RPA robot operation monitoring analysis method based on servitization platform

Abstract

The invention provides an RPA robot operation monitoring analysis method based on a servitization platform, and belongs to the technical field of RPA robots, and the method specifically comprises the steps: determining that a PRA robot does not have a business interface of which the operation state does not meet the requirement through reading failure data in different file data size intervals; on the basis of reading failure data and historical reading data in different file data volume intervals, reading problem coefficients and problem data volume intervals of the service interfaces in the different file data volume intervals are determined, and coincidence operation data of the problem data volume intervals of the different service interfaces of the RPA robot are determined based on an analysis result; and whether the service interface of the RPA robot needs to be optimized or not is determined by combining the reading problem coefficients of different problem data volume intervals, so that the operation reliability of the RPA robot is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of RPA robots, and in particular relates to an RPA robot operation monitoring and analysis method based on a service platform. Background Art

[0002] In order to improve the efficiency of data processing and reduce the data processing pressure on staff, power companies have deployed a large number of RPA robots based on different business needs. This makes how to monitor the operation of RPA robots and ensure the efficiency and accuracy of data processing a technical problem that needs to be solved urgently.

[0003] In the specific existing technical solutions, for example, CN202310753900.2 "A method, system and device for monitoring power grid work orders based on RPA robots" saves manpower and improves the efficiency of work order circulation through real-time automatic monitoring and reminder of various power grid work orders. However, the above technical solutions have the following technical problems: During the operation of the RPA robot, there may be a mismatch between the business interface and the file size of the uploaded file, which may cause the business call of the RPA robot to fail. Therefore, if the business interface cannot be adjusted in a targeted manner, the reliability of the RPA robot's operation cannot be guaranteed.

[0004] In response to the above technical problems, the present invention provides an RPA robot operation monitoring and analysis method based on a service-oriented platform. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: In order to solve the above technical problems, the present invention provides the following technical solutions to achieve the purpose of the present invention: According to one aspect of the present invention, a method for monitoring and analyzing the operation of an RPA robot based on a service-oriented platform is provided.

[0006] A RPA robot operation monitoring and analysis method based on a service-oriented platform, specifically including: S1 acquires the read failure data of the business interface of the RPA robot based on the analysis result of the operation data of the RPA robot of the service-oriented platform, and proceeds to the next step when it is determined that the operation status of the RPA robot meets the requirements according to the read failure data of different business interfaces when performing business processing; S2 divides the read failure data into different file data volume intervals according to the corresponding file data, and uses the read failure data in different file data volume intervals to determine that the PRA robot does not have a business interface whose operating status does not meet the requirements, and then proceeds to the next step; S3 determines the read problem coefficient and problem data volume interval of the service interface in different file data volume intervals based on the read failure data and historical read data in different file data volume intervals; S4 determines the overlapping operation data of the problem data volume intervals of different business interfaces of the RPA robot based on the analysis results, and determines whether the business interface of the RPA robot needs to be optimized in combination with the reading problem coefficients of different problem data volume intervals.

[0007] A further technical solution is that the operation data of the RPA robot is determined based on the analysis results of the operation log of the RPA robot of the service platform.

[0008] A further technical solution is that the read failure data includes file types, file data volumes and corresponding times corresponding to different read failure times.

[0009] A further technical solution is that the overlapping operation data includes the historical call times of different business interfaces of the RPA robot that are in the problem data volume range and the operation duration of different historical call times.

[0010] A further technical solution is to determine whether it is necessary to optimize the business interface of the RPA robot, which specifically includes: The problem data volume intervals of different business interfaces are combined for processing, and different overlap operation reference states are determined by taking the problem data volume intervals of different business interfaces as variables; Determine the number of historical calls and the running durations of different historical calls under the coincidence operation reference state by using the coincidence operation data under different coincidence operation reference states, and determine the running problem coefficients under different coincidence operation reference states by combining the reading problem coefficients of the problem data volume intervals of different business interfaces under the coincidence operation reference state; The comprehensive operation problem coefficient of the RPA robot is determined based on the operation problem coefficients under different overlapping operation reference states, and the comprehensive operation problem coefficient is used to determine whether the business interface of the RPA robot needs to be optimized.

