A method, apparatus and equipment for determining the capability level of an intelligent servo motor.

Abstract

This invention provides a method, apparatus, and device for determining the capability level of a smart servo motor. The method includes: acquiring indicator test data of the smart servo motor; obtaining a smart capability score of the smart servo motor based on the indicator test data, wherein the smart capability score includes at least one of the following: data acquisition capability score, fault alarm capability score, human-machine interaction capability score, fault identification capability score, health status assessment capability score, fault early warning capability score, and auxiliary decision-making capability score; and determining the capability level of the smart servo motor based on at least one of the smart capability scores. The solution provided by this invention can improve the completeness and accuracy of the smart servo motor's intelligence level assessment, and reduce the assessment difficulty and cost.

Description

Technical Field

[0001] This invention relates to the field of computer information processing technology, and in particular to a method, apparatus and equipment for determining the capability level of an intelligent servo motor. Background Technology

[0002] In recent years, the development of intelligent ships has entered a development stage. The definition and classification of intelligent ships have not yet been unified, and the standard system, testing and verification system for various intelligent ship systems urgently need to be established.

[0003] In the current technology, there is no effective assessment of the different levels of intelligence of various systems in intelligent ships, and it cannot provide an accurate and rigorous basis for assessing the overall capability level of the ship. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method, apparatus and equipment for determining the capability level of an intelligent servo motor, so as to improve the accuracy and completeness of the intelligent evaluation of the intelligent servo motor.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a method for determining the capability level of an intelligent servo motor, comprising:

[0006] Obtain test data for the intelligent servo motor's performance indicators;

[0007] Based on the test data of the aforementioned indicators, the intelligent capability score of the intelligent servo is obtained. The at least one intelligent capability score includes at least one of the following: data acquisition capability score, fault alarm capability score, human-computer interaction capability score, fault identification capability score, health status assessment capability score, fault early warning capability score, and decision support capability score.

[0008] The capability level of the intelligent servo is determined based on at least one of the aforementioned intelligent capability scores.

[0009] Optionally, a data acquisition capability score for the intelligent servo motor is obtained, including:

[0010] Based on the indicator test data and preset data that meet the preset conditions in the indicator test data, the comprehensiveness score of the data acquisition capability of the intelligent servo motor is obtained.

[0011] Based on the indicator test data corresponding to the samples that represent the accuracy of data acquisition and the indicator test data corresponding to all samples that represent the accuracy of data acquisition, the data acquisition accuracy score of the intelligent servo motor is obtained.

[0012] Based on the actual collection period and the preset collection period of the test data of the aforementioned indicators, the periodicity score of the data collection capability of the intelligent servo motor is obtained.

[0013] The data acquisition capability score of the intelligent servo motor is obtained based on the comprehensiveness score, the accuracy score, and the periodicity score.

[0014] Optionally, a fault alarm capability score for the intelligent servo motor is obtained, including:

[0015] Based on the indicator test data corresponding to the missed fault samples and the indicator test data corresponding to the fault samples in the indicator test data, the missed alarm rate score of the fault alarm capability of the intelligent servo motor is obtained.

[0016] Based on the indicator test data corresponding to the samples that were falsely reported as faults and the indicator test data corresponding to the normal samples in the indicator test data, the false alarm rate score of the fault alarm capability of the intelligent servo motor is obtained.

[0017] The fault alarm capability score of the intelligent servo motor is obtained based on the missed alarm rate score and the false alarm rate score.

[0018] Optionally, a human-machine interaction capability score for the intelligent servo motor is obtained, including:

[0019] Based on the types of indicator test data that represent the interface display information in the indicator test data, the comprehensiveness score of the interface display information of the human-computer interaction capability of the intelligent servo is obtained.

[0020] Based on the content of the indicator test data corresponding to the information displayed on the interface in the indicator test data, the information comprehension ease score of the human-computer interaction capability of the intelligent servo is obtained.

[0021] Based on the types of indicator data representing interface operations in the indicator test data, the comprehensiveness score of the human-computer interaction capability of the intelligent servo motor is obtained.

[0022] The human-computer interaction capability score of the intelligent servo is obtained based on the comprehensiveness score of the information displayed on the interface, the ease of understanding the information, and the comprehensiveness score of the usage functions.

[0023] Optionally, a fault identification capability score for the intelligent servo motor is obtained, including:

[0024] Based on the indicator test data that accurately analyzes any fault sample and the indicator test data that represents the occurrence of the fault sample, the identification accuracy score of the intelligent servo motor's fault identification capability is obtained.

[0025] Based on the indicator test data representing the types of fault samples and the indicator test data representing all types of fault samples in the indicator test data, the comprehensiveness score of the human-computer interaction capability of the intelligent servo is obtained.

[0026] The fault identification capability score of the intelligent servo motor is obtained based on the identification accuracy score and the identification comprehensiveness score.

[0027] Optionally, a health status assessment capability score for the intelligent servo motor is obtained, including:

[0028] Based on the indicator test data corresponding to the sample representing the accurate assessment of health status in the indicator test data and the indicator test data corresponding to all samples representing the assessment of health status, the assessment accuracy score of the health status assessment capability of the intelligent servo is obtained.

[0029] Based on the accuracy score of the assessment, a health status assessment capability score for the intelligent servo motor is obtained.

[0030] Optionally, a fault warning capability score for the intelligent servo motor is obtained, including:

[0031] Based on the indicator test data corresponding to the sample representing accurate early warning of faults in the indicator test data and the indicator test data corresponding to all samples representing early warning of faults, the early warning accuracy score of the fault early warning capability of the intelligent servo is obtained.

[0032] Based on the accuracy score of the early warning, a fault early warning capability score for the intelligent servo motor is obtained.

[0033] Optionally, the auxiliary decision-making capability score of the intelligent servo is obtained, including:

[0034] Based on the indicator test data corresponding to the samples representing successful decision creation and the indicator test data corresponding to all samples representing decision creation, the effectiveness score of the intelligent servo's auxiliary decision-making capability is obtained.

[0035] Based on the indicator test data corresponding to the samples representing effective creation decisions and the indicator test data corresponding to all samples representing creation decisions in the indicator test data, the diversity score of the auxiliary decision-making capability of the intelligent servo is obtained.

[0036] The auxiliary decision-making capability score of the intelligent servo is obtained based on the effectiveness score and the diversity score.

[0037] Optionally, the capability level of the intelligent servo is determined based on at least one of the aforementioned intelligent capability scores, including:

[0038] When the data acquisition capability score is greater than or equal to the first preset score, the fault alarm capability score is greater than or equal to the second preset score, the human-computer interaction capability score is greater than or equal to the third preset score, and the fault identification capability score is greater than or equal to the fourth preset score, the capability level of the intelligent servo motor is determined to be the first capability level.

[0039] When the intelligent servo meets the first capability level, and the health status assessment capability score of the intelligent servo is greater than or equal to the fifth preset score, and the fault warning capability score of the intelligent servo is greater than or equal to the sixth preset score, the capability level of the intelligent servo is determined to be the second capability level.

[0040] When the intelligent servo meets the second capability level and the auxiliary decision-making capability score of the intelligent servo is greater than or equal to the seventh preset score, the capability level of the intelligent servo is determined to be the third capability level.

[0041] Embodiments of the present invention also provide a device for determining the capability level of an intelligent servo motor, comprising:

[0042] The acquisition module is used to acquire the performance test data of the intelligent servo motor;

[0043] The processing module is used to obtain the intelligent capability score of the intelligent servo based on the indicator test data. The intelligent capability score includes at least one of the following: data acquisition capability score, fault alarm capability score, human-machine interaction capability score, fault identification capability score, health status assessment capability score, fault early warning capability score, and auxiliary decision-making capability score; and to determine the capability level of the intelligent servo based on at least one of the intelligent capability scores.

[0044] Embodiments of the present invention also provide a computing device, including: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0045] The memory is used to store at least one executable instruction that causes the processor to perform the operation corresponding to the method described above.

[0046] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the methods described above.

