Device evaluation method, apparatus, device, and storage medium
By acquiring the characteristic parameters of the equipment, identifying abnormal characteristic parameters, and correcting their weights, the inaccuracy caused by the failure to consider the balance of components in equipment evaluation is solved, thus achieving a more accurate assessment of equipment health.
Patent Information
- Application Number
- CN202211510987.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-11-29
- Publication Date
- 2026-03-03
- Estimated Expiration
- 2042-11-29
AI Technical Summary
In the existing equipment fault diagnosis process, the equipment operating environment is complex, making it difficult to accurately assess key equipment and key components using a single characteristic parameter. The lack of consideration for the balance of each component leads to inaccurate assessment results.
By acquiring the characteristic parameters of the target device, identifying abnormal characteristic parameters, calculating the variable weight constant and correcting the weight, the target weight is obtained, the device health is calculated, and the evaluation result is output.
This improves the accuracy of equipment assessment, making equipment health status more reflective of its true condition and enhancing the overall precision of equipment assessment.
Smart Images
Figure CN115718887B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of equipment evaluation technology, specifically to an equipment evaluation method, apparatus, device, and storage medium. Background Technology
[0002] Currently, in existing equipment fault diagnosis processes, fault diagnosis results of one or several types of critical equipment and components are usually used as fault diagnosis assessment results. However, due to the complexity of the equipment operating environment, it is difficult to achieve fault diagnosis assessment of critical equipment and components through a single characteristic parameter. Furthermore, the balance of each component is not considered during the detection process, which may lead to serious abnormalities in a certain characteristic parameter of the equipment component. However, the weight of this parameter is small, and the overall equipment assessment result cannot reflect the true state of the equipment, thus resulting in inaccurate equipment assessment results. Summary of the Invention
[0003] This application provides a device evaluation method, apparatus, equipment, and storage medium, aiming to solve the technical problem of inaccurate device fault diagnosis and evaluation results in the prior art.
[0004] On one hand, embodiments of this application provide a device evaluation method, which includes the following steps:
[0005] In response to equipment evaluation requests, obtain the characteristic parameters of each component in the target equipment;
[0006] If there are abnormal feature parameters that exceed the preset defect threshold, then the variable weight constant of the abnormal feature parameters is obtained;
[0007] The initial weights of each feature parameter are adjusted according to the weighting constant and the abnormal feature parameters to obtain the target weights of each feature parameter.
[0008] The device health score of the target device is calculated based on the feature parameters and the target weights of the feature parameters, and the device evaluation result corresponding to the device health score is output.
[0009] In one possible implementation of this application, the step of obtaining the variable weight constant of the abnormal feature parameter if there is an abnormal feature parameter exceeding a preset defect threshold includes:
[0010] Access the threshold database, obtain the defect threshold associated with the feature parameter, and compare the feature parameter and the defect threshold;
[0011] If the feature parameter exceeds the defect threshold, then the feature parameter is determined to be an abnormal feature parameter;
[0012] Read the feature type of the abnormal feature parameter, and obtain the variable weight constant associated with the feature type. The variable weight constant includes key variable weight constant and equilibrium variable weight constant.
[0013] In one possible implementation of this application, the step of performing weight transformation processing on the initial weights based on the weight transformation constants and the abnormal feature parameters to obtain the target weights of each feature parameter includes:
[0014] Obtain the initial weight of each feature parameter in the target device;
[0015] The abnormal feature parameters, the balance constant of the abnormal feature parameters, the feature parameters and the initial weights of the feature parameters are input into a preset weighting function model for weighting processing to generate the target weights of each feature parameter.
[0016] In one possible implementation of this application, the step of calculating the device health of the target device based on the feature parameters and the target weights of the feature parameters, and outputting the device evaluation result corresponding to the device health, includes:
[0017] Obtain each of the aforementioned feature parameters and the target weight of each of the aforementioned feature parameters, and perform weighted processing on the feature parameters according to the target weight to obtain the feature health of each feature parameter;
[0018] The device health score of the target device is obtained by summing the health scores of each feature of the target device.
[0019] Obtain the device assessment results associated with the device health status, and output the device assessment results.
[0020] In one possible implementation of this application, the step of calculating the device health of the target device based on the feature parameters and the target weights of the feature parameters, and outputting the device evaluation result corresponding to the device health, includes:
[0021] The sum of the feature health scores for each feature parameter is calculated to obtain the device health score of the target device.
[0022] Obtain the health intervals of each device associated with the target device, and the device health threshold corresponding to each health interval;
[0023] The target device is evaluated based on the device health status and the device health threshold, and the evaluation result of the target device is output.
[0024] In one possible implementation of this application, the step of evaluating the target device based on the device health level and the device health threshold, and outputting the device evaluation result of the target device, includes:
[0025] Read the device health threshold corresponding to the device health range, wherein the device health threshold includes a first health threshold and a second health threshold, and the first health threshold is less than the second health threshold;
[0026] If the health status of the target device is greater than the first health threshold and less than the second health threshold, then the device health level associated with the device health interval is set as the target health level of the target device.
[0027] Generate and output the device assessment results associated with the target health level.
