Operational Risk Assessment Method and Device Based on Multidimensional Data

Abstract

This invention discloses a method and apparatus for operational risk assessment based on multidimensional data. The method includes: acquiring operational information of a target device, including basic attribute information, real-time status information, and wear and tear maintenance information; determining whether the target device meets preset basic operational assessment conditions based on the operational information; and if so, determining the operational risk assessment result corresponding to the target device based on the operational information and the preset operational assessment conditions. Therefore, this invention can intelligently realize the function of equipment operational risk assessment, which is beneficial to improving the comprehensiveness and scientific nature of the equipment operational risk assessment method, thereby improving the accuracy and reliability of the determined operational risk assessment results, and also improving the efficiency and convenience of determining the operational risk assessment results.

Description

Technical Field

[0001] This invention relates to the field of risk assessment technology, and in particular to a method and apparatus for operational risk assessment based on multidimensional data. Background Technology

[0002] As the scale of power grid assets expands and the number of operating equipment gradually increases, there are also operational relationships between the equipment. Therefore, it is necessary to conduct operational risk assessments on the operating equipment, identify and eliminate equipment with high operational risks, and ensure the continuous and orderly operation of power grid equipment.

[0003] Currently, most equipment operation risk assessment methods involve staff collecting equipment operational data offline for each assessment and subjectively evaluating the data according to pre-defined assessment guidelines. This subjective evaluation is susceptible to influence from factors such as mental state, environment, and subjective bias. Furthermore, the lack of an information system to support these methods further impacts the assessment, resulting in low accuracy and efficiency. Therefore, providing a method that improves both accuracy and efficiency in equipment operation risk assessment is crucial. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and apparatus for assessing operational risks based on multidimensional data, which can improve the accuracy and efficiency of assessing equipment operational risks.

[0005] To address the aforementioned technical problems, the first aspect of this invention discloses a method for operational risk assessment based on multidimensional data, the method comprising:

[0006] Obtain the operating information of the target device, including basic attribute information, real-time status information, and wear and tear maintenance information;

[0007] Based on the operational information, determine whether the target device meets the preset basic operational evaluation conditions;

[0008] When it is determined that the target device meets the basic operation assessment conditions, the operation risk assessment result corresponding to the target device is determined based on the operation information and the preset operation assessment conditions.

[0009] As an optional implementation, in the first aspect of the present invention, determining the operational risk assessment result corresponding to the target device based on the operational information and preset operational assessment conditions includes:

[0010] Based on the basic attribute information, the real-time status information, and the preset health index assessment conditions, the health index assessment result corresponding to the target device is determined.

[0011] Based on the wear and tear maintenance information and the preset aging index evaluation conditions, the aging index evaluation result corresponding to the target equipment is determined.

[0012] Based on the health index assessment results, the aging index assessment results, and the preset index risk assessment conditions, the operational risk assessment results corresponding to the target equipment are determined.

[0013] As an optional implementation, in the first aspect of the present invention, determining the health index assessment result corresponding to the target device based on the basic attribute information, the real-time status information, and preset health index assessment conditions includes:

[0014] Based on the basic attribute information and the preset first sub-evaluation conditions, the first health index evaluation result corresponding to the target device is determined;

[0015] Based on the real-time status information and the preset second sub-evaluation conditions, the second health index evaluation result corresponding to the target device is determined;

[0016] Based on the first health index assessment result, the second health index assessment result, and the preset health index weight calculation conditions, the health index assessment result corresponding to the target device is calculated.

[0017] As an optional implementation, in the first aspect of the present invention, determining the operational risk assessment result corresponding to the target equipment based on the health index assessment result, the aging index assessment result, and preset index risk assessment conditions includes:

[0018] Based on the health index assessment results, the aging index assessment results, and the set risk weight assessment conditions, calculate the operational risk index corresponding to the target equipment;

[0019] Based on the operational risk index and the set risk level analysis conditions, the operational risk level corresponding to the target equipment is determined, which serves as the operational risk assessment result for the target equipment.

[0020] As an optional implementation, in the first aspect of the present invention, before calculating the operational risk index corresponding to the target equipment based on the health index assessment result, the aging index assessment result, and the risk weight assessment conditions, the method further includes:

[0021] Determine whether the health index assessment results match the aging index assessment results;

[0022] When it is determined that the health index assessment result matches the aging index assessment result, the operation of calculating the operating risk index corresponding to the target equipment based on the health index assessment result, the aging index assessment result, and the risk weight assessment conditions is performed.

[0023] When it is determined that the health index assessment result does not match the aging index assessment result, the basic attribute information, the real-time status information and the wear and tear maintenance information are analyzed to obtain the operation correlation degree, and it is determined whether the operation correlation degree is greater than or equal to the preset operation correlation degree threshold.

[0024] When it is determined that the operational correlation degree is greater than or equal to the operational correlation degree threshold, the received evaluation feedback information corresponding to the target device is obtained, and the target index evaluation result is selected from the health index evaluation result and the aging index evaluation result based on the evaluation feedback information; the operational risk index corresponding to the target device is calculated based on the target index evaluation result and the risk weight evaluation conditions; and the operation of determining the operational risk level corresponding to the target device based on the operational risk index and the set risk level analysis conditions is performed as the operational risk evaluation result corresponding to the target device.

[0025] When it is determined that the operational correlation is less than the operational correlation threshold, the operation of calculating the operational risk index corresponding to the target device based on the health index assessment result, the aging index assessment result, and the risk weight assessment condition is performed.

[0026] As an optional implementation, in the first aspect of the present invention, determining whether the health index assessment result matches the aging index assessment result includes:

[0027] By analyzing the health index assessment results, a first predicted risk category corresponding to the target device is obtained, and by analyzing the aging index assessment results, a second predicted risk category corresponding to the target device is obtained.