[0047] The above-described solution of the present invention has at least the following beneficial effects:

[0048] The above-described solution of the present invention obtains the performance test data of the intelligent servo; based on the performance test data, it obtains the intelligent capability score of the intelligent servo, wherein the intelligent capability score includes at least one of the following: data acquisition capability score, fault alarm capability score, human-computer interaction capability score, fault identification capability score, health status assessment capability score, fault early warning capability score, and decision support capability score; based on at least one of the intelligent capability scores, it determines the capability level of the intelligent servo, thereby improving the accuracy and completeness of the intelligent servo assessment and reducing the assessment cost and difficulty. Attached Figure Description

[0049] Figure 1 This is a flowchart of the method for determining the capability level of an intelligent servo motor provided in an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the module block of the intelligent servo motor capability level determination device provided in an embodiment of the present invention. Detailed Implementation

[0051] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0052] like Figure 1 As shown, an embodiment of the present invention proposes a method for determining the capability level of an intelligent servo motor, including:

[0053] Step 11: Obtain the performance test data of the intelligent servo motor;

[0054] Step 12: Based on the test data of the indicators, obtain the intelligent capability score of the intelligent servo motor. The intelligent capability score includes at least one of the following: data acquisition capability score, fault alarm capability score, human-machine interaction capability score, fault identification capability score, health status assessment capability score, fault early warning capability score, and auxiliary decision-making capability score.

[0055] Step 13: Determine the capability level of the intelligent servo motor based on at least one of the aforementioned intelligent capability scores.

[0056] In this embodiment, the indicator test data is obtained by testing and processing the servo motor multiple times in an intelligent testing platform according to preset application scenarios, preset data, and preset signals. The intelligent testing platform can be a system that simulates the operating environment of a ship. The preset application scenarios can be set according to user needs, and the preset data and preset signals can be set according to the preset application scenarios. The indicator test data can be used to characterize the performance of different important components in the intelligent servo motor, and can include various types and performance data, such as electrical signals and non-electrical signals. It should be noted that the indicator test data obtained under different preset application scenarios should be different.

[0057] Each of the at least one of the intelligent capability scores corresponds to the intelligent servo motor's data acquisition capability, fault alarm capability, human-machine interaction capability, fault identification capability, health status assessment capability, fault early warning capability, and decision support capability, respectively.

[0058] The data acquisition capability refers to the intelligent servo motor's ability to comprehensively and accurately acquire relevant data from sensors and other analog and digital test units of the device under test within its designed operating range.

[0059] The fault alarm capability refers to the intelligent servo motor's ability to compare the collected data with fault characteristics on the network or in the fault database, determine whether a fault has occurred in the system or measurement point, and generate corresponding data in response.

[0060] The aforementioned human-computer interaction capability refers to the ability of the intelligent servo to convert data into a format that clearly expresses the information necessary to make the correct decision, so that the human and the intelligent servo can exchange information conveniently, quickly and accurately to complete the defined task using a certain dialogue language in an interactive manner.

[0061] The fault identification capability refers to the intelligent servo motor's ability to accurately and promptly separate and identify faults that occur in the system, determine the type and specific location of the fault, and generate corresponding data in response.

[0062] The aforementioned health status assessment capability refers to the ability of the intelligent servo motor to assess its current health status (healthy, sub-healthy, unhealthy) based on collected historical and current data, and to generate corresponding data in return.

[0063] The aforementioned fault warning capability refers to the ability of the intelligent servo motor to predict the duration of the servo motor's health status and the time and location of possible faults by combining the equipment's health status, historical data, and task conditions, and to generate corresponding data in response.

[0064] The aforementioned decision support capability refers to the ability of the intelligent servo motor to compare the expected benefits of implementing each alternative plan based on the actual situation, by selecting appropriate evaluation methods and indicators, and finally select the best plan and generate corresponding data.

[0065] The data acquisition capability and the fault alarm capability are the basic intelligent capabilities of the intelligent servo; the human-machine interaction capability, the fault identification capability, the health status assessment capability, the fault early warning capability, and the auxiliary decision-making capability are the newly added intelligent capabilities of the intelligent servo; and the above-mentioned intelligent capabilities are in a progressive relationship, for example: when the intelligent servo has human-machine interaction capability and fault identification capability, it must have data acquisition capability and fault alarm capability; when the intelligent servo has health status assessment capability and fault early warning capability, it must have data acquisition capability, fault alarm capability, human-machine interaction capability, and fault identification capability;

[0066] Based on the test data of the aforementioned indicators, at least one intelligent capability score of the intelligent servo is obtained. Based on the capability score corresponding to each intelligent capability, the capability level of the intelligent servo can be determined. Furthermore, the intelligent servo can be divided into intelligent levels based on the capability levels to determine the intelligent level of the intelligent servo.

[0067] By testing the intelligent servo motor under different preset application scenarios, indicator test data is obtained. Based on the indicator test data, the capability score of the corresponding intelligent capability of the intelligent servo motor is obtained. The capability level of the intelligent servo motor is evaluated and classified according to the capability score, which ensures the accuracy of the evaluation and classification results. At the same time, it reduces the actual operating cost of the ship and the cost of actual scenario deployment.

[0068] In an optional embodiment of the present invention, step 12 above may include:

[0069] Step 121a: Based on the indicator test data and preset data that meet the preset conditions in the indicator test data, obtain the data acquisition comprehensiveness score of the intelligent servo motor's data acquisition capability.

[0070] Step 122a: Based on the indicator test data corresponding to the samples that represent the accuracy of data acquisition and the indicator test data corresponding to all samples that represent the accuracy of data acquisition, obtain the data acquisition accuracy score of the intelligent servo motor.

[0071] Step 123a: Based on the actual collection period and the preset collection period of the indicator test data, obtain the collection periodicity score of the data collection capability of the intelligent servo motor.

[0072] Step 124a: Obtain the data acquisition capability score of the intelligent servo motor based on the comprehensiveness score, the accuracy score, and the periodicity score.

[0073] In this embodiment, the preset conditions can be pre-set. Based on the indicator test data that meets the preset conditions and the preset data in the indicator test data, the data acquisition comprehensiveness score of the intelligent servo motor is obtained. Specifically, it refers to the number of indicator test data actually collected for any sampling point in the preset conditions. and the expected number of data points to be collected. The comprehensiveness score can be obtained by considering the number of preset data points. Specifically, it can be calculated using the formula: ;in, This indicates the comprehensiveness score of the data collection. , , , All are set constants (the specific values ​​can be set according to the application scenario or the basic attributes of different important components in the intelligent servo motor).

[0074] The data acquisition accuracy score of the intelligent servo motor is obtained based on the number of indicator test data corresponding to samples that meet the acquisition accuracy criteria and the total number of indicator test data corresponding to all samples that meet the acquisition accuracy criteria. Specifically, this can be achieved through the formula... ;in, The score represents the accuracy of the data collection. This indicates the number of indicator test data points corresponding to samples that meet the accuracy requirements of the data collection. This represents the number of indicator test data corresponding to all samples that characterize the accuracy of the data collection in the indicator test data;

[0075] Based on the actual and preset collection periods of the test data for the aforementioned indicators, the periodicity score of the data collection capability of the intelligent servo motor is obtained. Specifically, it can be calculated using the formula: ;in, This indicates that scores are collected periodically. , , , , All are set constants (the specific values ​​can be set according to the application scenario or the basic attributes of different important components in the intelligent servo motor), and T represents the actual acquisition period; Indicates the preset data collection period;

[0076] Furthermore, based on the comprehensiveness score of the data collection... The accuracy score of the data collection The periodic scoring of the data collection The data acquisition capability score of the intelligent servo motor can be obtained by considering the preset weights corresponding to each score; specifically, it can be obtained through the formula... ;in This indicates a score for data collection capabilities. This indicates the preset weights corresponding to each score. This represents the scores for each item, where j = 1, 2, 3;

[0077] The preset weights mentioned here can be determined by expert scoring and after multiple rounds of consultation, feedback and adjustment, and are the final weights of each score. By calculating the comprehensiveness score, accuracy score and periodicity score of data acquisition capability, and calculating the data acquisition capability score based on these three scores, a data foundation is provided for evaluating the data acquisition capability of intelligent servos, and the accuracy of subsequent capability level classification and determination is ensured.