[0028] In one possible implementation of this application, the step of outputting the device evaluation result corresponding to the device health status includes:
[0029] Obtain the target health level corresponding to the device health status, and determine the component evaluation result of each device component in the target device based on the target health level and the component health status of the device components;
[0030] Based on the target health level and the component evaluation results, generate the device evaluation result for the target device, and output the device evaluation result.
[0031] On the other hand, this application provides an equipment evaluation apparatus, the equipment evaluation apparatus comprising:
[0032] The feature acquisition module is configured to respond to a device evaluation request and acquire the feature parameters of each device component in the target device.
[0033] The constant acquisition module is configured to acquire the variable weight constant of the abnormal feature parameter if there is an abnormal feature parameter that exceeds a preset defect threshold.
[0034] The variable weight calculation module is configured to perform variable weight processing on the initial weights of each of the feature parameters according to the variable weight constant and the abnormal feature parameters, so as to obtain the target weights of each of the feature parameters.
[0035] The equipment evaluation module is configured to calculate the equipment health of the target equipment based on the feature parameters and the target weights of the feature parameters, and output the equipment evaluation result corresponding to the equipment health.
[0036] On the other hand, this application also provides an equipment evaluation device, the equipment evaluation device comprising:
[0037] One or more processors;
[0038] Memory; and
[0039] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the device evaluation method.
[0040] On the other hand, this application also provides a computer-readable storage medium having a computer program stored thereon, the computer program being loaded by a processor to perform the steps in the device evaluation method.
[0041] In this application, by responding to a device evaluation request, the system acquires characteristic parameters of each component in the target device. If any abnormal characteristic parameter exceeds a preset defect threshold, the system acquires the variable weight constant of the abnormal characteristic parameter. Based on the variable weight constant and the abnormal characteristic parameter, the initial weights of each characteristic parameter are reweighted to obtain the target weights of each characteristic parameter. The system then calculates the device health of the target device based on the characteristic parameters and their target weights, and outputs the device evaluation result corresponding to the device health. This system corrects the weights of the acquired characteristic parameters, making the device health of the target device more accurately reflect its true state and improving the overall accuracy of the device evaluation. Attached Figure Description
[0042] To more clearly illustrate the technical solutions in the embodiments of this application, 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.
[0043] Figure 1 This is a schematic diagram illustrating a scenario of the device evaluation method in an embodiment of this application;
[0044] Figure 2 This is a flowchart illustrating one embodiment of the device evaluation method in this application.
[0045] Figure 3 A flowchart illustrating an embodiment of the device evaluation method for determining the device evaluation result of a target device provided in this application;
[0046] Figure 4 This is a schematic flowchart of another embodiment of the device evaluation method provided in this application for evaluating a target device and obtaining a device evaluation result.
[0047] Figure 5 This is a schematic diagram of the structure of one embodiment of the device evaluation apparatus provided in this application;
[0048] Figure 6This is a schematic diagram of one embodiment of the device evaluation device provided in this application. Detailed Implementation
[0049] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. 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.
[0050] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.
[0051] In this application, the term "exemplary" is used to mean "serving as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.
[0052] Currently, in existing equipment fault diagnosis processes, fault diagnosis results of one or several types of critical equipment and components are usually used as fault diagnosis assessment results. However, due to the complexity of the equipment operating environment, it is difficult to achieve fault diagnosis assessment of critical equipment and components through a single characteristic parameter. Furthermore, the balance of each component is not considered during the detection process, which may lead to serious abnormalities in a certain characteristic parameter of the equipment component. However, the weight of this parameter is small, and the overall equipment assessment result cannot reflect the true state of the equipment, thus resulting in inaccurate equipment assessment results.
[0053] Based on this, this application proposes a method, apparatus, device, and computer-readable storage medium for equipment evaluation, in order to solve the technical problem of inaccurate equipment fault diagnosis and evaluation results in the prior art.
[0054] The device evaluation method in this embodiment of the invention is applied to a device evaluation apparatus, which is configured in a device evaluation device. The device evaluation device includes one or more processors, a memory, and one or more application programs. The one or more application programs are stored in the memory and configured to be executed by the processor to implement the device evaluation method. The device evaluation device can be a smart terminal, such as a mobile phone, tablet computer, network device, and smart computer. Optionally, the device evaluation device can also be a server or a service cluster composed of multiple servers.
[0055] like Figure 1 As shown, Figure 1 This is a schematic diagram of a scenario for the equipment evaluation method according to an embodiment of this application. In this embodiment, the equipment evaluation scenario includes an equipment evaluation device 100 (which integrates an equipment evaluation apparatus) and a monitored target device 200. The equipment evaluation device 100 runs a computer-readable storage medium corresponding to the equipment evaluation method to execute the steps of the equipment evaluation method. The target device 200 can be an industrial device or a smart device supporting business operations.
[0056] Understandable, Figure 1 The equipment evaluation equipment in the equipment evaluation method scenario shown, or the devices included in the equipment evaluation equipment, do not constitute a limitation on the embodiments of the present invention. That is, the number or type of equipment in the equipment evaluation equipment in the equipment evaluation method scenario, or the number or type of devices included in each equipment, do not affect the overall implementation of the technical solution in the embodiments of the present invention, and can all be considered as equivalent substitutions or derivatives of the technical solutions claimed in the embodiments of the present invention.