[0028] Based on the first predicted risk category and the second predicted risk category, the corresponding risk similarity is determined, and it is determined whether the risk similarity is greater than or equal to a preset risk similarity threshold.

[0029] When it is determined that the risk similarity is greater than or equal to the risk similarity threshold, it is determined that the health index assessment result matches the aging index assessment result;

[0030] When it is determined that the risk similarity is less than the risk similarity threshold, it is determined that the health index assessment result does not match the aging index assessment result.

[0031] The first and second predicted risk categories each include one or more of the following: the predicted risk level, the predicted risk type attribute, and the equipment information corresponding to the predicted risk.

[0032] As an optional implementation, in the first aspect of the present invention, the method further includes:

[0033] Based on the operational risk assessment results, determine the risk management situation corresponding to the target equipment.

[0034] When the risk handling status indicates that the target device meets the preset risk handling conditions, the target risk handling type corresponding to the target device is determined based on the operational risk assessment results and the set risk handling analysis information.

[0035] Based on the target risk handling type, the operational information, and the operational risk assessment results, determine the risk handling information corresponding to the target device;

[0036] Based on the risk processing information, an operational risk processing operation is performed on the target device to obtain the target device after operational risk processing.

[0037] A second aspect of this invention discloses an operational risk assessment device based on multidimensional data, the device comprising:

[0038] The acquisition module is used to acquire the operating information of the target device, including basic attribute information, real-time status information, and wear and maintenance information.

[0039] The judgment module is used to determine whether the target device meets the preset basic operation evaluation conditions based on the operation information.

[0040] The risk assessment module is used to determine the operational risk assessment result of the target device based on the operational information and preset operational assessment conditions when the judgment module determines that the target device meets the basic operational assessment conditions.

[0041] As an optional implementation, in the second aspect of the present invention, the method by which the risk assessment module determines the operational risk assessment result corresponding to the target device based on the operational information and preset operational assessment conditions specifically includes:

[0042] Based on the basic attribute information, the real-time status information, and the preset health index assessment conditions, the health index assessment result corresponding to the target device is determined.

[0043] Based on the wear and tear maintenance information and the preset aging index evaluation conditions, the aging index evaluation result corresponding to the target equipment is determined.

[0044] Based on the health index assessment results, the aging index assessment results, and the preset index risk assessment conditions, the operational risk assessment results corresponding to the target equipment are determined.

[0045] As an optional implementation, in the second aspect of the present invention, the method by which the risk assessment module determines the health index assessment result corresponding to the target device based on the basic attribute information, the real-time status information, and preset health index assessment conditions specifically includes:

[0046] Based on the basic attribute information and the preset first sub-evaluation conditions, the first health index evaluation result corresponding to the target device is determined;

[0047] Based on the real-time status information and the preset second sub-evaluation conditions, the second health index evaluation result corresponding to the target device is determined;

[0048] Based on the first health index assessment result, the second health index assessment result, and the preset health index weight calculation conditions, the health index assessment result corresponding to the target device is calculated.

[0049] As an optional implementation, in the second aspect of the present invention, the method by which the risk assessment module determines the operational risk assessment result corresponding to the target device based on the health index assessment result, the aging index assessment result, and preset index risk assessment conditions specifically includes:

[0050] Based on the health index assessment results, the aging index assessment results, and the set risk weight assessment conditions, calculate the operational risk index corresponding to the target equipment;

[0051] Based on the operational risk index and the set risk level analysis conditions, the operational risk level corresponding to the target equipment is determined, which serves as the operational risk assessment result for the target equipment.

[0052] As an optional implementation, in a second aspect of the present invention, the risk assessment module is further configured to determine whether the health index assessment result matches the aging index assessment result before calculating the operating risk index corresponding to the target equipment based on the health index assessment result, the aging index assessment result, and the risk weight assessment conditions.

[0053] When it is determined that the health index assessment result matches the aging index assessment result, the operation of calculating the operating risk index corresponding to the target equipment based on the health index assessment result, the aging index assessment result, and the risk weight assessment conditions is performed.

[0054] When it is determined that the health index assessment result does not match the aging index assessment result, the basic attribute information, the real-time status information and the wear and tear maintenance information are analyzed to obtain the operation correlation degree, and it is determined whether the operation correlation degree is greater than or equal to the preset operation correlation degree threshold.

[0055] When it is determined that the operational correlation degree is greater than or equal to the operational correlation degree threshold, the received evaluation feedback information corresponding to the target device is obtained, and the target index evaluation result is selected from the health index evaluation result and the aging index evaluation result based on the evaluation feedback information; the operational risk index corresponding to the target device is calculated based on the target index evaluation result and the risk weight evaluation conditions; and the operation of determining the operational risk level corresponding to the target device based on the operational risk index and the set risk level analysis conditions is performed as the operational risk evaluation result corresponding to the target device.

[0056] When it is determined that the operational correlation is less than the operational correlation threshold, the operation of calculating the operational risk index corresponding to the target device based on the health index assessment result, the aging index assessment result, and the risk weight assessment condition is performed.

[0057] As an optional implementation, in a second aspect of the present invention, the method by which the risk assessment module determines whether the health index assessment result matches the aging index assessment result specifically includes:

[0058] By analyzing the health index assessment results, a first predicted risk category corresponding to the target device is obtained, and by analyzing the aging index assessment results, a second predicted risk category corresponding to the target device is obtained.

[0059] Based on the first predicted risk category and the second predicted risk category, the corresponding risk similarity is determined, and it is determined whether the risk similarity is greater than or equal to a preset risk similarity threshold.