[0078] In an optional embodiment of the present invention, step 12 above may include:

[0079] Step 121b: Based on the indicator test data corresponding to the missed fault samples and the indicator test data corresponding to the fault samples in the indicator test data, obtain the missed alarm rate score of the fault alarm capability of the intelligent servo motor.

[0080] Step 122b: Based on the indicator test data corresponding to the samples that were falsely reported as faults and the indicator test data corresponding to the normal samples in the indicator test data, obtain the false alarm rate score of the fault alarm capability of the intelligent servo motor.

[0081] Step 123b: Obtain the fault alarm capability score of the intelligent servo motor based on the missed alarm rate score and the false alarm rate score.

[0082] In this embodiment, the false alarm rate score of the intelligent servo's fault alarm capability is obtained. Specifically, this score is calculated by the number of fault samples that were missed in the test data and the total number of test data corresponding to the samples that experienced faults. Specifically, this can be achieved using the formula... ,in, The score represents the false negative rate. This indicates the number of indicator test data points corresponding to the missed fault samples in the indicator test data. This indicates the total number of indicator test data corresponding to the samples that experienced failures in the indicator test data;

[0083] The false alarm rate score of the fault alarm capability of the intelligent servo motor is obtained, specifically based on the number of index test data points that falsely report normal samples as fault samples, and the number of index test data points corresponding to all normal samples; specifically, it can be obtained through the formula... ,in, The score represents the false alarm rate. This indicates the number of indicator test data points in the indicator test data that misreported normal samples as faulty samples. This indicates the number of indicator test data corresponding to all normal samples in the indicator test data;

[0084] Furthermore, based on the aforementioned false negative rate score and the missed detection rate score The fault alarm capability score of the intelligent servo motor is obtained by calculating the preset weights corresponding to each score; specifically, it can be obtained through the formula... ;in This indicates the score for fault alarm capability. The false negative rate score represents the score of the false negative rate. Preset weights, The false alarm rate score represents the false alarm rate score. Preset weights;

[0085] here , Similarly, the weights of each score can be determined by expert scoring and after multiple rounds of consultation, feedback and adjustment. By calculating the false alarm rate score and false alarm rate score of the fault alarm capability, and calculating the fault alarm capability score based on the calculated score, a data foundation is provided for evaluating the fault alarm capability of the intelligent servo motor, ensuring the accuracy of subsequent capability level classification and determination.

[0086] In an optional embodiment of the present invention, step 12 above may include:

[0087] Step 121c: Based on the types of indicator test data that represent the interface display information in the indicator test data, obtain the comprehensiveness score of the human-computer interaction capability of the intelligent servo motor for the interface display information.

[0088] Step 122c: Based on the content of the indicator test data corresponding to the information displayed on the interface in the indicator test data, obtain the information comprehension ease score of the human-computer interaction capability of the intelligent servo.

[0089] Step 123c: Based on the types of indicator data representing interface operations in the indicator test data, obtain the comprehensiveness score of the human-computer interaction capability of the intelligent servo motor.

[0090] Step 124c: Based on the comprehensiveness score of the information displayed on the interface, the ease of understanding the information, and the comprehensiveness score of the usage functions, obtain the human-computer interaction capability score of the intelligent servo.

[0091] In this embodiment, the evaluation indicators used to characterize the comprehensiveness of the display information of the intelligent servo motor human-machine interface may include: whether the identification code or number of the device or sub-component is displayed (the identification of the tested machinery is described through historical records such as device number, component number, and evaluation date); whether the status monitoring of the device or sub-component is displayed (the specific status information and trend data of the monitored object are displayed); and whether the health evaluation of the device or sub-component is displayed (the diagnostic conclusions of the current or potential faults and failures of the monitored object, as well as failure prediction information are displayed). According to the indicator test data corresponding to the evaluation indicators of the comprehensiveness of the interface display information in the indicator test data, when the indicator test data corresponding to the above evaluation indicators is not comprehensive, the evaluation is unqualified, and the comprehensiveness score of the interface display information is 0 (other specific values ​​can also be set according to actual needs); when the indicator test data corresponding to the above evaluation indicators is comprehensive, the evaluation is qualified, and the comprehensiveness score of the interface display information is 1 (other specific values ​​can also be set according to actual needs).

[0092] Based on the content of the indicator test data used to characterize the display information of the intelligent servo human-machine interface, the information comprehension ease score is obtained. Specifically: when the content of the indicator test data corresponding to the interface display information is difficult to understand, the information comprehension ease score is 0 (or other specific values ​​can be set according to actual needs); when the content of the indicator test data corresponding to the interface display information can be understood by a professionally trained person, the information comprehension ease score is 0.6 (or other specific values ​​can be set according to actual needs); when the content of the indicator test data corresponding to the interface display information can be understood by a person without professional training, the information comprehension ease score is 1 (or other specific values ​​can be set according to actual needs).

[0093] Indicators used to characterize the comprehensiveness of the human-machine interface of a smart servo motor may include: whether it supports the labeling of abnormal variables; whether it provides comprehensive safety protection; and whether the human-machine interaction is convenient.

[0094] Regarding support for anomaly variable labeling: when significant anomaly labeling is supported, the first-use functionality comprehensiveness score is 1 (or can be set to other specific values ​​as needed); when anomaly labeling is not supported, the first-use functionality comprehensiveness score is 0 (or can be set to other specific values ​​as needed).

[0095] Regarding comprehensive security protection: when there is no permission level, the comprehensiveness score of the second-use function is 0 (it can also be set to other specific values ​​according to actual needs); when there is only permission level, the comprehensiveness score of the second-use function is 0.6 (it can also be set to other specific values ​​according to actual needs); when authorized use level, the comprehensiveness score of the second-use function is 1 (it can also be set to other specific values ​​according to actual needs).

[0096] Regarding the convenience of human-computer interaction: when input commands are required for control, the comprehensiveness score for third-party functionality is 0 (this can also be set to other specific values ​​according to actual needs); when touchscreen button control is used, the comprehensiveness score for third-party functionality is 0.6 (this can also be set to other specific values ​​according to actual needs); when voice interaction is used, the comprehensiveness score for third-party functionality is 1 (this can also be set to other specific values ​​according to actual needs); and then, based on the scores corresponding to the above three evaluation indicators, the formula can be used to... The score for the comprehensiveness of the functionality is calculated; among which, The score indicates the comprehensiveness of the first-time user's functionality. Preset weights, This indicates the score for the comprehensiveness of the second-use functionality. Preset weights, This indicates the score for the comprehensiveness of the third-party usage function. Preset weights;

[0097] Furthermore, based on the comprehensiveness score of the information displayed on the interface... The information comprehension ease score The comprehensiveness score of the aforementioned functions The human-computer interaction capability score of the intelligent servo motor can be obtained by combining the preset weights of each score. Specifically: it can be done through formulas. ;in This indicates a score for data collection capabilities. This indicates the preset weights corresponding to each score. This represents the scores for each item, where k = 1, 2, 3;

[0098] The preset weights mentioned here can be determined by expert scoring and after multiple rounds of consultation, feedback and adjustment, and are the final weights of each score. The human-computer interaction capability score is calculated by evaluating the comprehensiveness of the interface display information, the comprehensiveness of the functions, and the ease of information comprehension. Based on these three scores, the human-computer interaction capability score is calculated, which provides a data foundation for evaluating the human-computer interaction capability of the intelligent servo and ensures the accuracy of subsequent capability level classification and determination.

[0099] In an optional embodiment of the present invention, step 12 above may include:

[0100] Step 121d: Based on the indicator test data that accurately analyzes any fault sample and the indicator test data that represents the occurrence of the fault sample in the indicator test data, obtain the identification accuracy score of the fault identification capability of the intelligent servo motor.