[0057] In this embodiment of the invention, the equipment evaluation device 100 is mainly used for: responding to an equipment evaluation request and obtaining each characteristic parameter of each equipment component in the target equipment; if there is an abnormal characteristic parameter that exceeds a preset defect threshold, obtaining the variable weight constant of the abnormal characteristic parameter; performing variable weight processing on the initial weight of each characteristic parameter according to the variable weight constant and the abnormal characteristic parameter to obtain the target weight of each characteristic parameter; calculating the equipment health of the target equipment according to the characteristic parameter and the target weight of the characteristic parameter, and outputting the equipment evaluation result corresponding to the equipment health.
[0058] In this embodiment of the invention, the device evaluation device 100 can be an independent device evaluation device, such as a mobile phone, tablet computer, network device, server, and smart computer, or it can be a device evaluation network or device evaluation cluster composed of multiple device evaluation devices.
[0059] This application provides a device evaluation method, apparatus, device, and computer-readable storage medium, which will be described in detail below.
[0060] It will be understood by those skilled in the art that Figure 1 The application environment shown is only one application scenario related to the solution of this application and does not constitute a limitation on the application scenario of this application. Other application environments may include more than one application scenario. Figure 1 The more or fewer devices shown are used to evaluate the devices, or the devices are used to evaluate network connectivity, for example... Figure 1 Only one device evaluation device is shown in the document. It is understood that the scenario of this device evaluation method may also include one or more device evaluation devices, which are not specifically limited here. The device evaluation device may also include a memory for storing feature parameters and other data.
[0061] It should be noted that, Figure 1 The schematic diagram of the equipment evaluation method shown is merely an example. The scenarios of the equipment evaluation method described in the embodiments of the present invention are intended to more clearly illustrate the technical solutions of the embodiments of the present invention and do not constitute a limitation on the technical solutions provided in the embodiments of the present invention.
[0062] Based on the scenarios described above regarding equipment evaluation methods, various embodiments of the equipment evaluation method disclosed in this invention are proposed.
[0063] like Figure 2 As shown, Figure 2 This is a flowchart illustrating one embodiment of the device evaluation method in this application. The device evaluation method includes the following steps 201 to 204:
[0064] 201. Respond to the equipment evaluation request and obtain the characteristic parameters of each component in the target equipment;
[0065] The device evaluation method in this embodiment is applied to a device evaluation device. The type and number of device evaluation devices are not specifically limited. That is, the device evaluation device can be one or more smart terminals or servers. In a specific embodiment, the device evaluation device is a smart computer.
[0066] Specifically, the device evaluation device is configured to communicate with the target device and monitor the target device, obtain at least one characteristic parameter of each device component in the monitored device, perform weighting processing on the initial weight of the characteristic parameter to obtain the target weight of the characteristic parameter, and calculate the device health of the device component and the target device through the characteristic parameter and the target weight, thereby obtaining the device evaluation result corresponding to the device health.
[0067] Specifically, during operation, the equipment evaluation device acquires a device evaluation request. This request is an operational instruction that drives the device evaluation device to perform a device evaluation on the target device, thereby determining the target device's operational status. The triggering method for this evaluation request is not specifically limited here; that is, the device evaluation request can be actively triggered by the user, for example, by a device maintenance personnel clicking the device monitoring button on the device evaluation device. Optionally, the device evaluation request can also be automatically triggered by the device evaluation device. For example, the device evaluation device may be pre-set with an automatic evaluation process, automatically acquiring the characteristic parameters of each target device within a preset time period and generating a device evaluation request.
[0068] Specifically, upon receiving a device evaluation request, the device evaluation equipment responds to the request and reads the characteristic parameters of each component in the target device. These characteristic parameters are key parameters characterizing the operating status of the target device or component. In one specific embodiment, the characteristic parameters may be temperature, pressure, speed, kurtosis, and other operating parameters affecting the device's operating status. Optionally, depending on the application scenario and device type, the user can pre-set the number and type of characteristic parameters used for subsequent device evaluation.
[0069] 202. If there are abnormal feature parameters that exceed a preset defect threshold, then obtain the variable weight constant of the abnormal feature parameters;
[0070] Specifically, after acquiring the characteristic parameters of each component in the target equipment, the equipment evaluation equipment analyzes these characteristic parameters, determines whether they are abnormal characteristic parameters that deviate significantly from the normal value, and decides whether to perform weighting processing on these characteristic parameters. This ensures the balance between the characteristic parameters and avoids situations where a certain characteristic parameter deviates from the normal value and has a small initial weight, causing the equipment evaluation results to fail to reflect the true operating status of the target equipment.
[0071] Specifically, before responding to an equipment evaluation request, the equipment evaluation device pre-generates a threshold database and generates defect thresholds for each characteristic parameter of the target equipment. These defect thresholds represent threshold data indicating that the characteristic parameter is in an abnormal state, deviating from its normal value. The equipment evaluation device then associates the defect threshold corresponding to the characteristic parameter with that characteristic parameter and stores it in the threshold database.