[0060] When it is determined that the risk similarity is greater than or equal to the risk similarity threshold, it is determined that the health index assessment result matches the aging index assessment result;

[0061] When it is determined that the risk similarity is less than the risk similarity threshold, it is determined that the health index assessment result does not match the aging index assessment result.

[0062] The first and second predicted risk categories each include one or more of the following: the predicted risk level, the predicted risk type attribute, and the equipment information corresponding to the predicted risk.

[0063] As an optional implementation, in a second aspect of the invention, the apparatus further includes:

[0064] The determination module is used to determine the risk handling status corresponding to the target device based on the operational risk assessment results; when the risk handling status indicates that the target device meets the preset risk handling conditions, the module determines the target risk handling type corresponding to the target device based on the operational risk assessment results and the set risk handling analysis information; and determines the risk handling information corresponding to the target device based on the target risk handling type, the operational information, and the operational risk assessment results.

[0065] The risk processing module is used to perform operational risk processing operations on the target device based on the risk processing information, so as to obtain the target device after operational risk processing.

[0066] A third aspect of the present invention discloses another operational risk assessment device based on multidimensional data, the device comprising:

[0067] Memory containing executable program code;

[0068] A processor coupled to the memory;

[0069] The processor calls the executable program code stored in the memory to execute the operational risk assessment method based on multidimensional data disclosed in the first aspect of the present invention.

[0070] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute the operational risk assessment method based on multidimensional data disclosed in the first aspect of the present invention.

[0071] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0072] In this embodiment of the invention, the operating information of the target device is acquired, including basic attribute information, real-time status information, and wear and tear maintenance information. Based on the operating information, it is determined whether the target device meets preset basic operating assessment conditions. When it is determined that the target device meets the basic operating assessment conditions, the operating risk assessment result corresponding to the target device is determined based on the operating information and the preset operating assessment conditions. Therefore, this invention can determine the operating risk assessment result of the device based on its operating information and operating assessment conditions, intelligently realizing the device operating risk assessment function. This is beneficial to improving the comprehensiveness and scientific nature of the device operating risk assessment method, thereby improving the accuracy and reliability of the determined operating risk assessment results, and also improving the efficiency and convenience of determining the operating risk assessment results. Attached Figure Description

[0073] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0074] Figure 1 This is a flowchart illustrating an operational risk assessment method based on multidimensional data disclosed in an embodiment of the present invention;

[0075] Figure 2 This is a flowchart illustrating another operational risk assessment method based on multidimensional data disclosed in an embodiment of the present invention;

[0076] Figure 3 This is a schematic diagram of the structure of an operational risk assessment device based on multidimensional data disclosed in an embodiment of the present invention;

[0077] Figure 4 This is a schematic diagram of another operational risk assessment device based on multidimensional data disclosed in an embodiment of the present invention;

[0078] Figure 5 This is a schematic diagram of the structure of another operational risk assessment device based on multidimensional data disclosed in an embodiment of the present invention;

[0079] Figure 6 This is a schematic diagram of the assessment process of an operational risk assessment method based on multidimensional data disclosed in an embodiment of the present invention. Detailed Implementation

[0080] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0081] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0082] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0083] This invention discloses a method and apparatus for operational risk assessment based on multidimensional data. It can determine the operational risk assessment results of equipment based on its operational information and assessment conditions, intelligently realizing the operational risk assessment function. This improves the comprehensiveness and scientific rigor of the operational risk assessment method, thereby enhancing the accuracy and reliability of the determined operational risk assessment results. Furthermore, it improves the efficiency and convenience of determining the operational risk assessment results. Detailed descriptions follow.

[0084] Example 1

[0085] Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for assessing operational risks based on multidimensional data, as disclosed in an embodiment of the present invention. Figure 1 The described method can be applied to an operational risk assessment device based on multidimensional data. This device may include a server, which may be a local server or a cloud server; this embodiment of the invention is not limited to this. Figure 1As shown, this operational risk assessment method based on multidimensional data includes the following operations:

[0086] 101. Obtain the operating information of the target device, including basic attribute information, real-time status information, and wear and tear maintenance information.

[0087] Optionally, the basic attribute information can be the basic ledger information of the equipment, such as rated voltage information, rated current information and operating years information, etc., which is not limited in this embodiment of the invention.

[0088] Optionally, the real-time status information can be the real-time operating information of the equipment, such as the temperature information of the equipment operating environment, the status of equipment components (such as whether the equipment has defects), and the real-time running stability trajectory information of the equipment, etc., which are not limited in this embodiment of the invention.

[0089] Optionally, the loss and maintenance information can be historical operating information of the equipment, such as equipment overload information, equipment over-excitation information, historical defect information of equipment components, and historical maintenance failure information of the equipment, etc., which are not limited in this embodiment of the invention.

[0090] 102. Based on the operational information, determine whether the target equipment meets the preset basic operational evaluation conditions.

[0091] Optionally, the basic operation evaluation conditions can be understood as whether the equipment exists or sends an operation fault signal, whether the equipment can no longer operate normally, and whether the equipment has a critical fault, etc., which are not limited in the embodiments of the present invention.

[0092] Alternatively, when it is determined that the target equipment does not meet the basic operation evaluation conditions, the operation information of the target equipment continues to be monitored and step 102 is executed.

[0093] 103. When it is determined that the target equipment meets the basic operation assessment conditions, the operation risk assessment result corresponding to the target equipment is determined based on the operation information and the preset operation assessment conditions.

[0094] Optionally, the application process for determining the equipment operation risk assessment results can be referred to... Figure 6 As shown, the embodiments of the present invention are not limited.