[0101] Step 122d: Based on the indicator test data representing the types of fault samples and the indicator test data representing all types of fault samples in the indicator test data, obtain the recognition comprehensiveness score of the human-machine interaction capability of the intelligent servo.

[0102] Step 123d: Based on the recognition accuracy score and the recognition comprehensiveness score, obtain the fault recognition capability score of the intelligent servo motor.

[0103] In this embodiment, the accuracy score of the fault identification capability of the intelligent servo is obtained based on the number of index test data corresponding to any fault sample in the index test data, and the number of index test data corresponding to all types of fault samples in the index test data. Specifically, it can be expressed by the formula: ;in, The score represents the accuracy of the recognition. This indicates the number of indicator test data points in the indicator test data that accurately represent the analysis of any fault sample. This indicates the number of indicator test data corresponding to all types of fault samples in the indicator test data;

[0104] The comprehensiveness score of the human-machine interaction capability of the intelligent servo is obtained based on the number of indicator test data corresponding to the types of fault samples in the indicator test data, and the number of indicator test data corresponding to all types of fault samples in the indicator test data. Specifically, it can be obtained through the formula: ;in, This indicates the score for comprehensiveness of recognition. This indicates the number of indicator test data points in the indicator test data that represent the types of fault samples. This represents the number of indicator test data corresponding to all samples representing all types of faults in the indicator test data;

[0105] Furthermore, based on the aforementioned recognition accuracy score The comprehensiveness score of the identification The human-machine interaction capability score S4 of the intelligent servo can be obtained by calculating the preset weights corresponding to each score; specifically, it can be obtained through the formula... ;in This indicates a score for data collection capabilities. This indicates the preset weights corresponding to each score. Represents the scores for each item, r=1, 2;

[0106] The preset weights here can also be determined by expert scoring, and the final weights of each score are determined after multiple rounds of consultation, feedback and adjustment. By calculating the comprehensiveness score and accuracy score of fault identification capability, and calculating the fault identification capability score based on these two scores, a data foundation is provided for evaluating the fault identification capability of intelligent servos, ensuring the accuracy of subsequent capability level classification and determination.

[0107] In an optional embodiment of the present invention, step 12 above may include:

[0108] Step 121e: Based on the indicator test data corresponding to the sample representing the accurate assessment of health status in the indicator test data and the indicator test data corresponding to all samples representing the assessment of health status, obtain the assessment accuracy score of the health status assessment capability of the intelligent servo.

[0109] Step 122e: Obtain the health status assessment capability score of the intelligent servo motor based on the assessment accuracy score.

[0110] In this embodiment, the accuracy score of the health status assessment capability of the intelligent servo is obtained based on the number of indicator test data corresponding to the samples representing accurate health status assessments in the indicator test data, and the number of indicator test data corresponding to all samples representing health status assessments in the indicator test data. Specifically, it can be expressed by the formula: ;in, Indicates the accuracy score of the assessment. , , Both are set constants (the specific values ​​can be set according to the application scenario or the basic attributes of different important components in the intelligent servo motor). This indicates the number of indicator test data points in the indicator test data that correspond to the samples used to accurately assess health status. This represents the number of indicator test data corresponding to all samples that characterize and assess health status in the indicator test data;

[0111] Furthermore, the accuracy score of the assessment will be... As a health status assessment capability score of the intelligent servo motor By calculating the accuracy score of the health status assessment capability, a data foundation is provided for evaluating the health status assessment capability of intelligent servos, ensuring the accuracy of subsequent capability level classification and determination.

[0112] In an optional embodiment of the present invention, step 12 above may include:

[0113] Step 121f: Obtain the warning accuracy score of the fault warning capability of the intelligent servo motor based on the indicator test data corresponding to the sample representing accurate warning faults and the indicator test data corresponding to all samples representing warning faults in the indicator test data.

[0114] Step 122f: Based on the accuracy score of the early warning, obtain the fault early warning capability score of the intelligent servo motor.

[0115] In this embodiment, the accuracy score of the fault warning capability of the intelligent servo is obtained based on the number of index test data corresponding to the samples representing accurate fault warnings in the index test data, and the total number of index test data corresponding to all samples representing fault warnings. Specifically, it can be expressed by the formula: ;in, The score indicates the accuracy of the early warning. , , , All of these are set constants (the specific values ​​can be set according to the application scenario or the basic attributes of different important components in the intelligent servo motor). This indicates the number of indicator test data points corresponding to the samples used to accurately predict faults in the indicator test data. This indicates the number of indicator test data corresponding to all samples representing early warning faults in the indicator test data;

[0116] Furthermore, the accuracy score of the aforementioned early warning will be determined. As a score for the fault early warning capability of the aforementioned intelligent servo motor By calculating the accuracy score of fault warning capability, a data foundation is provided for evaluating the fault warning capability of intelligent servos, ensuring the accuracy of subsequent capability level classification and determination.

[0117] In an optional embodiment of the present invention, step 12 above may include:

[0118] Step 121g: Based on the indicator test data corresponding to the sample representing the successful creation of the decision and the indicator test data corresponding to all samples representing the creation of the decision, obtain the effectiveness score of the intelligent servo's auxiliary decision-making capability.

[0119] Step 122g: Based on the indicator test data corresponding to the sample representing effective creation decision and the indicator test data corresponding to all samples representing creation decision in the indicator test data, obtain the diversity score of the auxiliary decision-making capability of the intelligent servo.

[0120] Step 123g: Based on the effectiveness score and the diversity score, obtain the auxiliary decision-making capability score of the intelligent servo motor.

[0121] In this embodiment, the diversity score of the intelligent servo's auxiliary decision-making capability is obtained based on the number of indicator test data representing accurate creation decisions and the total number of indicator test data representing creation decisions. Specifically, it can be calculated using the formula: ;in, The score indicates the accuracy of the early warning. , , , All of these are set constants (the specific values ​​can be set according to the application scenario or the basic attributes of different important components in the intelligent servo motor). This indicates the number of indicator test data points in the indicator test data that correspond to the samples used to characterize the successful creation of decisions. This represents the number of indicator test data corresponding to all samples representing the creation decision in the indicator test data;

[0122] The diversity score of the intelligent servo's decision-making assistance capability is obtained based on the number of indicator test data corresponding to samples representing effective decision creation in the indicator test data, and the indicator test data corresponding to all samples representing decision creation in the indicator test data. Specifically, the diversity score of the decision-making assistance capability is calculated by collecting the number of indicator test data in the indicator test data used to represent the provision of effective solutions; when no effective solution is provided, the diversity score is... When an effective solution is given, the diversity score is: When multiple valid values ​​are given, the diversity score is: It can be done through formula ,in, Indicates diversity score, This indicates the number of test data points for indicators for which no valid solutions were provided. This indicates the number of test data points for a single valid solution. This indicates the number of test data points for multiple valid solutions.

[0123] Furthermore, based on the aforementioned validity score The aforementioned diversity score The intelligent servo's auxiliary decision-making capability score can be obtained by considering the preset weights corresponding to these two scores. Specifically: it can be done through formulas. ;in This indicates the score for decision support capability. This indicates the preset weights corresponding to each score. This represents the scores for each item, t=1, 2;

[0124] The preset weights here can also be determined by expert scoring, and the final weights of each score are determined after multiple rounds of opinion solicitation, feedback and adjustment. By calculating the effectiveness score and diversity score of the auxiliary decision-making ability, and calculating the auxiliary decision-making ability score based on these two scores, a data foundation is provided for evaluating the auxiliary decision-making ability of the intelligent servo, ensuring the accuracy of subsequent capability level classification and determination.

[0125] In an optional embodiment of the present invention, step 13 above may include:

[0126] Step 131a: When the data acquisition capability score is greater than or equal to the first preset score, the fault alarm capability score is greater than or equal to the second preset score, the human-machine interaction capability score is greater than or equal to the third preset score, and the fault identification capability score is greater than or equal to the fourth preset score, the capability level of the intelligent servo motor is determined to be the first capability level.

