include the following steps S601-S605. Steps S601-S605 can be used as a further refinement of the above-mentioned step of "determining the target ranking result based on the health information and fault information of each target device within the target time range".

[0090] S601, Obtain grouping information for each target device, the grouping information including at least one of device type and device batch; S602, group multiple target devices according to the grouping information to obtain multiple device groups, and each device group includes at least one target device; S603, determine a first health ranking result and a second health ranking result based on the health information of each target device within the target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices, and the second health ranking result is used to characterize the health ranking of each device group among multiple device groups. S604, determine a first fault ranking result and a second fault ranking result based on the fault information of each target device within the target time range. The first fault ranking result is used to characterize the fault ranking of each target device among multiple target devices, and the second fault ranking result is used to characterize the fault ranking of each device group among multiple device groups. S605, determine the target ranking result based on the first health ranking result, the second health ranking result, the first fault ranking result, and the second fault ranking result.

[0091] Specifically, considering that equipment management decisions need to focus not only on the performance of individual devices, but also on macroscopic analysis from the perspective of equipment groups (such as groups divided according to specific attributes), this embodiment proposes a method to obtain ranking results at different granularities by grouping devices.

[0092] First, to group the target devices to support subsequent group analysis, it is necessary to obtain grouping information for each target device. Grouping information includes at least one of the following: device type and device batch. Specifically, grouping information refers to attribute data used to classify the target devices; device type refers to data used to identify the technical specifications or model category followed by the device; and device batch refers to data used to identify the batch number of the device during production or deployment. Regarding this step, in some possible implementations, the device type identifier and device batch identifier corresponding to each target device can be read from a preset device attribute database, and the read device type identifier and device batch identifier can be used as grouping information.

[0093] To group target devices with the same or similar attributes for statistical analysis at the group level, it is necessary to group multiple target devices according to grouping information, resulting in multiple device groups. Each device group includes at least one target device. A device group refers to a set containing one or more target devices, obtained by dividing the data according to grouping information. It can be represented as a list of device identifiers or a set of devices with common grouping attribute values. Regarding this step, in some possible implementations, multiple target devices can be traversed, and target devices with the same device type identifier can be grouped into the same device group, thereby obtaining multiple device groups divided by device type.

[0094] Furthermore, in order to assess the health status of devices at both the individual and group levels, it is necessary to determine a first health ranking result and a second health ranking result based on the health information of each target device within the target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices, and the second health ranking result is used to characterize the health ranking of each device group among multiple device groups.

[0095] The first health ranking result can be represented as an ordered list, in which the target devices are sorted according to the quality of their health status as reflected by their health information. The second health ranking result can also be represented as an ordered list, in which the device groups are sorted according to the quality of their health status calculated by comprehensively analyzing the health information of all the target devices included in each group.

[0096] Regarding this step, in some possible implementations, the average health value of each target device within the target time range can be extracted, and all target devices can be sorted according to the magnitude of the average health value. The sorted ordered list can be used as the first health ranking result. At the same time, for each device group, the average of the average health values ​​of all target devices in the device group can be calculated, and all device groups can be sorted according to the magnitude of the average value. The sorted ordered list can be used as the second health ranking result.

[0097] Furthermore, in order to assess the failure status of equipment at both the individual and group levels, it is necessary to determine a first failure ranking result and a second failure ranking result based on the failure information of each target equipment within the target time range. The first failure ranking result is used to characterize the failure ranking of each target equipment among multiple target equipment, and the second failure ranking result is used to characterize the failure ranking of each equipment group among multiple equipment groups.

[0098] The first fault ranking result can be represented as an ordered list, in which the target devices are sorted according to the frequency of fault occurrence reflected by their fault information. The second fault ranking result can also be represented as an ordered list, in which the device groups are sorted according to the frequency of fault occurrence calculated by comprehensively analyzing the fault information of all the target devices included in the list.

[0099] Regarding this step, in some possible implementations, the average number of faults in the fault information of each target device within the target time range can be extracted, and all target devices can be sorted according to the magnitude of the average number of faults. The sorted ordered list can be used as the first fault ranking result. At the same time, for each device group, the sum or average value of the average number of faults of all target devices in the device group can be calculated, and all device groups can be sorted according to the magnitude of the sum or average value. The sorted ordered list can be used as the second fault ranking result.