[0095] As can be seen, the operational risk assessment method based on multidimensional data described in the embodiments of the present invention can determine the operational risk assessment result of the equipment according to the equipment's operational information and operational assessment conditions, intelligently realize the equipment operational risk assessment function, which is conducive to improving the comprehensiveness and scientific nature of the equipment operational risk assessment method, thereby improving the accuracy and reliability of the determined operational risk assessment result, thus improving the accuracy and reliability of the equipment operational risk assessment, and also improving the efficiency and convenience of determining the operational risk assessment result, thereby improving the efficiency and convenience of the equipment operational risk assessment.

[0096] In an optional embodiment, the determination of the operational risk assessment result corresponding to the target device based on operational information and preset operational assessment conditions may include:

[0097] Based on basic attribute information, real-time status information, and preset health index assessment conditions, determine the health index assessment result corresponding to the target device;

[0098] Based on the wear and tear maintenance information and the preset aging index assessment conditions, determine the aging index assessment result corresponding to the target equipment.

[0099] Based on the health index assessment results, aging index assessment results, and preset index risk assessment conditions, the operational risk assessment results corresponding to the target equipment are determined.

[0100] Optionally, the health index assessment results, aging index assessment results, and operational risk assessment results can be represented in numerical form, in grade form, in the form of matching degree with the set evaluation index, or in the form of the target device being within the evaluation index range. This embodiment of the invention does not limit these methods.

[0101] As can be seen, this optional embodiment can determine the health index assessment result and the aging index assessment result, and then determine the operation risk assessment result. Matching the corresponding index assessment conditions with different equipment information types is conducive to improving the comprehensiveness, scientificity and pertinence of the operation risk assessment result determination method, and thus conducive to improving the accuracy and reliability of the determined index assessment result, thereby improving the accuracy and reliability of the determined operation risk assessment result.

[0102] In another optional embodiment, the determination of the health index assessment result corresponding to the target device based on basic attribute information, real-time status information, and preset health index assessment conditions may include:

[0103] Based on the basic attribute information and the preset first sub-evaluation conditions, determine the first health index evaluation result corresponding to the target device;

[0104] Based on real-time status information and preset second sub-evaluation conditions, determine the second health index evaluation result corresponding to the target device;

[0105] Based on the results of the first health index assessment, the results of the second health index assessment, and the preset health index weight calculation conditions, the health index assessment result corresponding to the target device is calculated.

[0106] Optionally, different evaluation conditions can be matched for different health indices, and the embodiments of the present invention do not limit this.

[0107] Optionally, when the first health index assessment result does not match the second health index assessment result, a third health index assessment result is determined by combining the historical operational health data of the target equipment, the normalized health change data of the equipment type corresponding to the target equipment, and the equipment health evaluation data of the staff / users using the target equipment. Based on the third health index assessment result, the above-mentioned operation of calculating the health index assessment result corresponding to the target equipment according to the first health index assessment result, the second health index assessment result, and the preset health index weight calculation conditions is performed.

[0108] As can be seen, this optional embodiment can determine the first health index assessment result and the second health index assessment result, and then calculate the health index assessment result of the device. According to the matching sub-assessment conditions, the sub-health index assessment result determination operation is performed on the basic attribute information and real-time status information, which is conducive to improving the comprehensiveness, rationality and scientific nature of the health index assessment result determination method, and thus conducive to improving the accuracy and reliability of the determined first health index assessment result and the second health index assessment result, thereby improving the accuracy and reliability of the determined device health index assessment result.

[0109] In another optional embodiment, the determination of the operational risk assessment result corresponding to the target equipment based on the health index assessment result, the aging index assessment result, and the preset index risk assessment conditions may include:

[0110] Based on the health index assessment results, aging index assessment results, and the established risk weight assessment conditions, calculate the operational risk index corresponding to the target equipment;

[0111] Based on the operational risk index and the established risk level analysis conditions, the operational risk level corresponding to the target equipment is determined, which serves as the operational risk assessment result for the target equipment.

[0112] Optionally, the operational risk index may represent the degree of stable operation of the target equipment, the probability of the target equipment malfunctioning, or the degree of operational safety of the target equipment. This embodiment of the invention does not limit the index.

[0113] As can be seen, this optional embodiment can determine the operational risk assessment results of the equipment by combining the risk weight assessment conditions and the risk level analysis conditions, which is conducive to improving the comprehensiveness and rationality of the operational risk assessment results, thereby improving the observability, intuitiveness and simplicity of the operational risk assessment results, and thus improving the practicality and callability of the operational risk assessment results.

[0114] In yet another optional embodiment, before calculating the operational risk index corresponding to the target equipment based on the health index assessment results, aging index assessment results, and risk weight assessment conditions, the method may further include the following operations:

[0115] Determine whether the health index assessment results match the aging index assessment results;

[0116] When it is determined that the health index assessment result matches the aging index assessment result, perform the above-mentioned operation of calculating the operating risk index corresponding to the target equipment based on the health index assessment result, the aging index assessment result and the risk weight assessment conditions.

[0117] When it is determined that the health index assessment result does not match the aging index assessment result, the basic attribute information, real-time status information and wear and tear maintenance information are analyzed to obtain the operational correlation degree, and it is determined whether the operational correlation degree is greater than or equal to the preset operational correlation degree threshold.

[0118] When it is determined that the operational correlation is greater than or equal to the operational correlation threshold, the evaluation feedback information corresponding to the target device is obtained, and the target index evaluation result is selected from the health index evaluation result and aging index evaluation result based on the evaluation feedback information; the operational risk index corresponding to the target device is calculated based on the target index evaluation result and the risk weight evaluation conditions; and the above-mentioned operation of determining the operational risk level corresponding to the target device based on the operational risk index and the set risk level analysis conditions is performed, which is used as the operational risk evaluation result corresponding to the target device.