[0127] Step 131b: When the intelligent servo meets the first capability level, and the health status assessment capability score of the intelligent servo is greater than or equal to the fifth preset score, and the fault warning capability score of the intelligent servo is greater than or equal to the sixth preset score, the capability level of the intelligent servo is determined to be the second capability level.

[0128] Step 131c: When the intelligent servo meets the second intelligence level and the auxiliary decision-making capability score of the intelligent servo is greater than or equal to the seventh preset score, the capability level of the intelligent servo is determined to be the third capability level.

[0129] In this embodiment, at least one intelligent capability score of the intelligent servo is calculated, and the capability level of the intelligent servo is evaluated and classified based on the result of the at least one intelligent capability score, so as to determine the final capability level of the intelligent servo.

[0130] Specifically: when the data acquisition capability score is... Greater than or equal to the first preset score The fault alarm capability score Greater than or equal to the second preset score The human-computer interaction ability score Greater than or equal to the third preset score The fault identification capability score Greater than or equal to the fourth preset score The health status assessment ability score Greater than or equal to the fifth preset score The fault early warning capability score Greater than or equal to the sixth preset score And the aforementioned decision support ability score Greater than or equal to the seventh preset score At that time, the capability level of the intelligent servo motor is determined to be the third capability level L3;

[0131] When the data acquisition capability score Greater than or equal to the first preset score The fault alarm capability score Greater than or equal to the second preset score The human-computer interaction ability score Greater than or equal to the third preset score The fault identification capability score Greater than or equal to the fourth preset score The health status assessment ability score Greater than or equal to the fifth preset score And the fault early warning capability score Greater than or equal to the sixth preset score The capability level of the intelligent servo motor is determined to be the second capability level L2;

[0132] When the data acquisition capability score Greater than or equal to the first preset score The fault alarm capability score Greater than or equal to the second preset score And the human-computer interaction ability score Greater than or equal to the third preset score and the fault identification capability score Greater than or equal to the fourth preset score At that time, the capability level of the intelligent servo motor is determined to be the first capability level L1;

[0133] Here, the first preset score The second preset score The third preset score The fourth preset score The fifth preset score The sixth preset score and the seventh preset score All can be set according to preset application scenarios and the attributes of different important components of the intelligent servo motor;

[0134] Based on the capability levels of the aforementioned intelligent servo motors, the intelligence level classification table of the intelligent servo motors shown in Table 1 below can be obtained.

[0135]

[0136] Table 1. Capability Level Classification Table for Intelligent Servo Motors

[0137] In practical applications, the above embodiments of the present invention test the intelligent servo motor under different preset application scenarios to obtain indicator test data. Based on the indicator test data, the capability scores of multiple intelligent capabilities of the intelligent servo motor are obtained. Furthermore, by comparing the capability scores of each intelligent capability with a capability level rating table, the corresponding capability level of the intelligent servo motor is determined by its capability scores. The capability level of the intelligent servo motor is evaluated and classified based on the capability scores of multiple intelligent capabilities, and the capability level evaluation and classification of the intelligent servo motor is specifically quantified, ensuring the accuracy and completeness of the capability level evaluation and classification results of the intelligent servo motor, while reducing the actual operating cost of the ship and the cost of actual scenario deployment.

[0138] Embodiments of the present invention also provide a capability level determination device 20 for an intelligent servo motor, comprising:

[0139] Module 21 is used to acquire the performance test data of the intelligent servo motor;

[0140] Processing module 22 is used to obtain the intelligent capability score of the intelligent servo based on the indicator test data. The intelligent capability score includes at least one of the following: data acquisition capability score, fault alarm capability score, human-machine interaction capability score, fault identification capability score, health status assessment capability score, fault early warning capability score, and auxiliary decision-making capability score; and to determine the capability level of the intelligent servo based on at least one of the intelligent capability scores.

[0141] Optionally, when the processing module 22 obtains the data acquisition capability score of the intelligent servo motor, it is specifically used for:

[0142] Based on the indicator test data and preset data that meet the preset conditions in the indicator test data, the comprehensiveness score of the data acquisition capability of the intelligent servo motor is obtained.

[0143] Based on the indicator test data corresponding to the samples that represent the accuracy of data acquisition and the indicator test data corresponding to all samples that represent the accuracy of data acquisition, the data acquisition accuracy score of the intelligent servo motor is obtained.

[0144] Based on the actual collection period and the preset collection period of the test data of the aforementioned indicators, the periodicity score of the data collection capability of the intelligent servo motor is obtained.

[0145] The data acquisition capability score of the intelligent servo motor is obtained based on the comprehensiveness score, the accuracy score, and the periodicity score.

[0146] Optionally, the processing module 22 obtains the fault alarm capability score of the intelligent servo motor, specifically for:

[0147] Based on the indicator test data corresponding to the missed fault samples and the indicator test data corresponding to the fault samples in the indicator test data, the missed alarm rate score of the fault alarm capability of the intelligent servo motor is obtained.

[0148] Based on the indicator test data corresponding to the samples that were falsely reported as faults and the indicator test data corresponding to the normal samples in the indicator test data, the false alarm rate score of the fault alarm capability of the intelligent servo motor is obtained.

[0149] The fault alarm capability score of the intelligent servo motor is obtained based on the missed alarm rate score and the false alarm rate score.

[0150] Optionally, the processing module 22 obtains a human-machine interaction capability score for the intelligent servo motor, specifically for:

[0151] Based on the types of indicator test data that represent the interface display information in the indicator test data, the comprehensiveness score of the interface display information of the human-computer interaction capability of the intelligent servo is obtained.

[0152] Based on the content of the indicator test data corresponding to the information displayed on the interface in the indicator test data, the information comprehension ease score of the human-computer interaction capability of the intelligent servo is obtained.

[0153] Based on the types of indicator data representing interface operations in the indicator test data, the comprehensiveness score of the human-computer interaction capability of the intelligent servo motor is obtained.

[0154] The human-computer interaction capability score of the intelligent servo is obtained based on the comprehensiveness score of the information displayed on the interface, the ease of understanding the information, and the comprehensiveness score of the usage functions.

[0155] Optionally, the processing module 22 obtains a fault identification capability score for the intelligent servo motor, specifically for:

[0156] Based on the indicator test data that accurately analyzes any fault sample and the indicator test data that represents the occurrence of the fault sample, the identification accuracy score of the intelligent servo motor's fault identification capability is obtained.

[0157] Based on the indicator test data representing the types of fault samples and the indicator test data representing all types of fault samples in the indicator test data, the comprehensiveness score of the human-computer interaction capability of the intelligent servo is obtained.

[0158] The fault identification capability score of the intelligent servo motor is obtained based on the identification accuracy score and the identification comprehensiveness score.

[0159] Optionally, the processing module 22 obtains a health status assessment capability score for the intelligent servo motor, specifically for:

[0160] Based on the indicator test data corresponding to the sample representing the accurate assessment of health status in the indicator test data and the indicator test data corresponding to all samples representing the assessment of health status, the assessment accuracy score of the health status assessment capability of the intelligent servo is obtained.

[0161] Based on the accuracy score of the assessment, a health status assessment capability score for the intelligent servo motor is obtained.

[0162] Optionally, the processing module 22 obtains a fault warning capability score for the intelligent servo motor, specifically for:

[0163] Based on the indicator test data corresponding to the sample representing accurate early warning of faults in the indicator test data and the indicator test data corresponding to all samples representing early warning of faults, the early warning accuracy score of the fault early warning capability of the intelligent servo is obtained.

[0164] Based on the accuracy score of the early warning, a fault early warning capability score for the intelligent servo motor is obtained.

[0165] Optionally, the processing module 22 obtains the auxiliary decision-making capability score of the intelligent servo motor, specifically for:

[0166] Based on the indicator test data corresponding to the samples representing successful decision creation and the indicator test data corresponding to all samples representing decision creation, the effectiveness score of the intelligent servo's auxiliary decision-making capability is obtained.