[0100] Finally, in order to generate a final result that integrates ranking information at different granularities, the target ranking result needs to be determined based on the first health ranking result, the second health ranking result, the first fault ranking result, and the second fault ranking result.

[0101] Regarding this step, in some possible implementations, the first health ranking result, the second health ranking result, the first fault ranking result, and the second fault ranking result can be combined into a data structure containing multiple sub-ranking results, and this data structure can be used as the target ranking result.

[0102] Understandably, since the target ranking results combine individual-based ranking results and device group-based ranking results, the target ranking results can reflect the multi-level performance of the target devices in terms of both health status and failure status, from micro-individual to macro-group.

[0103] In this embodiment, by introducing equipment grouping and determining the health and failure ranking results at the individual and group levels respectively, a richer and more comprehensive analytical perspective can be provided for equipment management decisions, thereby enhancing the comprehensiveness of the target ranking results and their decision support value.

[0104] Please see Figure 7 This application provides a flowchart illustrating the process of generating report information, such as... Figure 7 As shown, the method of this application embodiment may include the following steps S701-S704, which can be used as a further refinement of the above-mentioned step of "generating report information based on the target ranking result".

[0105] S701, acquire the fault records of each target device within the target time range; S702, based on the fault records of each target device within the target time range, determine multiple fault causes, and the total number of faults for each fault cause among the multiple fault causes; S703, determine the ranking result of the fault causes based on the total number of faults for each fault cause. The ranking result of the fault causes is used to characterize the ranking of the number of each fault cause among multiple fault causes. S704 generates report information based on the target ranking results and the fault cause ranking results.

[0106] Specifically, considering that equipment management decisions not only require understanding the ranking of equipment, but also need to deeply analyze the root causes of equipment failures in order to formulate targeted maintenance strategies, this embodiment proposes a method to enrich the content of report information by analyzing the causes of failures.

[0107] First, it is necessary to obtain the fault records of each target device within the target time range. The fault records of the target device within the target time range refer to the raw data set used to record detailed information about every fault event that occurred on that target device within the target time range. Regarding this step, in some possible implementations, a preset fault event database can be queried to retrieve all fault event entries for each target device within the target time range, and the retrieved set of fault event entries can be used as the fault record for each target device within the target time range.

[0108] To extract statistically significant fault cause distribution information from fault records, it is necessary to determine multiple fault causes and the total number of faults for each fault cause based on the fault records of each target device within the target time range. Here, a fault cause refers to the type code or descriptive information used to identify the root cause of a fault event; it can be represented as a predefined fault code or text description. The total number of faults for a fault cause refers to the sum of the occurrences of all fault events belonging to the same fault cause within the target time range. Regarding this step, in some possible implementations, each fault event entry in the fault records of each target device within the target time range can be parsed, and the fault cause field recorded therein can be extracted; all extracted fault causes can be classified to obtain multiple distinct fault causes; then, the total number of fault event entries belonging to each fault cause can be counted, and the total number obtained can be used as the total number of faults for that fault cause.

[0109] Furthermore, to identify the most significant causes of failure, a ranking of failure causes needs to be determined based on the total number of failures for each cause. This ranking represents the numerical ranking of each failure cause among multiple failure causes. The ranking can be represented as an ordered list, where failure causes are sorted according to their total number of failures. Regarding this step, in some possible implementations, all fault causes can be sorted in descending or ascending order according to the total number of faults for each fault cause, and the resulting ordered list can be used as the ranking result of the fault causes.

[0110] Finally, in order to generate a comprehensive report that includes overall equipment ranking information and root cause analysis of failures, report information needs to be generated based on the target ranking results and the failure cause ranking results.

[0111] Regarding this step, in some possible implementations, the target ranking results and the failure cause ranking results can be used as data sources to populate a predefined report template, generating report information containing text, tables, or charts.

[0112] Understandably, because the report information integrates the relative quality of equipment status reflected in the target ranking results and the distribution of fault root causes reflected in the fault cause ranking results, the report information can reflect the overall performance of equipment operation and the main reasons behind it, thus providing a more comprehensive basis for making accurate equipment maintenance and management decisions.

[0113] In this embodiment, by introducing fault cause analysis and generating fault cause ranking results, and using them together with the target ranking results to generate report information, the reliability of the report information is enhanced.