[0119] When it is determined that the operational correlation is less than the operational correlation threshold, the above-mentioned operation of calculating the operational risk index corresponding to the target equipment based on the health index assessment results, aging index assessment results, and risk weight assessment conditions is performed.

[0120] Optionally, the evaluation feedback information of the target device may include, but is not limited to, one or more of the following: the target device's operational evaluation information, the target device's user experience evaluation information, the target device's self-monitoring fault and wear feedback information, the target device's maintenance feedback information, and the target device's corresponding predicted operational information. This embodiment of the invention does not limit the scope of the information.

[0121] As can be seen, this optional embodiment can perform similarity verification between health index assessment results and aging index assessment results, and introduce evaluation feedback information to determine the operational risk assessment results. It considers more influencing factors in determining the operational risk assessment results, which is conducive to improving the comprehensiveness, rationality and scientific nature of the operational risk assessment method based on multidimensional data. In turn, it is conducive to improving the diversity, flexibility and selectivity of the method for determining operational risk assessment results, thereby improving the accuracy and reliability of the determined operational risk assessment results, and also helps to reduce unnecessary waste of assessment resources.

[0122] In another optional embodiment, the determination of whether the health index assessment result matches the aging index assessment result may include:

[0123] By analyzing the health index assessment results, the first predicted risk category corresponding to the target equipment is obtained, and by analyzing the aging index assessment results, the second predicted risk category corresponding to the target equipment is obtained.

[0124] Based on the first predicted risk category and the second predicted risk category, determine the corresponding risk similarity and determine whether the risk similarity is greater than or equal to the preset risk similarity threshold.

[0125] When the risk similarity is determined to be greater than or equal to the risk similarity threshold, the health index assessment result is determined to match the aging index assessment result.

[0126] When the risk similarity is determined to be less than the risk similarity threshold, it is determined that the health index assessment result and the aging index assessment result do not match.

[0127] The first and second risk prediction categories each include one or more of the following: the degree of risk prediction, the type of risk prediction, and the equipment information corresponding to the risk prediction.

[0128] Optionally, the equipment information corresponding to the predicted risk can be understood as the location information of the specific components in the target equipment that have operational risks, the location information of the specific operating procedures that have operational risks, etc., and this embodiment of the invention does not limit it.

[0129] As can be seen, this optional embodiment can determine the predicted risk categories corresponding to the health index assessment results and the aging index assessment results, and determine the risk similarity corresponding to different predicted risk categories. Based on the comparison between the risk similarity and the risk similarity threshold, the matching situation between the health index assessment results and the aging index assessment results is determined. This helps to improve the rationality and scientificity of the method for determining the matching situation of assessment results, thereby improving the accuracy and reliability of the determined matching situation of assessment results, as well as improving the efficiency and convenience of determining the matching situation of assessment results.

[0130] Example 2

[0131] Please see Figure 2 , Figure 2 This is a flowchart illustrating another operational risk assessment method based on multidimensional data disclosed in an embodiment of the present invention. Figure 2 The described method can be applied to an operational risk assessment device based on multidimensional data. This device may include a server, which may be a local server or a cloud server; this embodiment of the invention is not limited to this. Figure 2 As shown, this operational risk assessment method based on multidimensional data includes the following operations:

[0132] 201. Obtain the operating information of the target device, including basic attribute information, real-time status information, and wear and tear maintenance information.

[0133] 202. Based on the operational information, determine whether the target equipment meets the preset basic operational evaluation conditions.

[0134] 203. When it is determined that the target equipment meets the basic operation assessment conditions, the operation risk assessment result corresponding to the target equipment is determined based on the operation information and the preset operation assessment conditions.

[0135] 204. Based on the operational risk assessment results, determine the risk management measures required for the target equipment.

[0136] 205. When the risk handling status is used to indicate that the target equipment meets the preset risk handling conditions, the target risk handling type corresponding to the target equipment is determined based on the operational risk assessment results and the set risk handling analysis information.

[0137] Optionally, the target risk treatment type can be type information reflecting the specific risk location of the target device, type information reflecting the risk severity of the target device, type information reflecting the risk treatment configuration of the target device, type information reflecting the risk attribute of the target device, type information reflecting the risk treatment strategy of the target device, etc., and the embodiments of the present invention do not limit it.

[0138] 206. Based on the target risk treatment type, operational information, and operational risk assessment results, determine the risk treatment information corresponding to the target equipment.

[0139] 207. Based on the risk processing information, perform operational risk processing operations on the target equipment to obtain the target equipment after operational risk processing.

[0140] In this embodiment of the invention, for other descriptions of steps 201-203, please refer to the other detailed descriptions of steps 101-103 in Embodiment 1. These descriptions will not be repeated in this embodiment of the invention.

[0141] As can be seen, the embodiments of the present invention can determine the operational risk assessment results of the equipment based on the equipment's operating information and operational assessment conditions, intelligently realizing the equipment operational risk assessment function. This is beneficial to improving the comprehensiveness and scientific nature of the equipment operational risk assessment method, thereby improving the accuracy and reliability of the determined operational risk assessment results, and thus improving the accuracy and reliability of equipment operational risk assessment. Furthermore, it is beneficial to improve the efficiency and convenience of determining the operational risk assessment results, thereby improving the efficiency and convenience of equipment operational risk assessment. In addition, it can also provide equipment risk processing functions, enriching the intelligent functions of the multi-dimensional data-based operational risk assessment method, which is beneficial to improving the comprehensiveness and rationality of the multi-dimensional data-based operational risk assessment method, thereby improving the real-time nature of equipment risk monitoring and the timeliness of operation and maintenance, and thus improving the operational stability and reliability of the equipment.