[0167] Based on the indicator test data corresponding to the samples representing effective creation decisions and the indicator test data corresponding to all samples representing creation decisions in the indicator test data, the diversity score of the auxiliary decision-making capability of the intelligent servo is obtained.

[0168] The auxiliary decision-making capability score of the intelligent servo is obtained based on the effectiveness score and the diversity score.

[0169] Optionally, when the processing module 22 determines the capability level of the intelligent servo motor based on at least one of the intelligent capability scores, it is specifically used for:

[0170] When the data acquisition capability score is greater than or equal to the first preset score, the fault alarm capability score is greater than or equal to the second preset score, the human-computer interaction capability score is greater than or equal to the third preset score, and the fault identification capability score is greater than or equal to the fourth preset score, the capability level of the intelligent servo motor is determined to be the first capability level.

[0171] When the intelligent servo meets the first capability level, and the health status assessment capability score of the intelligent servo is greater than or equal to the fifth preset score, and the fault warning capability score of the intelligent servo is greater than or equal to the sixth preset score, the capability level of the intelligent servo is determined to be the second capability level.

[0172] When the intelligent servo meets the second capability level and the auxiliary decision-making capability score of the intelligent servo is greater than or equal to the seventh preset score, the capability level of the intelligent servo is determined to be the third capability level.

[0173] It should be noted that this device is a device corresponding to the above-mentioned method for determining the capability level of intelligent servos. All implementation methods in the above-mentioned method embodiments are applicable to the embodiments of this device and can achieve the same technical effect.

[0174] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0175] Embodiments of the present invention also provide a computer-readable storage medium including instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0176] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0177] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0178] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0179] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0180] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0181] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0182] Furthermore, it should be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Moreover, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof. This is something that those skilled in the art can achieve by using their basic programming skills after reading the description of the present invention.

[0183] Therefore, the object of the present invention can also be achieved by running a program or a set of programs on any computing device. The computing device can be a known general-purpose device. Therefore, the object of the present invention can also be achieved simply by providing a program product containing program code implementing the method or apparatus. That is, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent to the present invention. Furthermore, the steps performing the above series of processes can naturally be performed in the order described, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0184] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining the capability level of an intelligent servo motor, characterized in that, include: Obtain test data for the intelligent servo motor's performance indicators; Based on the test data of the aforementioned indicators, the intelligent capability score of the intelligent servo motor is obtained. The intelligent capability score includes at least one of the following: data acquisition capability score, fault alarm capability score, human-computer interaction capability score, fault identification capability score, health status assessment capability score, fault early warning capability score, and decision support capability score. The capability level of the intelligent servo is determined based on at least one of the aforementioned intelligent capability scores; wherein obtaining the data acquisition capability score of the intelligent servo includes: Based on the indicator test data and preset data that meet the preset conditions in the indicator test data, the comprehensiveness score of the data acquisition capability of the intelligent servo motor is obtained. Based on the indicator test data corresponding to the samples that represent the accuracy of data acquisition and the indicator test data corresponding to all samples that represent the accuracy of data acquisition, the data acquisition accuracy score of the intelligent servo motor is obtained. Based on the actual collection period and the preset collection period of the test data of the aforementioned indicators, the periodicity score of the data collection capability of the intelligent servo motor is obtained. The data acquisition capability score of the intelligent servo motor is obtained based on the comprehensiveness score, the accuracy score, and the periodicity score. The data acquisition capability score of the intelligent servo motor is obtained based on the comprehensiveness score, the accuracy score, and the periodicity score, including: pass The data acquisition capability score of the intelligent servo motor is obtained; wherein, This indicates a score for data collection capabilities. This indicates the preset weights corresponding to each score. This represents the scores for each item, where j = 1, 2, 3; Among them, the comprehensiveness score was collected. : ;in, This indicates the comprehensiveness score of the data collection. , , , All are set constants; This indicates the number of index test data points actually collected at any sampling point under the preset conditions. Indicates the expected number of data points to be collected; Among them, the accuracy score of data collection : ;in, The score represents the accuracy of the data collection. This indicates the number of indicator test data points corresponding to samples that meet the accuracy requirements of the data collection. This represents the number of indicator test data points corresponding to all samples representing the accuracy of the data collection in the indicator test data. Among them, periodic scores are collected. : ;in, This indicates that scores are collected periodically. , , , , All of these are set constants, and T represents the actual acquisition period; Indicates the preset data collection period; The process of obtaining the auxiliary decision-making capability score of the intelligent servo motor includes: The effectiveness score of the intelligent servo's auxiliary decision-making capability is obtained based on the indicator test data corresponding to the sample representing the successful creation of the decision and the indicator test data corresponding to all samples representing the creation of the decision. Based on the indicator test data corresponding to the samples representing effective creation decisions and the indicator test data corresponding to all samples representing creation decisions in the indicator test data, the diversity score of the auxiliary decision-making capability of the intelligent servo is obtained. The auxiliary decision-making capability score of the intelligent servo is obtained based on the effectiveness score and the diversity score. Among them, according to The effectiveness score of the intelligent servo's auxiliary decision-making capability is determined; wherein, The score represents the effectiveness of the intelligent servo's decision-making assistance capability. , , , All of these are set constants. This indicates the number of indicator test data points in the indicator test data that correspond to the samples used to characterize the successful creation of decisions. This represents the number of indicator test data corresponding to all samples representing the creation decision in the indicator test data; Among them, according to The diversity score of the auxiliary decision-making capability of the intelligent servo motor is determined; wherein, The score represents the diversity of the intelligent servo's decision-making assistance capabilities. This indicates the number of test data points for indicators for which no valid solutions were provided. This indicates the number of test data points for a single valid solution. This indicates the number of test data points for multiple valid solutions. Among them, according to The auxiliary decision-making capability score of the intelligent servo motor was determined; among which This indicates the score for decision support capability. This indicates the preset weights corresponding to each score. This represents the scores for each item, t=1, 2; The fault alarm capability score of the intelligent servo motor includes: Based on the indicator test data corresponding to the missed fault samples and the indicator test data corresponding to the fault samples in the indicator test data, the missed alarm rate score of the fault alarm capability of the intelligent servo motor is