[0114] In one embodiment, please refer to Figure 8 , Figure 8 This is a schematic diagram of the overall process of the report information generation method provided in the embodiments of this application.

[0115] Specifically, Figure 8 This paper comprehensively illustrates the main flow of the report information generation method provided in the embodiments of this application. The method begins in response to a report information generation instruction. Specifically, the report information generation instruction can be actively triggered by the user through the operation interface, or it can be automatically generated by the system according to a preset time period. In response to this instruction, filtering conditions are determined based on the report information generation instruction. The filtering conditions are used to precisely define the scope of the equipment to be analyzed, and may include at least one of location information, subsystem information, and time information. Location information may be, for example, a rail transit line number or a specific station identifier; subsystem information may be, for example, a classification identifier for equipment functional modules such as a signaling system or a power system; and time information is used to specify the target time range for data analysis.

[0116] Next, based on the established filtering criteria, multiple devices that meet the criteria are queried from the preset device database and selected as the target devices for this report generation process. The device database stores the basic attribute information of all managed devices. By performing database queries, target devices located in specific locations, belonging to specific subsystems, or active within specific time periods can be accurately filtered out.

[0117] After determining the target device set, the process enters the data acquisition phase, which involves acquiring the health and fault information of each target device within a target time range. Health information characterizes the operational reliability and performance status of the devices and can be obtained by calculating the average health level and health level fluctuation of the target devices within the target time range. Fault information characterizes the occurrence of abnormal or failure events in the devices and can be obtained by calculating the average number of faults and the fluctuation of the number of faults of the target devices within the target time range. To obtain this information, it is necessary to first acquire the health level sample value and fault count statistics for each target device at each unit of time (e.g., daily or hourly) within the target time range, and then calculate the average value and fluctuation (e.g., variance or standard deviation) for each.

[0118] Subsequently, the process enters the ranking result determination stage. Based on the acquired health information, a first health ranking result is determined. The first health ranking result is used to characterize the relative superiority or inferiority of each target device among all target devices based on its health status. For example, it can be obtained by sorting the target devices in descending order based on their average health score. Simultaneously, based on the acquired fault information, a first fault ranking result is determined. The first fault ranking result is used to characterize the relative ranking of each target device among all target devices based on its fault occurrence frequency. For example, it can be obtained by sorting the target devices in ascending order based on their average number of faults (fewer faults, higher ranking).

[0119] Then, based on the obtained first health ranking and first failure ranking results, the final target ranking result is determined comprehensively. This target ranking result comprehensively reflects the overall performance of the target equipment in both health status and failure status dimensions. One implementation method is to take a weighted sum of the ranking numbers of each equipment in the first health ranking and first failure ranking results, and then re-sort them according to the comprehensive score.

[0120] To further enrich the report content, the process continues to obtain detailed fault records for each target device within the target time frame. These fault records contain specific information about each fault event. Based on these records, a ranking of fault causes is determined. Specifically, this includes: extracting and categorizing multiple different fault causes from the fault records; calculating the total number of faults occurring for each cause across all target devices within the target time frame; and then ranking each fault cause according to the total number of faults to generate a fault cause ranking. This result reveals the distribution of the main root causes leading to device failures.

[0121] Finally, based on the determined target ranking results and the ranking results of the causes of failures, the final report information is generated. The report information can be a structured document formed by filling these ranking results, relevant statistical data, and possible visualization charts into a preset template, providing a comprehensive and reliable basis for equipment maintenance and management decisions. The entire process effectively improves the reliability of the report information through automated processing and multi-dimensional analysis.

[0122] Regarding the application of this embodiment in a rail transit scenario, signaling equipment can be used as the target device for specific explanation. Signaling equipment is a key device in the rail transit system used to control train intervals and ensure train operation safety; its reliability is related to the efficiency and safety of the entire transportation system. In this scenario, the report information generation instruction may be issued by the dispatch center operator for a specific line or a specific batch of signaling equipment. For example, the location information in the instruction's filtering conditions can be specified as "Metro Line 1," the subsystem information can be specified as "Automatic Train Supervision (ATS)," and the time information can be set to "the previous quarter."