[0142] Example 3

[0143] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of an operational risk assessment device based on multidimensional data disclosed in an embodiment of the present invention. Figure 3 The described apparatus may include a server, wherein the server includes a local server or a cloud server, and the embodiments of the present invention are not limited thereto. Figure 3 As shown, the operational risk assessment device based on multidimensional data may include:

[0144] The acquisition module 301 is used to acquire the operating information of the target device, including basic attribute information, real-time status information, and wear and maintenance information.

[0145] The judgment module 302 is used to determine whether the target device meets the preset basic operation evaluation conditions based on the operation information.

[0146] The risk assessment module 303 is used to determine the operational risk assessment result of the target equipment based on the operational information and the preset operational assessment conditions when the judgment module 302 determines that the target equipment meets the basic operational assessment conditions.

[0147] It is evident that implementation Figure 3The described multi-dimensional data-based operational risk assessment device can determine the operational risk assessment results of equipment based on its operational information and operational assessment conditions. This intelligently realizes the operational risk assessment function, which helps improve the comprehensiveness and scientific nature of the operational risk assessment method, thereby improving the accuracy and reliability of the determined operational risk assessment results. Furthermore, it also helps improve the efficiency and convenience of determining the operational risk assessment results.

[0148] In an optional embodiment, the risk assessment module 303 determines the operational risk assessment result corresponding to the target device based on operational information and preset operational assessment conditions in the following specific ways:

[0149] Based on basic attribute information, real-time status information, and preset health index assessment conditions, determine the health index assessment result corresponding to the target device;

[0150] Based on the wear and tear maintenance information and the preset aging index assessment conditions, determine the aging index assessment result corresponding to the target equipment.

[0151] Based on the health index assessment results, aging index assessment results, and preset index risk assessment conditions, the operational risk assessment results corresponding to the target equipment are determined.

[0152] It is evident that implementation Figure 4 The described device can determine the health index assessment results and aging index assessment results, and then determine the operational risk assessment results. Matching different equipment information types with corresponding index assessment conditions helps to improve the comprehensiveness, scientificity and pertinence of the method for determining operational risk assessment results, thereby improving the accuracy and reliability of the determined index assessment results, and thus improving the accuracy and reliability of the determined operational risk assessment results.

[0153] In another optional embodiment, the risk assessment module 303 determines the health index assessment result corresponding to the target device based on basic attribute information, real-time status information, and preset health index assessment conditions in the following specific ways:

[0154] Based on the basic attribute information and the preset first sub-evaluation conditions, determine the first health index evaluation result corresponding to the target device;

[0155] Based on real-time status information and preset second sub-evaluation conditions, determine the second health index evaluation result corresponding to the target device;

[0156] Based on the results of the first health index assessment, the results of the second health index assessment, and the preset health index weight calculation conditions, the health index assessment result corresponding to the target device is calculated.

[0157] It is evident that implementation Figure 4 The described device can also determine the first health index assessment result and the second health index assessment result, and then calculate the health index assessment result of the device. According to the matching sub-assessment conditions, the device performs sub-health index assessment result determination operations on the basic attribute information and real-time status information, which helps to improve the comprehensiveness, rationality and scientific nature of the health index assessment result determination method, and thus helps to improve the accuracy and reliability of the determined first health index assessment result and the second health index assessment result, thereby helping to improve the accuracy and reliability of the determined device health index assessment result.

[0158] In another optional embodiment, the risk assessment module 303 determines the operational risk assessment result corresponding to the target equipment based on the health index assessment result, the aging index assessment result, and preset index risk assessment conditions in the following specific ways:

[0159] Based on the health index assessment results, aging index assessment results, and the established risk weight assessment conditions, calculate the operational risk index corresponding to the target equipment;

[0160] Based on the operational risk index and the established risk level analysis conditions, the operational risk level corresponding to the target equipment is determined, which serves as the operational risk assessment result for the target equipment.

[0161] It is evident that implementation Figure 4 The described device can also combine risk weight assessment conditions and risk level analysis conditions to determine the operational risk assessment results of the equipment, which helps to improve the comprehensiveness and rationality of the operational risk assessment results, thereby improving the observability, intuitiveness and simplicity of the operational risk assessment results, and thus improving the practicality and callability of the operational risk assessment results.

[0162] In another optional embodiment, the risk assessment module 303 is further configured to determine whether the health index assessment result matches the aging index assessment result before calculating the operating risk index corresponding to the target equipment based on the health index assessment result, the aging index assessment result and the risk weight assessment condition.

[0163] When it is determined that the health index assessment result matches the aging index assessment result, perform the above-mentioned operation of calculating the operating risk index corresponding to the target equipment based on the health index assessment result, the aging index assessment result and the risk weight assessment conditions.

[0164] When it is determined that the health index assessment result does not match the aging index assessment result, the basic attribute information, real-time status information and wear and tear maintenance information are analyzed to obtain the operational correlation degree, and it is determined whether the operational correlation degree is greater than or equal to the preset operational correlation degree threshold.

[0165] When it is determined that the operational correlation is greater than or equal to the operational correlation threshold, the evaluation feedback information corresponding to the target device is obtained, and the target index evaluation result is selected from the health index evaluation result and aging index evaluation result based on the evaluation feedback information; the operational risk index corresponding to the target device is calculated based on the target index evaluation result and the risk weight evaluation conditions; and the above-mentioned operation of determining the operational risk level corresponding to the target device based on the operational risk index and the set risk level analysis conditions is performed, which is used as the operational risk evaluation result corresponding to the target device.