obtained. Based on the indicator test data corresponding to the samples that were falsely reported as faults and the indicator test data corresponding to the normal samples in the indicator test data, the false alarm rate score of the fault alarm capability of the intelligent servo motor is obtained. The fault alarm capability score of the intelligent servo motor is obtained based on the false alarm rate score and the false alarm rate score. Among them, according to Determine the false negative rate score, where, The score represents the false negative rate. This indicates the number of indicator test data points corresponding to the missed fault samples in the indicator test data. This indicates the total number of indicator test data corresponding to the samples that experienced failures in the indicator test data; Among them, according to Determine the false positive rate score, where, The score represents the false alarm rate. This indicates the number of indicator test data points in the indicator test data that misreported normal samples as faulty samples. This indicates the number of indicator test data corresponding to all normal samples in the indicator test data; Among them, according to Determine the fault alarm capability score, among which, This indicates the score for fault alarm capability. The false negative rate score represents the score of the false negative rate. Preset weights, The false alarm rate score represents the false alarm rate score. Preset weights; The process of obtaining a human-machine interaction capability score for the intelligent servo motor includes: Based on the types of indicator test data that represent the interface display information in the indicator test data, the comprehensiveness score of the interface display information of the human-computer interaction capability of the intelligent servo is obtained. Based on the content of the indicator test data corresponding to the information displayed on the interface in the indicator test data, the information comprehension ease score of the human-computer interaction capability of the intelligent servo is obtained. Based on the types of indicator data representing interface operations in the indicator test data, the comprehensiveness score of the human-computer interaction capability of the intelligent servo motor is obtained. The human-computer interaction capability score of the intelligent servo motor is obtained based on the comprehensiveness score of the information displayed on the interface, the ease of understanding of the information, and the comprehensiveness score of the usage functions. The evaluation indicators characterizing the comprehensiveness of the display information of the intelligent servo motor human-machine interface include: whether the identification code or number of the device or sub-component is displayed, whether the status monitoring of the device or sub-component is displayed, and whether the health evaluation of the device or sub-component is displayed. The comprehensiveness score of the interface display information is determined based on the evaluation indicators. Specifically, when the content of the indicator test data corresponding to the information displayed on the interface is difficult to understand, the information comprehension ease score is 0; when the content of the indicator test data corresponding to the information displayed on the interface is comprehensible to a person with professional training, the information comprehension ease score is 0.6; when the content of the indicator test data corresponding to the information displayed on the interface is comprehensible to a person without professional training, the information comprehension ease score is 1. The indicators used to characterize the comprehensiveness of the intelligent servo's human-machine interface include: whether it supports anomaly variable labeling; whether it provides comprehensive safety protection; and whether the human-machine interaction is convenient. Specifically, regarding anomaly variable labeling: when significant anomaly quantity labeling is supported, the first comprehensiveness score is 1; when anomaly quantity labeling is not supported, the first comprehensiveness score is 0. Regarding comprehensive safety protection: when there is no access control hierarchy, the second comprehensiveness score is 0; when only access control hierarchy is available, the second comprehensiveness score is 0.6; when authorized access control hierarchy is available, the second comprehensiveness score is 1. Regarding the convenience of human-machine interaction: when input commands are required for control, the third comprehensiveness score is 0; when touchscreen button control is used, the third comprehensiveness score is 0.6; when voice interaction is used, the third comprehensiveness score is 1. The comprehensiveness score is determined based on these indicators characterizing the comprehensiveness of the intelligent servo's human-machine interface. The score for the comprehensiveness of the functionality is calculated; among which, The score indicates the comprehensiveness of the first-time user's functionality. Preset weights, This indicates the score for the comprehensiveness of the second-use functionality. Preset weights, This indicates the score for the comprehensiveness of the third-party usage function. Preset weights; Among them, according to Determine the human-machine interaction capability score of the intelligent servo motor, wherein This indicates a score for human-computer interaction capabilities. This indicates the preset weights corresponding to each score. Indicates the scores for each item; The fault identification capability score of the intelligent servo motor includes: Based on the indicator test data that accurately analyzes any fault sample and the indicator test data that represents the occurrence of the fault sample, the identification accuracy score of the intelligent servo motor's fault identification capability is obtained. Based on the indicator test data representing the types of fault samples and the indicator test data representing all types of fault samples in the indicator test data, the comprehensiveness score of the human-computer interaction capability of the intelligent servo is obtained. The fault identification capability score of the intelligent servo motor is obtained based on the identification accuracy score and the identification comprehensiveness score. Among them, according to Determine the recognition accuracy score, where, The score represents the accuracy of the recognition. This indicates the number of indicator test data points in the indicator test data that accurately represent the analysis of any fault sample. This indicates the number of indicator test data corresponding to all types of fault samples in the indicator test data; Among them, according to Determine the comprehensiveness score, among which, This indicates the score for comprehensiveness of recognition. This indicates the number of indicator test data points in the indicator test data that represent the types of fault samples. This represents the number of indicator test data corresponding to all samples representing all types of faults in the indicator test data; Among them, according to Determine the fault identification capability score, among which, This indicates the preset weights corresponding to each score. Indicates the scores for each item; The ability to obtain a health status assessment score for the intelligent servo motor includes: Based on the indicator test data corresponding to the sample representing the accurate assessment of health status in the indicator test data and the indicator test data corresponding to all samples representing the assessment of health status, the assessment accuracy score of the health status assessment capability of the intelligent servo is obtained. Based on the accuracy score of the assessment, a health status assessment capability score for the intelligent servo motor is obtained; Among them, according to Determine the accuracy score of the assessment, whereby, Indicates the accuracy score of the assessment. , , , All of these are set constants. This indicates the number of indicator test data points in the indicator test data that correspond to the samples used to accurately assess health status. This represents the number of indicator test data points corresponding to all samples representing the assessed health status in the indicator test data; wherein, obtaining the fault warning capability score of the intelligent servo includes: Based on the indicator test data corresponding to the sample representing accurate early warning of faults in the indicator test data and the indicator test data corresponding to all samples representing early warning of faults, the early warning accuracy score of the fault early warning capability of the intelligent servo is obtained. Based on the accuracy score of the early warning, the fault early warning capability score of the intelligent servo motor is obtained; Among them, according to Determine the accuracy score of the early warning, among which, The score indicates the accuracy of the early warning. , , , All of these are set constants. This indicates the number of indicator test data points corresponding to the samples used to accurately predict faults in the indicator test data. This indicates the number of indicator test data corresponding to all samples representing early warning faults in the indicator test data.