[0123] In response to the report generation command, the system, based on filtering criteria, identifies all signaling equipment located on Metro Line 1, belonging to the Automatic Train Control (ATS) subsystem, and with operational records in the previous quarter from a database containing information on all signaling equipment along the entire line. Subsequently, it retrieves the health and fault information of these target signaling equipment from the previous quarter. The calculation of health information relies on monitoring data of key operating parameters of the signaling equipment, calculating daily health sampling values ​​and further deriving the average health level and its fluctuation. Fault information is calculated by statistically analyzing the number of various alarm events recorded by the signaling equipment, calculating the average number of faults and the fluctuation of the number of faults.

[0124] Based on the acquired health and fault information, the system begins to determine the ranking results. First, a first health ranking result is generated based on the average health of each target signaling device, identifying the signaling devices with the best and worst health status. Simultaneously, a first fault ranking result is generated based on the average number of faults for each target signaling device, identifying the signaling devices with the lowest and highest fault rates. Next, the first health ranking result and the first fault ranking result are combined and weighted to generate the final target ranking result, which reflects the overall performance of the signaling devices in terms of reliability and stability.

[0125] To analyze the root causes of the faults, the system further obtains detailed fault records for each target signaling device in the previous quarter. By categorizing and analyzing these records, the main causes of faults can be identified, such as "communication module malfunction," "external electromagnetic interference," and "software logic errors." The system also counts the total number of occurrences for each fault cause, thereby generating a ranking of fault causes. Finally, the system integrates the target ranking results with the fault cause ranking results to generate a comprehensive report on the signaling equipment of the ATS system on Metro Line 1.

[0126] This embodiment offers a solution that differs from typical industrial equipment management in the rail transit scenario. First, due to the high safety and real-time requirements of rail transit signaling equipment, the operational parameters and their fluctuations upon which its health assessment relies are crucial. This embodiment, by calculating the degree of health fluctuation, can capture the degradation trend of signaling equipment performance and provide early warnings. Second, rail transit signaling systems have standardized equipment and strong batch characteristics. This embodiment supports grouping and ranking by equipment type and batch, enabling the identification of common problems for a specific model or batch of signaling equipment at the group level, providing a basis for batch maintenance or recall decisions. Finally, by ranking and analyzing the causes of failures, the most frequent root causes of failures in the rail transit signaling system can be identified, facilitating the concentration of resources to address issues affecting system reliability.

[0127] The following will combine Figure 9 The report information generation apparatus 800 provided in this application embodiment will be described in detail. The report information generation apparatus 800 and the report information generation method described above can be referred to and correspond to each other. It should be noted that... Figure 9 The report information generation device 800 in the present application is used to perform the report information generation device 800. Figure 1 - Figure 8 The methods shown in the embodiments are illustrated for ease of explanation, showing only the parts relevant to the embodiments of this application. For specific technical details not disclosed, please refer to this application. Figure 1 - Figure 8 The illustrated embodiment. Specifically, the report information generation device 800 may include a first determining module 810, an acquisition module 820, a second determining module 830, and a generation module 840, as detailed below: The first determining module 810 is used to determine multiple target devices corresponding to the report information generation instruction in response to the report information generation instruction. The acquisition module 820 is used to acquire the health information and fault information of each of the multiple target devices within a target time range. The second determining module 830 is used to determine the target ranking result based on the health information and fault information of each target device within the target time range. The target ranking result is used to characterize the ranking of the target devices. The generation module 840 is used to generate report information based on the target ranking results.

[0128] Optionally, in some embodiments, the first determining module 810 is further configured to: In response to a report information generation instruction, the filtering criteria are determined based on the report information generation instruction. The filtering criteria include at least one of location information, subsystem information, and time information. From the preset device library, select multiple devices that meet the filtering criteria as the target devices corresponding to the report information generation instruction.

[0129] Optionally, in some embodiments, the acquisition module 820 is further configured to: Obtain the average health level and health level fluctuation of each target device within the target time range; The health information of each target device is determined based on its average health level and the degree of health level fluctuation within the target time range. Obtain the average number of failures and the degree of fluctuation in the number of failures for each target device within the target time range; The fault information of each target device is determined based on the average number of faults and the degree of fluctuation of the number of faults within the target time range.