[0011] A further technical solution is that, when the comprehensive operation problem coefficient of the RPA robot does not meet the requirements, it is determined that the business interface of the RPA robot needs to be optimized.

[0012] The beneficial effects of the present invention are: 1. The read failure data in different file data volume ranges is used to determine whether the PRA robot has a business interface whose running status does not meet the requirements, thereby avoiding the technical problem of being unable to comprehensively consider different business interfaces due to single consideration of the read failure data of the RPA robot. The business interfaces that do not meet the running status requirements are screened from the perspective of the read failure data, ensuring the reliability of the running status of the business interface and avoiding the impact of abnormal read failure data of a certain business interface on the normal operation of the RPA robot.

[0013] 2. Determine whether the business interface of the RPA robot needs to be optimized based on the overlapping operation data of the problem data volume intervals of different business interfaces and the reading problem coefficients of different problem data volume intervals. This allows comprehensive consideration of the abnormal operation conditions of the different business interfaces of the PRA robot that are in the problem data volume interval, avoids the technical problem of the RPA robot's operating status not meeting the requirements due to frequent abnormal operation conditions, and achieves differentiated optimization of the business interfaces of the RPA robot, ensuring the operational reliability of the RPA robot.

[0014] Other features and advantages will be described in the following description, and partly become apparent from the description, or understood by practicing the invention. The purpose and other advantages of the invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0015] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0017] Figure 1 It is a flow chart of the RPA robot operation monitoring and analysis method based on the service-oriented platform; Figure 2 It is a flow chart of a method for determining whether the operating status of an RPA robot meets the requirements; Figure 3 It is a flow chart of a method for determining a reading problem coefficient of a business interface in different file data volume intervals. DETAILED DESCRIPTION

[0018] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that the present invention will be comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The same reference numerals in the figures represent the same or similar structures, and thus their detailed description will be omitted.

[0019] The terms "a", "an", "the", and "said" are used to indicate the presence of one or more elements / components / etc.; the terms "comprising" and "having" are used to express an open-ended inclusive meaning and mean that additional elements / components / etc. may be present in addition to the listed elements / components / etc.

[0020] To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, according to one aspect of the present invention, a RPA robot operation monitoring and analysis method based on a service-oriented platform is provided, which specifically includes: S1 acquires the read failure data of the business interface of the RPA robot based on the analysis result of the operation data of the RPA robot of the service-oriented platform, and proceeds to the next step when it is determined that the operation status of the RPA robot meets the requirements according to the read failure data of different business interfaces when performing business processing; S2 divides the read failure data into different file data volume intervals according to the corresponding file data, and uses the read failure data in different file data volume intervals to determine that the PRA robot does not have a business interface whose operating status does not meet the requirements, and then proceeds to the next step; S3 determines the read problem coefficient and problem data volume interval of the service interface in different file data volume intervals based on the read failure data and historical read data in different file data volume intervals; S4 determines the overlapping operation data of the problem data volume intervals of different business interfaces of the RPA robot based on the analysis results, and determines whether the business interface of the RPA robot needs to be optimized in combination with the reading problem coefficients of different problem data volume intervals.

[0021] Furthermore, the operation data of the RPA robot is determined based on the analysis results of the operation log of the RPA robot of the service platform.

[0022] Specifically, the read failure data includes file types, file data volumes, and corresponding times corresponding to different read failure times.

[0023] It should be noted that if Figure 2As shown, determining whether the running status of the RPA robot meets the requirements specifically includes: Determine the number of read failures of the business interface of the RPA robot using the read failure data when the RPA robot performs business processing, and determine the failure reading problem coefficient of the RPA robot using the proportion of the number of read failures in the historical read times of the RPA robot; Obtain the business interface with read failure data and use it as the problem business interface, determine the interface problem coefficients of different problem business interfaces according to the number of read failures of the problem business interface, and determine the interface problem coefficient of the RPA robot based on the proportion of the problem business interface in the number of business interfaces of the RPA robot and the interface problem coefficients of different problem business interfaces; The operating status value of the RPA robot is determined by the failed reading problem coefficient and the interface problem coefficient of the RPA robot, and the operating status value is used to determine whether the operating status of the RPA robot meets the requirements.