2. The method for determining the capability level of an intelligent servo motor according to claim 1, characterized in that, The capability level of the intelligent servo is determined based on at least one of the aforementioned intelligent capability scores, including: When the data acquisition capability score is greater than or equal to the first preset score, the fault alarm capability score is greater than or equal to the second preset score, the human-computer interaction capability score is greater than or equal to the third preset score, and the fault identification capability score is greater than or equal to the fourth preset score, the capability level of the intelligent servo motor is determined to be the first capability level. When the intelligent servo meets the first capability level, and the health status assessment capability score of the intelligent servo is greater than or equal to the fifth preset score, and the fault warning capability score of the intelligent servo is greater than or equal to the sixth preset score, the capability level of the intelligent servo is determined to be the second capability level. When the intelligent servo meets the second capability level and the auxiliary decision-making capability score of the intelligent servo is greater than or equal to the seventh preset score, the capability level of the intelligent servo is determined to be the third capability level.

3. A device for determining the capability level of an intelligent servo motor, characterized in that, include: The acquisition module is used to acquire the performance test data of the intelligent servo motor; The processing module is configured to obtain at least one intelligent capability score of the intelligent servo based on the indicator test data, wherein the at least one intelligent capability score includes: data acquisition capability score, fault alarm capability score, human-machine interaction capability score, fault identification capability score, health status assessment capability score, fault early warning capability score, and decision support capability score; and determine the capability level of the intelligent servo based on the at least one intelligent capability score. The data acquisition capability score of the intelligent servo motor includes: Based on the indicator test data and preset data that meet the preset conditions in the indicator test data, the comprehensiveness score of the data acquisition capability of the intelligent servo motor is obtained. Based on the indicator test data corresponding to the samples that represent the accuracy of data acquisition and the indicator test data corresponding to all samples that represent the accuracy of data acquisition, the data acquisition accuracy score of the intelligent servo motor is obtained. Based on the actual collection period and the preset collection period of the test data of the aforementioned indicators, the periodicity score of the data collection capability of the intelligent servo motor is obtained. The data acquisition capability score of the intelligent servo motor is obtained based on the comprehensiveness score, the accuracy score, and the periodicity score. The data acquisition capability score of the intelligent servo motor is obtained based on the comprehensiveness score, the accuracy score, and the periodicity score, including: pass The data acquisition capability score of the intelligent servo motor is obtained; wherein, This indicates a score for data collection capabilities. This indicates the preset weights corresponding to each score. This represents the scores for each item, where j = 1, 2, 3; Among them, the comprehensiveness score was collected. : ;in, This indicates the comprehensiveness score of the data collection. , , , All are set constants; This indicates the number of index test data points actually collected at any sampling point under the preset conditions. Indicates the expected number of data points to be collected; Among them, the accuracy score of data collection : ;in, The score represents the accuracy of the data collection. This indicates the number of indicator test data points corresponding to samples that meet the accuracy requirements of the data collection. This represents the number of indicator test data corresponding to all samples that characterize the accuracy of the data collection in the indicator test data; Among them, periodic scores are collected. : ;in, This indicates that scores are collected periodically. , , , , All of these are set constants, and T represents the actual acquisition period; Indicates the preset data collection period; The process of obtaining the auxiliary decision-making capability score of the intelligent servo motor includes: The effectiveness score of the intelligent servo's auxiliary decision-making capability is obtained based on the indicator test data corresponding to the sample representing the successful creation of the decision and the indicator test data corresponding to all samples representing the creation of the decision. Based on the indicator test data corresponding to the samples representing effective creation decisions and the indicator test data corresponding to all samples representing creation decisions in the indicator test data, the diversity score of the auxiliary decision-making capability of the intelligent servo is obtained. The auxiliary decision-making capability score of the intelligent servo is obtained based on the effectiveness score and the diversity score. Among them, according to The effectiveness score of the intelligent servo's auxiliary decision-making capability is determined; wherein, The score represents the effectiveness of the intelligent servo's decision-making assistance capability. , , , All of these are set constants. This indicates the number of indicator test data points in the indicator test data that correspond to the samples used to characterize the successful creation of decisions. This represents the number of indicator test data corresponding to all samples representing the creation decision in the indicator test data; Among them, according to The diversity score of the auxiliary decision-making capability of the intelligent servo motor is determined; wherein, The score represents the diversity of the intelligent servo's decision-making assistance capabilities. This indicates the number of test data points for indicators for which no valid solutions were provided. This indicates the number of test data points for a single valid solution. This indicates the number of test data points for multiple valid solutions. Among them, according to The auxiliary decision-making capability score of the intelligent servo motor was determined; among which This indicates the score for decision support capability. This indicates the preset weights corresponding to each score. This represents the scores for each item, t=1, 2; The fault alarm capability score of the intelligent servo motor includes: Based on the indicator test data corresponding to the missed fault samples and the indicator test data corresponding to the fault samples in the indicator test data, the missed alarm rate score of the fault alarm capability of the intelligent servo motor is obtained. Based on the indicator test data corresponding to the samples that were falsely reported as faults and the indicator test data corresponding to the normal samples in the indicator test data, the false alarm rate score of the fault alarm capability of the intelligent servo motor is obtained. The fault alarm capability score of the intelligent servo motor is obtained based on the false alarm rate score and the false alarm rate score. Among them, according to Determine the false negative rate score, where, The score represents the false negative rate. This indicates the number of indicator test data points corresponding to the missed fault samples in the indicator test data. This indicates the total number of indicator test data corresponding to the samples that experienced failures in the indicator test data; Among them, according to Determine the false positive rate score, where, The score represents the false alarm rate. This indicates the number of indicator test data points in the indicator test data that misreported normal samples as faulty samples. This indicates the number of indicator test data corresponding to all normal samples in the indicator test data; Among them, according to Determine the fault alarm capability score, among which, This indicates the score for fault alarm capability. The false negative rate score represents the score of the false negative rate. Preset weights, The false alarm rate score represents the false alarm rate score. Preset weights; The process of obtaining a human-machine interaction capability score for the intelligent servo motor includes: Based on the types of indicator test data that represent the interface display information in the indicator test data, the comprehensiveness score of the interface display information of the human-computer interaction capability of the intelligent servo is obtained. Based on the content of the indicator test data corresponding to the information displayed on the interface in the indicator test data, the information comprehension ease score of the human-computer interaction capability of the intelligent servo is obtained. Based on the types of indicator data representing interface operations in the indicator test data, the comprehensiveness score of the human-computer interaction capability of the intelligent servo motor is obtained. The human-computer interaction capability score of the intelligent servo motor is obtained based on the comprehensiveness score of the information displayed on the interface, the ease of understanding of the information, and the comprehensiveness score of the usage functions. The evaluation indicators characterizing the comprehensiveness of the display information of the intelligent servo motor human-machine interface include: whether the identification code or number of the device or sub-component is displayed, whether the status monitoring of the device or sub-component is displayed, and whether the health evaluation of the device or sub-component is displayed. The comprehensiveness score of the interface display information is determined based on the evaluation indicators. Specifically, when the content of the indicator test data corresponding to the information displayed on the interface is difficult to understand, the information comprehension ease score is 0; when the content of the indicator test data corresponding to the information displayed on the interface is comprehensible to a person with professional training, the information comprehension ease score is 0.6; when the content of the indicator test data corresponding to the information displayed on the interface is comprehensible to a person without professional training, the information comprehension ease score is 1. The indicators used to characterize the comprehensiveness of the intelligent servo's human-machine interface include: whether it supports anomaly variable labeling; whether it provides comprehensive safety protection; and whether the human-machine interaction is convenient. Specifically, regarding anomaly variable labeling: when significant anomaly quantity labeling is supported, the first comprehensiveness score is 1; when anomaly quantity labeling is not supported, the first comprehensiveness score is 0. Regarding comprehensive safety protection: when there is no access control hierarchy, the second comprehensiveness score is 0; when only access control hierarchy is available, the second comprehensiveness score is 0.6; when authorized access control hierarchy is available, the second comprehensiveness score is 1. Regarding the convenience of human-machine interaction: when input commands are required for control, the third comprehensiveness score is 0; when touchscreen button control is used, the third comprehensiveness score is 0.6; when voice interaction is used, the third comprehensiveness score is 1. The comprehensiveness score is determined based on these indicators characterizing the comprehensiveness of the intelligent servo's human-machine interface. The score for the comprehensiveness of the functionality is calculated; among which, The score indicates the comprehensiveness of the first-time user's functionality. Preset weights, This indicates the score for the comprehensiveness of the second-use functionality. Preset weights, This indicates the score for the comprehensiveness of the third-party usage function. Preset weights; Among them, according to Determine the human-machine interaction capability score of the intelligent servo motor, wherein This indicates a score for human-computer interaction capabilities. This indicates the preset weights corresponding to each score. Indicates the scores for each item; The fault identification capability score of the intelligent servo motor includes: Based on the indicator test data that accurately analyzes any fault sample and the indicator test data that represents the occurrence of the fault sample, the identification accuracy score of the intelligent servo motor's fault identification capability is obtained. Based on the indicator test data representing the types of fault samples and the indicator test data representing all types of fault samples in the indicator test data, the comprehensiveness score of the human-computer interaction capability of the intelligent servo is obtained. The fault identification capability score of the intelligent servo motor is obtained based on the identification accuracy score and the identification comprehensiveness score. Among them, according to Determine the recognition accuracy score, where, The score represents the accuracy of the recognition. This indicates the number of indicator test data points in the indicator test data that accurately represent the analysis of any fault sample. This indicates the number of indicator test data corresponding to all types of fault samples in the indicator test data; Among them, according to Determine the comprehensiveness score, among which, This indicates the score for comprehensiveness of recognition. This indicates the number of indicator test data points in the indicator test data that represent the types of fault samples. This represents the number of indicator test data corresponding to all samples representing all types of faults in the indicator test data; Among them, according to Determine the fault identification capability score, among which, This indicates the preset weights corresponding to each score. Indicates the scores for each item; The ability to obtain a health status assessment score for the intelligent servo motor includes: Based on the indicator test data corresponding to the sample representing the accurate assessment of health status in the indicator test data and the indicator test data corresponding to all samples representing the assessment of health status, the assessment accuracy score of the health status assessment capability of the intelligent servo is obtained. Based on the accuracy score of the assessment, a health status assessment capability score for the intelligent servo motor is obtained; Among them, according to Determine the accuracy score of the assessment, whereby, Indicates the accuracy score of the assessment. , , , All of these are set constants. This indicates the number of indicator test data points in the indicator test data that correspond to the samples used to accurately assess health status. This represents the number of indicator test data corresponding to all samples that characterize and assess health status in the indicator test data; The fault warning capability score of the intelligent servo motor includes: Based on the indicator test data corresponding to the sample representing accurate early warning of faults in the indicator test data and the indicator test data corresponding to all samples representing early warning of faults, the early warning accuracy score of the fault early warning capability of the intelligent servo is obtained. Based on the accuracy score of the early warning, the fault early warning capability score of the intelligent servo motor is obtained; Among them, according to Determine the accuracy score of the early warning, among which, The score indicates the accuracy of the early warning. , , , All of these are set constants. This indicates the number of indicator test data points corresponding to the samples used to accurately predict faults in the indicator test data. This indicates the number of indicator test data corresponding to all samples representing early warning faults in the indicator test data.

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