[0072] The equipment evaluation equipment associates the defect threshold corresponding to the feature parameter with the feature parameter and stores it in the threshold database.
[0073] Specifically, after obtaining the characteristic parameters of the target device, the equipment evaluation equipment accesses the threshold database, obtains the defect threshold associated with the characteristic parameter, and compares the characteristic parameter with the defect threshold to determine the parameter status of the characteristic parameter.
[0074] Optionally, if any of the feature parameters exceeds the defect threshold, the equipment evaluation equipment determines that the parameter status of the feature parameter is an abnormal feature status that is seriously deviating from the normal value, and determines that the feature parameter is an abnormal feature parameter.
[0075] After detecting an abnormal feature parameter that exceeds the defect threshold, the equipment evaluation equipment further reads the feature type of the abnormal feature parameter and determines the variable weight constant of the abnormal feature parameter through the feature type.
[0076] Specifically, after power-on, the equipment evaluation equipment pre-classifies the characteristic types of each characteristic parameter of the target device based on their varying degrees of influence on the device's health. The characteristic type can be categorized as either a critical characteristic type or a balanced characteristic type. A critical characteristic type represents a parameter that significantly impacts the device's health, while a balanced characteristic type represents a parameter that has a relatively minor impact. Optionally, in one specific embodiment, the characteristic parameters include speed, temperature exceeding a threshold, kurtosis value, and parameter exceeding a threshold. The characteristics of speed and temperature exceeding a threshold are considered balanced characteristic types, while the characteristics of kurtosis value and parameter exceeding a threshold are considered critical characteristic types.
[0077] After obtaining the feature type of the abnormal feature parameter, the equipment evaluation equipment acquires the corresponding variable weight constant. Different feature types correspond to different variable weight constants. These variable weight constants include key variable weight constants and equilibrium variable weight constants. The key variable weight constant corresponds to the key feature type and is used to adjust the initial weights of each feature parameter; it is a constant with a value range of (0, 0.5). The equilibrium variable weight constant corresponds to the feature parameter of the equilibrium variable weight type and is used to adjust the initial weights of each feature parameter; it is a constant with a value range of (0.5, 1).
[0078] 203. Perform weight transformation on the initial weights of each feature parameter according to the weight transformation constant and the abnormal feature parameter to obtain the target weights of each feature parameter;
[0079] After obtaining the abnormal feature parameters and the corresponding variable weight constants, the equipment evaluation equipment performs variable weight processing on the initial weights of each feature parameter of the target equipment according to the variable weight constants and the abnormal feature parameters, thereby obtaining the updated target weights of each feature parameter, thus improving the accuracy of subsequent equipment health calculations.
[0080] Specifically, the equipment evaluation equipment is pre-set with a variable weighting function model that adjusts the initial weights of the target equipment's feature parameters after detecting abnormal feature parameters. The formula for this variable weighting function model is as follows:
[0081]
[0082] Where, ρ ij x represents the target weight after the weighting adjustment. ij Let m be the j-th characteristic parameter of the i-th component of the target device, and m be the number of characteristic parameters of the target device or its components. is the initial weight of the feature parameters, and a is the variable weight constant of the abnormal feature parameters.
[0083] After obtaining the abnormal feature parameters and the corresponding variable weight constants, the equipment evaluation equipment uses the abnormal feature parameters, variable weight constants, initial weights of the abnormal feature parameters, each feature parameter of the target equipment and its initial weight as input to the variable weight function model. The initial weights of the feature parameters are then processed by the variable weight function model, and the equipment evaluation equipment obtains the target weights of each feature parameter output by the variable weight function model.
[0084] 204. Calculate the device health of the target device based on the feature parameters and the target weights of the feature parameters, and output the device evaluation result corresponding to the device health.
[0085] After obtaining the target weights of each feature parameter, the equipment evaluation equipment calculates the equipment health of the target equipment based on the target weights and the corresponding feature parameters, and outputs the equipment evaluation result corresponding to the equipment health.
[0086] Specifically, the equipment evaluation equipment obtains each feature parameter of the target device and the target weight of each feature parameter. The associated feature parameters are weighted using the target weight to obtain the feature health of each feature parameter of the target device.
[0087] Specifically, after acquiring the feature health score of each characteristic parameter of the target device, the equipment evaluation equipment summarizes these feature health scores to obtain the equipment health score of the target device. This equipment health score is an equipment evaluation parameter characterizing the operating status of the target device. Optionally, the calculation formula for the equipment health score is as follows:
[0088]
[0089] Among them, h i (t) represents the health status of the target device, m represents the number of characteristic parameters of the target device, and ρ ij For the characteristic parameter x j The target weight after the weighting is determined, and the range of the target weight is 0 ≤ ρ. ij ≤1 and
[0090] After obtaining the health status of the target device, the device evaluation device determines the device evaluation result based on the health status and displays the device evaluation result in the designated display area.