[0166] When it is determined that the operational correlation is less than the operational correlation threshold, the above-mentioned operation of calculating the operational risk index corresponding to the target equipment based on the health index assessment results, aging index assessment results, and risk weight assessment conditions is performed.

[0167] It is evident that implementation Figure 4 The described device can also perform similarity verification between health index assessment results and aging index assessment results, and introduce evaluation feedback information to determine the operational risk assessment results. It takes into account more influencing factors in determining the operational risk assessment results, which is conducive to improving the comprehensiveness, rationality and scientific nature of the operational risk assessment method based on multidimensional data. In turn, it is conducive to improving the diversity, flexibility and selectivity of the method for determining operational risk assessment results, thereby improving the accuracy and reliability of the determined operational risk assessment results, and also helps to reduce unnecessary waste of assessment resources.

[0168] In another optional embodiment, the risk assessment module 303 determines whether the health index assessment result matches the aging index assessment result by specifically including:

[0169] By analyzing the health index assessment results, the first predicted risk category corresponding to the target equipment is obtained, and by analyzing the aging index assessment results, the second predicted risk category corresponding to the target equipment is obtained.

[0170] Based on the first predicted risk category and the second predicted risk category, determine the corresponding risk similarity and determine whether the risk similarity is greater than or equal to the preset risk similarity threshold.

[0171] When the risk similarity is determined to be greater than or equal to the risk similarity threshold, the health index assessment result is determined to match the aging index assessment result.

[0172] When the risk similarity is determined to be less than the risk similarity threshold, it is determined that the health index assessment result and the aging index assessment result do not match.

[0173] The first and second risk prediction categories each include one or more of the following: the degree of risk prediction, the type of risk prediction, and the equipment information corresponding to the risk prediction.

[0174] It is evident that implementation Figure 4 The described device can also determine the predicted risk range corresponding to the health index assessment results and the aging index assessment results, and determine the risk similarity corresponding to different predicted risk ranges. Based on the comparison between the risk similarity and the risk similarity threshold, the matching situation between the health index assessment results and the aging index assessment results is determined. This helps to improve the rationality and scientific nature of the method for determining the matching situation of assessment results, thereby improving the accuracy and reliability of the determined matching situation of assessment results, as well as improving the efficiency and convenience of determining the matching situation of assessment results.

[0175] In yet another alternative embodiment, such as Figure 4 As shown, the device may further include:

[0176] The determination module 304 is used to determine the risk handling status corresponding to the target equipment based on the operation risk assessment results; when the risk handling status indicates that the target equipment meets the preset risk handling conditions, the target risk handling type corresponding to the target equipment is determined based on the operation risk assessment results and the set risk handling analysis information; and the risk handling information corresponding to the target equipment is determined based on the target risk handling type, operation information and operation risk assessment results.

[0177] The risk processing module 305 is used to perform operational risk processing operations on the target device based on the risk processing information, so as to obtain the target device after operational risk processing.

[0178] It is evident that implementation Figure 4 The described device can also provide equipment risk processing functions, enriching the intelligent functions of operation risk assessment methods based on multi-dimensional data. This is conducive to improving the comprehensiveness and rationality of operation risk assessment methods based on multi-dimensional data, thereby improving the real-time nature of equipment risk monitoring and the timeliness of operation and maintenance, and thus improving the stability and reliability of equipment operation.

[0179] Example 4

[0180] Please see Figure 5 , Figure 5 This is a schematic diagram of another operational risk assessment device based on multidimensional data disclosed in an embodiment of the present invention. Figure 5The described apparatus may include a server, wherein the server includes a local server or a cloud server, and the embodiments of the present invention are not limited thereto. Figure 5 As shown, the device may include:

[0181] Memory 401 storing executable program code;

[0182] Processor 402 coupled to memory 401;

[0183] Furthermore, it may also include an input interface 403 coupled to the processor 402 and an output interface 404;

[0184] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the multidimensional data-based operational risk assessment method described in Embodiment 1 or Embodiment 2.

[0185] Example 5

[0186] This invention discloses a computer storage medium that stores a computer program for electronic data interchange, wherein the computer program causes a computer to execute the steps in the multidimensional data-based operational risk assessment method described in Embodiment 1 or Embodiment 2.

[0187] Example 6

[0188] This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the multidimensional data-based operational risk assessment method described in Embodiment 1 or Embodiment 2.

[0189] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. 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.

[0190] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method 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, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0191] Finally, it should be noted that the operational risk assessment method and apparatus based on multidimensional data disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention 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 the present invention.