[0130] Optionally, in some embodiments, the acquisition module 820 is further configured to: Obtain the health status of each target device at each unit of time within the target time range; The average health of each target device within the target time range is determined by averaging its health status at each unit of time within the target time range. The fluctuation of the health status of each target device within the target time range is calculated based on the health status of each target device per unit time and the average health status within the target time range. Optionally, in some embodiments, the acquisition module 820 is further configured to: Obtain the number of faults for each target device per unit time within the target time range; The average number of failures for each target device within the target time range is determined by averaging the number of failures per unit time within the target time range. The fluctuation of the number of faults of each target device within the target time range is calculated based on the number of faults per unit time and the average number of faults within the target time range.

[0131] Optionally, in some embodiments, the second determining module 830 is further configured to: The first health ranking result is determined based on the health information of each target device within the target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices. The first fault ranking result is determined based on the fault information of each target device within the target time range. The first fault ranking result is used to characterize the fault ranking of each target device among multiple target devices. The target ranking result is determined based on the first health ranking result and the first failure ranking result.

[0132] Optionally, in some embodiments, the second determining module 830 is further configured to: Obtain the grouping information for each target device, which includes at least one of the device type and device batch. Multiple target devices are grouped according to the grouping information to obtain multiple device groups. Each device group includes at least one target device. The first health ranking result and the second health ranking result are determined based on the health information of each target device within the target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices, and the second health ranking result is used to characterize the health ranking of each device group among multiple device groups. The first fault ranking result and the second fault ranking result are determined based on the fault information of each target device within the target time range. The first fault ranking result is used to characterize the fault ranking of each target device among multiple target devices, and the second fault ranking result is used to characterize the fault ranking of each device group among multiple device groups. The target ranking result is determined based on the first health ranking result, the second health ranking result, the first fault ranking result, and the second fault ranking result.

[0133] Optionally, in some embodiments, the generation module 840 is further configured to: Acquire fault records for each target device within the target time range; Based on the fault records of each target device within the target time range, determine multiple fault causes, and the total number of faults for each fault cause among the multiple fault causes. Based on the total number of faults for each fault cause, the fault cause ranking result is determined. The fault cause ranking result is used to characterize the ranking of each fault cause among multiple fault causes. The report information is generated based on the target ranking results and the fault cause ranking results.

[0134] The effects achievable in this embodiment can be found in the relevant embodiments of the above-mentioned report information generation method, and will not be repeated here.

[0135] Figure 10 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 10 As shown, the electronic device may include: a processor 1301, a communication interface 1302, a memory 1303, and a communication bus 1304, wherein the processor 1301, the communication interface 1302, and the memory 1303 communicate with each other via the communication bus 1304. The processor 1301 can call a computer program stored in the memory 1303 to execute the steps of a report information generation method, such as including: In response to a report information generation command, identify multiple target devices corresponding to the report information generation command; Acquire health and fault information for each of multiple target devices within a target time range; Based on the health and fault information of each target device within the target time range, the target ranking result is determined, and the target ranking result is used to characterize the ranking of the target devices. Generate report information based on the target ranking results.

[0136] Furthermore, the logical instructions in the aforementioned memory 1303 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0137] On the other hand, embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program. The computer program is used to cause a processor to execute the steps of the methods provided in the above embodiments, including, for example: In response to a report information generation command, identify multiple target devices corresponding to the report information generation command; Acquire health and fault information for each of multiple target devices within a target time range; Based on the health and fault information of each target device within the target time range, the target ranking result is determined, and the target ranking result is used to characterize the ranking of the target devices. Generate report information based on the target ranking results.

[0138] The aforementioned non-transitory computer-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic storage (e.g., floppy disks, hard disks, magnetic tapes, magneto-optical disks (MOs), etc.), optical storage (e.g., CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (e.g., ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)).

[0139] On the other hand, embodiments of this application also provide a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of the report information generation method provided in the above embodiments, such as including: In response to a report information generation command, identify multiple target devices corresponding to the report information generation command; Acquire health and fault information for each of multiple target devices within a target time range; Based on the health and fault information of each target device within the target time range, the target ranking result is determined, and the target ranking result is used to characterize the ranking of the target devices. Generate report information based on the target ranking results.

[0140] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and 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 modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0141] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0142] Finally, it should be noted that 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.

Claims

1. A method for generating report information, characterized in that, include: In response to a report information generation instruction, multiple target devices corresponding to the report information generation instruction are determined; Obtain health information and fault information of each of the multiple target devices within a target time range; Based on the health information and fault information of each target device within the target time range, a target ranking result is determined, and the target ranking result is used to characterize the ranking of the target devices; Based on the target ranking results, generate report information.