[0091] Optionally, in other embodiments, when calculating the device health of the target device, the device evaluation device also calculates the component health of each device component of the target device, generates the component evaluation result of the device component based on the component health, and outputs the component evaluation result and the device evaluation result.
[0092] In this embodiment, the equipment evaluation device, in response to an equipment evaluation request, acquires the characteristic parameters of each component in the target equipment. If any abnormal characteristic parameter exceeds a preset defect threshold, the device acquires the variable weight constant of the abnormal characteristic parameter. Based on the variable weight constant and the abnormal characteristic parameter, the device performs a variable weighting process on the initial weights of each characteristic parameter to obtain the target weight of each characteristic parameter. The device health of the target equipment is calculated based on the characteristic parameters and their target weights, and the equipment evaluation result corresponding to the device health is output. This process corrects the weights of the acquired characteristic parameters, making the device health of the target equipment more accurately reflect its true state and improving the overall accuracy of the equipment evaluation.
[0093] like Figure 3 As shown, Figure 3 A flowchart illustrating an embodiment of the equipment evaluation method for determining the equipment evaluation result of a target device provided in this application, specifically including steps 301 to 303:
[0094] 301. Calculate the sum of the feature health scores of each feature parameter to obtain the device health score of the target device;
[0095] 302. Obtain the health intervals of each device associated with the target device, and the device health threshold corresponding to each health interval;
[0096] 303. Perform an equipment evaluation on the target device based on the device health status and the device health threshold, and output the equipment evaluation result of the target device.
[0097] Based on the above embodiments, in this embodiment, the equipment evaluation device performs weighted processing on the feature parameters, obtains the sum of the feature health scores of each feature parameter, and then determines the equipment evaluation result of the target equipment based on the sum of the feature health scores.
[0098] Specifically, the equipment evaluation equipment pre-establishes equipment health intervals corresponding to different equipment evaluation states for the target equipment. Different equipment health thresholds are set for different equipment health intervals. Optionally, the equipment health threshold for each equipment health interval includes a first health threshold and a second health threshold, where the first health threshold is less than the second health threshold. Optionally, in a specific embodiment, the correspondence between the equipment health status of the target equipment and the equipment health intervals is shown in the following table:
[0099]
[0100]
[0101] Specifically, the equipment evaluation equipment reads the equipment health threshold corresponding to each equipment health interval of the target equipment, and compares the equipment health threshold with the equipment health of the target equipment to determine the equipment health interval of the target equipment and the corresponding equipment evaluation result.
[0102] Optionally, if the health status of the target device is greater than a first health threshold of a certain device health interval and less than a second health threshold of the same interval, then the device evaluation device determines that the health status of the target device falls within the device health interval.
[0103] After determining the health range of the target device, the equipment evaluation device determines the corresponding health level of the target device as the target health level. The equipment evaluation device then generates an evaluation result associated with the health range and health level, and displays the evaluation result in a designated display area or on a mobile terminal bound to the device. Optionally, in one specific embodiment, the evaluation result includes any one or more of the following: excellent health condition, suitable for long-term operation; good health condition, suitable for long-term operation; average health condition, showing minor or early signs of abnormal faults, requiring monitoring; poor health condition, showing obvious or mid-to-late stage signs of abnormal faults, requiring shutdown for maintenance. Optionally, maintenance personnel can also customize the equipment evaluation results associated with different health ranges according to actual application scenarios.
[0104] In this embodiment, the device evaluation device calculates the sum of the feature health scores of each feature parameter to obtain the device health score of the target device; it obtains each device health interval associated with the target device and the corresponding device health threshold for each device health interval; it performs device evaluation on the target device based on the device health score and the device health threshold, and outputs the device evaluation result of the target device. This achieves device evaluation of the target device based on the sum of the feature health scores of the feature parameters after variable weight correction, thus improving the accuracy of device evaluation.
[0105] like Figure 4 As shown, Figure 4 A flowchart illustrating another embodiment of the device evaluation method provided in this application for evaluating a target device and obtaining a device evaluation result, specifically including steps 401 to 402:
[0106] 401. Obtain the target health level corresponding to the health of the device, and determine the component evaluation result of each device component in the target device based on the target health level and the component health of the device component;
[0107] 402. Generate the equipment evaluation result of the target device based on the target health level and the component evaluation result, and output the equipment evaluation result.
[0108] Based on the above embodiments, in this embodiment, when the device evaluation device acquires the feature health degree of each feature parameter, calculates the device health degree of the target device based on the feature health degree, and determines the target health level of the target device, it also calculates the component health degree of each device component in the target device based on the device component identifier corresponding to the feature parameter, and determines the component evaluation result of the device component based on the target health level and the component health degree.
[0109] Specifically, the equipment evaluation equipment obtains the component health evaluation threshold for each equipment component corresponding to the target health level, and compares the component health status with the component health evaluation threshold to determine the component evaluation result. The component health evaluation threshold is the critical threshold for assessing whether the equipment component is faulty.
[0110] Optionally, if the health status of the component does not exceed the health assessment threshold of the component, then the component is determined to be in good operating condition, and the equipment assessment device generates a normal component assessment result.