Claims

1. A method for operational risk assessment based on multidimensional data, characterized in that, The method includes: Obtain the operating information of the target device, including basic attribute information, real-time status information, and wear and tear maintenance information; Based on the operational information, determine whether the target device meets the preset basic operational evaluation conditions; When it is determined that the target device meets the basic operation evaluation conditions, the health index evaluation result corresponding to the target device is determined based on the basic attribute information, the real-time status information and the preset health index evaluation conditions. Based on the wear and tear maintenance information and the preset aging index evaluation conditions, the aging index evaluation result corresponding to the target equipment is determined. Determine whether the health index assessment results match the aging index assessment results; When it is determined that the health index assessment result matches the aging index assessment result, the operation of calculating the operating risk index corresponding to the target equipment based on the health index assessment result, the aging index assessment result, and the risk weight assessment conditions is performed. When it is determined that the health index assessment result does not match the aging index assessment result, the basic attribute information, the real-time status information and the wear and tear maintenance information are analyzed to obtain the operation correlation degree, and it is determined whether the operation correlation degree is greater than or equal to the preset operation correlation degree threshold. When it is determined that the operational correlation degree is greater than or equal to the operational correlation degree threshold, the evaluation feedback information corresponding to the target device is obtained, and the target index evaluation result is selected from the health index evaluation result and the aging index evaluation result based on the evaluation feedback information; the operational risk index corresponding to the target device is calculated based on the target index evaluation result and the risk weight evaluation conditions. When it is determined that the operational correlation is less than the operational correlation threshold, the operational risk index corresponding to the target equipment is calculated based on the health index assessment result, the aging index assessment result, and the set risk weight assessment conditions. Based on the operational risk index and the set risk level analysis conditions, the operational risk level corresponding to the target equipment is determined, which serves as the operational risk assessment result for the target equipment. And, the determination of whether the health index assessment result matches the aging index assessment result includes: By analyzing the health index assessment results, a first predicted risk category corresponding to the target device is obtained, and by analyzing the aging index assessment results, a second predicted risk category corresponding to the target device is obtained. Based on the first predicted risk category and the second predicted risk category, the corresponding risk similarity is determined, and it is determined whether the risk similarity is greater than or equal to a preset risk similarity threshold. When it is determined that the risk similarity is greater than or equal to the risk similarity threshold, it is determined that the health index assessment result matches the aging index assessment result; When it is determined that the risk similarity is less than the risk similarity threshold, it is determined that the health index assessment result does not match the aging index assessment result. The first and second predicted risk categories each include one or more of the following: the predicted risk level, the predicted risk type attribute, and the equipment information corresponding to the predicted risk.

2. The operational risk assessment method based on multidimensional data according to claim 1, characterized in that, The step of determining the health index assessment result corresponding to the target device based on the basic attribute information, the real-time status information, and preset health index assessment conditions includes: Based on the basic attribute information and the preset first sub-evaluation conditions, the first health index evaluation result corresponding to the target device is determined; Based on the real-time status information and the preset second sub-evaluation conditions, the second health index evaluation result corresponding to the target device is determined; Based on the first health index assessment result, the second health index assessment result, and the preset health index weight calculation conditions, the health index assessment result corresponding to the target device is calculated.

3. The operational risk assessment method based on multidimensional data according to claim 1, characterized in that, The method further includes: Based on the operational risk assessment results, determine the risk management situation corresponding to the target equipment. When the risk handling status indicates that the target device meets the preset risk handling conditions, the target risk handling type corresponding to the target device is determined based on the operational risk assessment results and the set risk handling analysis information. Based on the target risk handling type, the operational information, and the operational risk assessment results, determine the risk handling information corresponding to the target device; Based on the risk processing information, an operational risk processing operation is performed on the target device to obtain the target device after operational risk processing.

4. An operational risk assessment device based on multidimensional data, characterized in that, The device includes: The acquisition module is used to acquire the operating information of the target device, including basic attribute information, real-time status information, and wear and maintenance information. The judgment module is used to determine whether the target device meets the preset basic operation evaluation conditions based on the operation information. The risk assessment module is used to determine the health index assessment result corresponding to the target device based on the basic attribute information, the real-time status information, and preset health index assessment conditions when the judgment module determines that the target device meets the basic operation assessment conditions; determine the aging index assessment result corresponding to the target device based on the wear and tear maintenance information and preset aging index assessment conditions; determine whether the health index assessment result matches the aging index assessment result; when the health index assessment result matches the aging index assessment result, execute the operation of calculating the operation risk index corresponding to the target device based on the health index assessment result, the aging index assessment result, and risk weight assessment conditions; when the health index assessment result does not match the aging index assessment result, analyze the basic attribute information, the real-time status information, and the wear and tear maintenance information. The system obtains the operational correlation degree and determines whether the operational correlation degree is greater than or equal to a preset operational correlation degree threshold. When the operational correlation degree is determined to be greater than or equal to the operational correlation degree threshold, it acquires the received evaluation feedback information corresponding to the target device and, based on the evaluation feedback information, filters the target index evaluation result from the health index evaluation result and the aging index evaluation result. Based on the target index evaluation result and risk weight evaluation conditions, it calculates the operational risk index corresponding to the target device. When the operational correlation degree is determined to be less than the operational correlation threshold, it calculates the operational risk index corresponding to the target device based on the health index evaluation result, the aging index evaluation result, and the set risk weight evaluation conditions. Based on the operational risk index and the set risk level analysis conditions, it determines the operational risk level corresponding to the target device, which is used as the operational risk evaluation result corresponding to the target device. Furthermore, the specific methods by which the risk assessment module determines whether the health index assessment result matches the aging index assessment result include: By analyzing the health index assessment results, a first predicted risk category corresponding to the target device is obtained, and by analyzing the aging index assessment results, a second predicted risk category corresponding to the target device is obtained. Based on the first predicted risk category and the second predicted risk category, the corresponding risk similarity is determined, and it is determined whether the risk similarity is greater than or equal to a preset risk similarity threshold. When it is determined that the risk similarity is greater than or equal to the risk similarity threshold, it is determined that the health index assessment result matches the aging index assessment result; When it is determined that the risk similarity is less than the risk similarity threshold, it is determined that the health index assessment result does not match the aging index assessment result. The first and second predicted risk categories each include one or more of the following: the predicted risk level, the predicted risk type attribute, and the equipment information corresponding to the predicted risk.

5. An operational risk assessment device based on multidimensional data, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the operational risk assessment method based on multidimensional data as described in any one of claims 1-3.

6. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the operational risk assessment method based on multidimensional data as described in any one of claims 1-3.

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