[0024] Furthermore, when the operating status value of the RPA robot is not within a preset range, it is determined that the operating status of the RPA robot does not meet the requirements.

[0025] It is understandable that when the operating status of the RPA robot does not meet the requirements, it is determined that the business interface of the RPA robot needs to be optimized.

[0026] It should also be noted that determining whether the operating status of the RPA robot meets the requirements specifically includes: S11 determines the number of read failures of the business interface of the RPA robot based on the read failure data when the RPA robot performs business processing, obtains the business interface with the read failure data, and uses it as the problematic business interface; S12 determines the interface problem coefficients of different problematic service interfaces according to the number of read failures of the problematic service interface; S13 determines the interface problem coefficient of the RPA robot based on the proportion of the problematic business interface in the number of business interfaces of the RPA robot and the interface problem coefficients of different problematic business interfaces, determines the operating status value of the RPA robot through the failed reading problem coefficient and the interface problem coefficient of the RPA robot, and uses the operating status value to determine whether the operating status of the RPA robot meets the requirements.

[0027] Optionally, the above step S11 includes the following contents: S111 determines the number of read failures of the business interface of the RPA robot based on the read failure data of the RPA robot when performing business processing, and judges whether the number of read failures of the business interface of the RPA robot is greater than the preset number of failures. If so, proceed to the next step; if not, proceed to step S12; S112 determines the failure reading problem coefficient of the RPA robot by using the proportion of the number of failed reads in the historical number of reads of the RPA robot, and judges whether the failure reading problem coefficient of the RPA robot meets the requirement. If so, proceeds to the next step; if not, determines that the operating state of the RPA robot does not meet the requirement. S113 obtains the business interface with failed reading data and uses it as the problem business interface to determine whether the proportion of the problem business interface in the number of business interfaces of the RPA robot meets the requirements. If so, proceed to step S12; if not, determine that the operating status of the RPA robot does not meet the requirements.

[0028] Optionally, the above step S12 includes the following contents: The interface problem coefficients of different problem business interfaces are determined by the number of failed reads of the problem business interface, and it is determined whether there is a problem business interface whose interface problem coefficient does not meet the requirements. If so, it is determined that the operating status of the RPA robot does not meet the requirements. If not, proceed to step S13.

[0029] Furthermore, the read failure data is divided into different file data volume intervals, specifically including: The file data volume intervals in which the file data volumes corresponding to different read failed data are located are used to divide the read failed data into different file data volume intervals.

[0030] It can be understood that determining that the PRA robot does not have a business interface whose operating status does not meet the requirements specifically includes: Determine the number of read failures of the service interface in different file data volume intervals based on the read failure data of the service interface in different file data volume intervals, and determine the interval problem coefficients of the different file data volume intervals according to the number of read failures in different file data volume intervals; The file data volume interval whose interval problem coefficient is greater than a preset coefficient threshold is used as a screening problem interval, and the number of the screening problem interval is used to determine whether the operating status of the service interface meets the requirements.

[0031] It should be noted that, when the number of the screening problem intervals is greater than the preset number of intervals, it is determined that the operating status of the service interface does not meet the requirements.

[0032] Furthermore, when the PRA robot does not have a business interface whose operating status does not meet the requirements, it is determined that the business interface of the RPA robot needs to be optimized.

[0033] It can be understood that determining that the PRA robot does not have a business interface whose operating status does not meet the requirements specifically includes: S21 uses the read failure data of the service interface in different file data volume intervals, and regards the file data volume interval with the read failure data as a potential abnormal interval S22 determines interval problem coefficients of different file data volume intervals according to the number of read failures in different file data volume intervals; S23 determines the weight values ​​of different potential abnormal intervals based on the proportion of the number of historical read times of different potential abnormal intervals, and determines the comprehensive problem coefficient in combination with the interval problem coefficients of different potential abnormal intervals, and uses the comprehensive problem coefficient to determine whether the operating status of the business interface meets the requirements.