[0111] Optionally, if the health status of a component exceeds the health assessment threshold for that component, then the characteristic parameters of the component are determined to be abnormal, i.e., the operating status of the component is abnormal, and the equipment assessment device generates an assessment result for the abnormal component.
[0112] After obtaining the component evaluation results of each equipment component, the equipment evaluation equipment generates the equipment evaluation result of the target equipment based on the target health level and the component evaluation result, and outputs the equipment evaluation result.
[0113] Specifically, the equipment evaluation device queries the overall equipment evaluation result corresponding to the target health level, and summarizes the overall equipment evaluation result and the component evaluation results of each equipment component to generate an equipment evaluation result that represents the overall operating status of the target equipment and the operating status of each component. The equipment evaluation result is then displayed in the designated display area of the equipment evaluation device or on the mobile terminal bound to the equipment evaluation device.
[0114] In this embodiment, the equipment evaluation device obtains the target health level corresponding to the equipment health level, determines the component evaluation result of each equipment component in the target equipment based on the target health level and the component health level of the equipment components, generates the equipment evaluation result of the target equipment based on the target health level and the component evaluation result, and outputs the equipment evaluation result. This achieves equipment evaluation of the target equipment from partial to overall, improving the integrity and accuracy of equipment evaluation.
[0115] To better implement the equipment evaluation method in the embodiments of this application, based on the equipment evaluation method, the embodiments of this application also provide an equipment evaluation apparatus, such as... Figure 5 As shown, Figure 5 This is a schematic diagram of one embodiment of the device evaluation apparatus provided in this application. The device evaluation apparatus 500 includes:
[0116] The feature acquisition module 501 is configured to acquire the feature parameters of each device component in the target device in response to the device evaluation request.
[0117] The constant acquisition module 502 is configured to acquire the variable weight constant of the abnormal feature parameter if there is an abnormal feature parameter that exceeds a preset defect threshold.
[0118] The variable weight calculation module 503 is configured to perform variable weight processing on the initial weights of each of the feature parameters according to the variable weight constant and the abnormal feature parameters, so as to obtain the target weights of each of the feature parameters.
[0119] The equipment evaluation module 504 is configured to calculate the equipment health of the target equipment based on the feature parameters and the target weights of the feature parameters, and output the equipment evaluation result corresponding to the equipment health.
[0120] In some embodiments of this application, if the equipment evaluation device has abnormal feature parameters exceeding a preset defect threshold, it acquires the variable weight constants of the abnormal feature parameters, including:
[0121] Access the threshold database, obtain the defect threshold associated with the feature parameter, and compare the feature parameter and the defect threshold;
[0122] If the feature parameter exceeds the defect threshold, then the feature parameter is determined to be an abnormal feature parameter;
[0123] Read the feature type of the abnormal feature parameter, and obtain the variable weight constant associated with the feature type. The variable weight constant includes key variable weight constant and equilibrium variable weight constant.
[0124] In some embodiments of this application, the device evaluation apparatus performs weight transformation processing on the initial weights based on the weight transformation constants and the abnormal feature parameters to obtain target weights for each feature parameter, including:
[0125] Obtain the initial weight of each feature parameter in the target device;
[0126] The abnormal feature parameters, the balance constant of the abnormal feature parameters, the feature parameters and the initial weights of the feature parameters are input into a preset weighting function model for weighting processing to generate the target weights of each feature parameter.
[0127] In some embodiments of this application, the device evaluation apparatus calculates the device health of the target device based on the feature parameters and the target weights of the feature parameters, and outputs the device evaluation result corresponding to the device health, including:
[0128] Obtain each of the aforementioned feature parameters and the target weight of each of the aforementioned feature parameters, and perform weighted processing on the feature parameters according to the target weight to obtain the feature health of each feature parameter;
[0129] The device health score of the target device is obtained by summing the health scores of each feature of the target device.
[0130] Obtain the device assessment results associated with the device health status, and output the device assessment results.
[0131] In some embodiments of this application, the device evaluation apparatus calculates the device health of the target device based on the feature parameters and the target weights of the feature parameters, and outputs the device evaluation result corresponding to the device health, including:
[0132] The sum of the feature health scores for each feature parameter is calculated to obtain the device health score of the target device.
[0133] Obtain the health intervals of each device associated with the target device, and the device health threshold corresponding to each health interval;
[0134] The target device is evaluated based on the device health status and the device health threshold, and the evaluation result of the target device is output.
[0135] In some embodiments of this application, the device evaluation apparatus performs a device evaluation on the target device based on the device health level and the device health threshold, and outputs the device evaluation result of the target device, including:
[0136] Read the device health threshold corresponding to the device health range, wherein the device health threshold includes a first health threshold and a second health threshold, and the first health threshold is less than the second health threshold;
[0137] If the health status of the target device is greater than the first health threshold and less than the second health threshold, then the device health level associated with the device health interval is set as the target health level of the target device.
[0138] Generate and output the device assessment results associated with the target health level.