2. The method according to claim 1, characterized in that, The step of responding to a report information generation instruction and determining multiple target devices corresponding to the report information generation instruction includes: In response to the report information generation instruction, filtering conditions are determined according to the report information generation instruction, and the filtering conditions include at least one of location information, subsystem information and time information; From a preset device library, multiple devices that meet the filtering criteria are identified as the target devices corresponding to the report information generation instruction.

3. The method according to claim 1, characterized in that, The step of acquiring the health information and fault information of each of the multiple target devices within a target time range includes: Obtain the average health level and the degree of health level fluctuation for each target device within the target time range; The health information of each target device is determined based on the average health level and the degree of health level fluctuation of each target device within the target time range; Obtain the average number of failures and the degree of fluctuation in the number of failures for each target device within the target time range; The fault information of each target device is determined based on the average number of faults and the degree of fluctuation of the number of faults within the target time range.

4. The method according to claim 3, characterized in that, The step of obtaining the average health level and health level fluctuation of each target device within the target time range includes: Obtain the health status of each target device at each unit time within the target time range; The average health of each target device within the target time range is determined by averaging its health status at each unit of time within the target time range. The fluctuation of the health status of each target device within the target time range is calculated based on the health status and average health status of each target device per unit time within the target time range. The step of obtaining the average number of failures and the degree of fluctuation in the number of failures for each target device within the target time range includes: Obtain the number of faults of each target device per unit time within the target time range; The average number of failures of each target device within the target time range is determined by averaging the number of failures per unit time within the target time range. The degree of fluctuation in the number of faults of each target device within the target time range is obtained by calculating the fluctuation of the number of faults of each target device within the target time range based on the number of faults per unit time and the average number of faults.

5. The method according to claim 1, characterized in that, The step of determining the target ranking result based on the health information and fault information of each target device within the target time range includes: A first health ranking result is determined based on the health information of each target device within the target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices. A first fault ranking result is determined based on the fault information of each target device within the target time range. The first fault ranking result is used to characterize the fault ranking of each target device among multiple target devices. The target ranking result is determined based on the first health ranking result and the first fault ranking result.

6. The method according to claim 1, characterized in that, The step of determining the target ranking result based on the health information and fault information of each target device within the target time range includes: Obtain grouping information for each of the target devices, wherein the grouping information includes at least one of device type and device batch; The multiple target devices are grouped according to the grouping information to obtain multiple device groups, and each of the multiple device groups includes at least one target device. A first health ranking result and a second health ranking result are determined based on the health information of each target device within the target time range. The first health ranking result is used to characterize the health ranking of each target device among multiple target devices, and the second health ranking result is used to characterize the health ranking of each device group among multiple device groups. A first fault ranking result and a second fault ranking result are determined based on the fault information of each target device within the target time range. The first fault ranking result is used to characterize the fault ranking of each target device among multiple target devices, and the second fault ranking result is used to characterize the fault ranking of each device group among multiple device groups. The target ranking result is determined based on the first health ranking result, the second health ranking result, the first fault ranking result, and the second fault ranking result.

7. The method according to claim 1, characterized in that, The step of generating report information based on the target ranking result includes: Obtain fault records for each of the target devices within the target time range; Based on the fault records of each target device within the target time range, determine multiple fault causes and the total number of faults for each of the multiple fault causes; Based on the total number of faults for each of the aforementioned fault causes, a fault cause ranking result is determined, which is used to characterize the ranking of the number of each of the aforementioned fault causes among the multiple fault causes. A report is generated based on the target ranking results and the fault cause ranking results.

8. A report information generation device, characterized in that, include: The first determining module is used to determine multiple target devices corresponding to the report information generation instruction in response to the report information generation instruction; The acquisition module is used to acquire health information and fault information of each of the multiple target devices within a target time range; The second determining module is used to determine the target ranking result based on the health information and fault information of each target device within the target time range, wherein the target ranking result is used to characterize the ranking status of the target device; The generation module is used to generate report information based on the target ranking results.

9. An electronic device comprising a processor and a memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the report information generation method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the report information generation method as described in any one of claims 1 to 7.

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