[0034] Optionally, step S21 includes the following contents: S211 determines whether the number of failed reads of the service interface meets the requirement, if so, proceeds to the next step, if not, determines that the operating state of the service interface does not meet the requirement; S212 uses the read failure data of the service interface in different file data volume intervals, and uses the file data volume interval with the read failure data as the potential abnormal interval, and determines whether the number of the potential abnormal intervals meets the requirement. If yes, proceed to the next step, if not, proceed to step S22; S213 obtains the number of read failures of the service interface in different potential abnormal intervals, and determines whether the total number of read failures of the service interface in different potential abnormal intervals meets the requirements. If so, it is determined that the operating state of the service interface meets the requirements. If not, proceed to the next step. S214 determines whether there is a potential abnormal interval with a number of read failures greater than a preset number threshold based on the number of read failures in different potential abnormal intervals. If so, proceed to step S22. If not, determine whether the operating status of the business interface meets the requirements.

[0035] Optionally, step S22 includes the following contents: Determine the interval problem coefficients of different file data volume intervals according to the number of read failures in different file data volume intervals, and judge whether the number of file data volume intervals whose interval problem coefficients are greater than a preset problem coefficient threshold meets the requirements. If so, enter step S23; if not, determine that the operating status of the business interface does not meet the requirements.

[0036] Specifically, Figure 3 As shown, the method for determining the reading problem coefficient of the business interface in different file data volume intervals is: Based on the read failure data of the service interface in the file data volume interval, determine the number of read failures of the service interface in the file data volume interval, and determine the failure problem coefficient of the file data volume interval in combination with the historical read number of the service interface in the file data volume interval; Based on the historical reading data of the business interface in the file data volume interval, determining the reading delays of different historical reading times in the file data volume interval, and determining the delay problem coefficient of the file data volume interval by using the proportion of the historical reading times with a reading delay greater than a preset time length; The read problem coefficient of the service interface in the file data volume range is determined based on the weight of the delay problem coefficient and the failure problem coefficient.

[0037] Furthermore, the reading problem coefficient of the business interface in the file data volume interval ranges from 0 to 1, wherein when the reading problem coefficient of the business interface in the file data volume interval is greater than a preset problem coefficient threshold, the file data volume interval is determined to be a problem data volume interval.

[0038] It should also be noted that the method for determining the reading problem coefficient of the business interface in different file data volume intervals is: S31 determines the number of read failures of the service interface in the file data volume interval based on the read failure data of the service interface in the file data volume interval; S32 determines the failure problem coefficient of the file data volume interval based on the historical read times and read failure times of the business interface in the file data volume interval, determines the delay problem coefficient of the file data volume interval using the proportion of the historical read times in which the read delay is greater than a preset time length, and determines the read problem coefficient of the business interface in the file data volume interval based on the weight sum of the delay problem coefficient and the failure problem coefficient.

[0039] Optionally, the above step S31 includes the following contents: S311 determines whether the service interface has read failure data in the file data volume interval, if yes, proceeds to the next step, if no, determines that the file data volume interval does not belong to the problem data volume interval; S312 determines the number of read failures of the service interface in the file data volume interval based on the read failure data of the service interface in the file data volume interval, and judges whether the number of read failures of the service interface in the file data volume interval is less than a preset failure number threshold, if yes, proceeds to the next step, if no, proceeds to step S32; S313 determines the reading delays of different historical reading times in the file data volume interval based on the historical reading data of the service interface in the file data volume interval, and judges whether the average of the reading delays of different historical reading times in the file data volume interval is less than a preset delay amount. If so, it is determined that the file data volume interval does not belong to the problem data volume interval. If not, proceed to the next step. S314 determines whether the number of historical reads with a read delay greater than a preset time length is less than a preset delay number threshold. If so, it is determined that the file data volume interval does not belong to the problem data volume interval. If not, enter step S32.

[0040] Furthermore, the overlapping operation data includes the historical call times of different business interfaces of the RPA robot in the problem data volume range and the operation duration of different historical call times.

[0041] It is understandable that determining whether the business interface of the RPA robot needs to be optimized specifically includes: The problem data volume intervals of different business interfaces are combined for processing, and different overlap operation reference states are determined by taking the problem data volume intervals of different business interfaces as variables; Determine the number of historical calls and the running durations of different historical calls under the coincidence operation reference state by using the coincidence operation data under different coincidence operation reference states, and determine the running problem coefficients under different coincidence operation reference states by combining the reading problem coefficients of the problem data volume intervals of different business interfaces under the coincidence operation reference state; The comprehensive operation problem coefficient of the RPA robot is determined based on the operation problem coefficients under different overlapping operation reference states, and the comprehensive operation problem coefficient is used to determine whether the business interface of the RPA robot needs to be optimized.