[0139] In some embodiments of this application, the device evaluation apparatus outputs a device evaluation result corresponding to the device health status, including:
[0140] Obtain the target health level corresponding to the device health status, and determine the component evaluation result of each device component in the target device based on the target health level and the component health status of the device components;
[0141] Based on the target health level and the component evaluation results, generate the device evaluation result for the target device, and output the device evaluation result.
[0142] In this embodiment, the equipment evaluation device obtains the characteristic parameters of each equipment component in the target equipment by responding to the equipment evaluation request; if there are abnormal characteristic parameters that exceed a preset defect threshold, the device obtains the variable weight constant of the abnormal characteristic parameter; the device performs variable weight processing on the initial weight of each characteristic parameter according to the variable weight constant and the abnormal characteristic parameter to obtain the target weight of each characteristic parameter; the device health of the target equipment is calculated according to the characteristic parameter and the target weight of the characteristic parameter, and the device evaluation result corresponding to the device health is output to correct the weight of the obtained characteristic parameters, so that the device health of the target equipment can better reflect the true state of the target equipment and improve the overall equipment evaluation accuracy of the target equipment.
[0143] This invention also provides an equipment evaluation device, such as... Figure 6 As shown, Figure 6 This is a schematic diagram of one embodiment of the device evaluation device provided in this application.
[0144] The equipment evaluation device integrates any of the equipment evaluation apparatuses provided in the embodiments of the present invention, and the equipment evaluation device includes:
[0145] One or more processors;
[0146] Memory; and
[0147] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor as steps in the device evaluation method described in any of the embodiments of the above-described device evaluation method.
[0148] Specifically, the equipment evaluation equipment may include components such as a processor 601 with one or more processing cores, a memory 602 with one or more computer-readable storage media, a power supply 603, and an input unit 604. Those skilled in the art will understand that... Figure 6 The equipment evaluation device structure shown does not constitute a limitation on the equipment evaluation device. It may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:
[0149] The processor 601 is the control center of the device evaluation equipment. It connects various parts of the equipment evaluation equipment via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 602, and by calling data stored in the memory 602, it performs various functions and processes data, thereby providing overall monitoring of the equipment evaluation equipment. Optionally, the processor 601 may include one or more processing cores; preferably, the processor 601 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 601.
[0150] The memory 602 can be used to store software programs and modules. The processor 601 executes various functional applications and data processing by running the software programs and modules stored in the memory 602. The memory 602 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on device usage evaluation, etc. In addition, the memory 602 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 602 may also include a memory controller to provide the processor 601 with access to the memory 602.
[0151] The equipment evaluation device also includes a power supply 603 that supplies power to the various components. Preferably, the power supply 603 can be logically connected to the processor 601 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 603 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.
[0152] The device evaluation device may also include an input unit 604, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
[0153] Although not shown, the device evaluation device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 601 in the device evaluation device loads the executable files corresponding to the processes of one or more applications into the memory 602 according to the following instructions, and the processor 601 runs the applications stored in the memory 602 to realize various functions, as follows:
[0154] In response to equipment evaluation requests, obtain the characteristic parameters of each component in the target equipment;
[0155] If there are abnormal feature parameters that exceed the preset defect threshold, then the variable weight constant of the abnormal feature parameters is obtained;
[0156] The initial weights of each feature parameter are adjusted according to the weighting constant and the abnormal feature parameters to obtain the target weights of each feature parameter.
[0157] The device health score of the target device is calculated based on the feature parameters and the target weights of the feature parameters, and the device evaluation result corresponding to the device health score is output.
[0158] Therefore, embodiments of the present invention provide a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a magnetic disk or optical disk, etc. A computer program is stored thereon, which is loaded by a processor to execute the steps in any of the device evaluation methods provided in the embodiments of the present invention. For example, the computer program loaded by the processor can execute the following steps:
[0159] In response to equipment evaluation requests, obtain the characteristic parameters of each component in the target equipment;
[0160] If there are abnormal feature parameters that exceed the preset defect threshold, then the variable weight constant of the abnormal feature parameters is obtained;
[0161] The initial weights of each feature parameter are adjusted according to the weighting constant and the abnormal feature parameters to obtain the target weights of each feature parameter.
[0162] The device health score of the target device is calculated based on the feature parameters and the target weights of the feature parameters, and the device evaluation result corresponding to the device health score is output.
[0163] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the detailed descriptions of other embodiments above, which will not be repeated here.
[0164] In practice, each of the above units or structures can be implemented as an independent entity or can be arbitrarily combined to be implemented as the same or several entities. For the specific implementation of each of the above units or structures, please refer to the previous method embodiments, which will not be repeated here.
[0165] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.
[0166] The above provides a detailed description of a device evaluation method provided by the embodiments of this application. Specific embodiments have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.