[0042] Furthermore, when the comprehensive operation problem coefficient of the RPA robot does not meet the requirements, it is determined that the business interface of the RPA robot needs to be optimized.

[0043] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0044] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0045] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A RPA robot operation monitoring and analysis method based on a service-oriented platform, characterized in that: Specifically include: Based on the analysis result of the operation data of the RPA robot of the service-oriented platform, the read failure data of the business interface of the RPA robot is obtained, and when it is determined that the operation status of the RPA robot meets the requirements according to the read failure data of different business interfaces during business processing, the next step is entered; Divide the read failure data into different file data volume intervals according to the corresponding file data, and use the read failure data in different file data volume intervals to determine that the PRA robot does not have a business interface whose operating status does not meet the requirements, and then proceed to the next step; Based on the read failure data and historical read data in different file data volume intervals, determining the read problem coefficient and the problem data volume interval of the service interface in different file data volume intervals; Based on the analysis results, the overlapping operation data of the problem data volume intervals of different business interfaces of the RPA robot are determined, and combined with the reading problem coefficients of different problem data volume intervals, it is determined whether the business interface of the RPA robot needs to be optimized.

2. The RPA robot operation monitoring and analysis method based on the service platform according to claim 1 is characterized in that: The operation data of the RPA robot is determined according to the analysis result of the operation log of the RPA robot of the service platform.

3. The RPA robot operation monitoring and analysis method based on the service platform according to claim 1 is characterized in that: The read failure data includes file types, file data volumes, and corresponding times corresponding to different read failure times.

4. The RPA robot operation monitoring and analysis method based on a service platform according to claim 1, characterized in that: Determine whether the operating status of the RPA robot meets the requirements, including: Determine the number of read failures of the business interface of the RPA robot using the read failure data when the RPA robot performs business processing, and determine the failure reading problem coefficient of the RPA robot using the proportion of the number of read failures in the historical read times of the RPA robot; Obtain the business interface with read failure data and use it as the problem business interface, determine the interface problem coefficients of different problem business interfaces according to the number of read failures of the problem business interface, and determine the interface problem coefficient of the RPA robot based on the proportion of the problem business interface in the number of business interfaces of the RPA robot and the interface problem coefficients of different problem business interfaces; The operating status value of the RPA robot is determined by the failed reading problem coefficient and the interface problem coefficient of the RPA robot, and the operating status value is used to determine whether the operating status of the RPA robot meets the requirements.

5. The RPA robot operation monitoring and analysis method based on a service platform according to claim 1, characterized in that: When the operating status of the RPA robot does not meet the requirements, it is determined that the business interface of the RPA robot needs to be optimized.

6. The RPA robot operation monitoring and analysis method based on a service platform according to claim 1, characterized in that: Dividing the read failure data into different file data volume intervals specifically includes: The file data volume intervals in which the file data volumes corresponding to different read failed data are located are used to divide the read failed data into different file data volume intervals.

7. The RPA robot operation monitoring and analysis method based on a service platform according to claim 1, characterized in that: Determining that the PRA robot does not have a business interface whose operating status does not meet the requirements, specifically includes: Determine the number of read failures of the service interface in different file data volume intervals based on the read failure data of the service interface in different file data volume intervals, and determine the interval problem coefficients of the different file data volume intervals according to the number of read failures in different file data volume intervals; The file data volume interval whose interval problem coefficient is greater than a preset coefficient threshold is used as a screening problem interval, and the number of the screening problem interval is used to determine whether the operating status of the service interface meets the requirements.

8. The RPA robot operation monitoring and analysis method based on a service platform according to claim 1, characterized in that: When the PRA robot does not have a business interface whose operating status does not meet the requirements, it is determined that the business interface of the RPA robot needs to be optimized.

9. The RPA robot operation monitoring and analysis method based on a service platform as claimed in claim 1, characterized in that: The overlapping operation data includes the historical call times of different business interfaces of the RPA robot in the problem data volume range and the operation duration of different historical call times.

Images