Claims
1. A device evaluation method characterized by, The device evaluation method comprises: in response to a device evaluation request, obtaining each feature parameter of each device component in the target device; if there is an abnormal feature parameter exceeding a preset defect threshold, obtaining a variable weight constant of the abnormal feature parameter; according to the variable weight constant and the abnormal feature parameter, performing variable weight processing on the initial weight of each feature parameter to obtain the target weight of each feature parameter; calculating the device health degree of the target device according to the feature parameter and the target weight of the feature parameter, and outputting the device evaluation result corresponding to the device health degree; if there is an abnormal feature parameter exceeding a preset defect threshold, obtaining a variable weight constant of the abnormal feature parameter, comprising: accessing a threshold database to obtain a defect threshold associated with the feature parameter, comparing the feature parameter with the defect threshold, if the feature parameter exceeds the defect threshold, determining that the feature parameter is an abnormal feature parameter; reading the feature type of the abnormal feature parameter, obtaining a variable weight constant associated with the feature type; wherein, when the feature type is a key feature type, the variable weight constant is a key variable weight constant, and the key variable weight constant is a constant with a value range of (0, 0.5); when the feature type is a balanced feature type, the variable weight constant is a balanced variable weight constant, and the balanced variable weight constant is a constant with a value range of (0.5, 1); when the abnormal feature parameter includes speed and temperature threshold value, the feature type is the balanced feature type; when the abnormal feature parameter includes kurtosis value and parameter threshold value, the feature type is the key feature type.
2. The device evaluation method of claim 1, wherein, According to the variable weight constant and the abnormal feature parameter, the initial weight is processed to obtain the target weight of each feature parameter, comprising: obtaining the initial weight of each feature parameter in the target device; inputting the abnormal feature parameter, the balanced constant of the abnormal feature parameter, the feature parameter and the initial weight of the feature parameter into a preset variable weight function model for variable weight processing to generate the target weight of each feature parameter.
3. The device evaluation method of claim 1, wherein, According to the feature parameter and the target weight of the feature parameter, the device health degree of the target device is calculated, and the device evaluation result corresponding to the device health degree is output, comprising: obtaining each feature parameter and the target weight of each feature parameter, weighting the feature parameter according to the target weight to obtain the feature health degree of each feature parameter; summing up the sum of each feature health degree of the target device to obtain the device health degree of the target device; obtaining the device evaluation result associated with the device health degree, and outputting the device evaluation result.
4. The device evaluation method of claim 1, wherein, According to the feature parameter and the target weight of the feature parameter, the device health degree of the target device is calculated, and the device evaluation result corresponding to the device health degree is output, comprising: calculating the sum of the feature health degree of each feature parameter to obtain the device health degree of the target device; obtaining each device health interval associated with the target device, and the device health threshold corresponding to each device health interval; The target device is evaluated according to the device health degree and the device health threshold, and a device evaluation result of the target device is output.
5. The device evaluation method of claim 4, wherein, The device evaluation according to the device health degree and the device health threshold, and the output of the device evaluation result of the target device, comprises: reading the device health threshold corresponding to the device health interval, wherein the device health threshold comprises a first health threshold and a second health threshold, and the first health threshold is less than the second health threshold; if the device health degree of the target device is greater than the first health threshold and less than the second health threshold, setting the device health level associated with the device health interval as the target health level of the target device; generating a device evaluation result associated with the target health level, and outputting the device evaluation result.
6. The method of claim 1-5, wherein, The output of the device evaluation result corresponding to the device health degree comprises: obtaining a target health level corresponding to the device health degree, and determining a component evaluation result of each device component in the target device according to the target health level and a component health degree of the device component; generating a device evaluation result of the target device according to the target health level and the component evaluation result, and outputting the device evaluation result.
7. An apparatus evaluation device, characterized by The device evaluation device comprises: a feature acquisition module configured to acquire each feature parameter of each device component in a target device in response to a device evaluation request; a constant acquisition module configured to acquire a variable weight constant of an abnormal feature parameter if the abnormal feature parameter exceeds a preset defect threshold; the acquisition of the variable weight constant of the abnormal feature parameter if the abnormal feature parameter exceeds the preset defect threshold comprises: accessing a threshold database to acquire a defect threshold associated with the feature parameter, comparing the feature parameter with the defect threshold, determining the feature parameter as an abnormal feature parameter if the feature parameter exceeds the defect threshold, reading a feature type of the abnormal feature parameter, and acquiring a variable weight constant associated with the feature type; wherein, when the feature type is a key feature type, the variable weight constant is a key variable weight constant, and the key variable weight constant is a constant with a value range of (0, 0.5); when the feature type is a balanced feature type, the variable weight constant is a balanced variable weight constant, and the balanced variable weight constant is a constant with a value range of (0.5, 1); when the abnormal feature parameter includes a speed and a temperature exceeding a threshold, the feature type is the balanced feature type; when the abnormal feature parameter includes a kurtosis value and a parameter exceeding a threshold, the feature type is the key feature type; a variable weight calculation module configured to perform variable weight processing on an initial weight of each feature parameter according to the variable weight constant and the abnormal feature parameter to obtain a target weight of each feature parameter; a device evaluation module configured to calculate a device health degree of the target device according to the feature parameter and the target weight of the feature parameter, and output a device evaluation result corresponding to the device health degree.
8. An apparatus for evaluating an apparatus, characterized by The device evaluation device comprises: one or more processors; a memory; and one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to implement the steps of the device evaluation method of any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that, a computer program stored thereon, the computer program being loaded by a processor to execute the steps of the device evaluation method of any one of claims 1 to 6.