Equipment health management system scheme optimization method based on performance evaluation

Abstract

The invention belongs to the technical field of equipment health management, and particularly relates to an efficiency evaluation-based equipment health management system scheme optimization method, which comprises the following steps of: constructing an efficiency evaluation system of an equipment health management system; setting a first-level capability index weight of the efficiency evaluation system of the equipment health management system; establishing a second-level capability index quantification criterion of the performance evaluation system; performing quantitative evaluation on secondary capability indexes of the schemes of the equipment health management system; excluding the equipment health management system scheme with the lack of the second-level capability; analyzing principal components of secondary capability indexes of the efficiency evaluation system of the equipment health management system; comprehensively evaluating each scheme of the equipment health management system; and preferably, a health management system scheme is provided. According to the optimization method, comprehensive scoring of all the schemes of the health management system is achieved, the technical problem of scheme optimization of the health management system is successfully solved, and the method can be applied to scheme optimization of any equipment health management system.

Description

Technical Field

[0001] This invention belongs to the field of equipment health management technology, specifically to a method for optimizing equipment health management system solutions based on performance evaluation. By analyzing the design requirements of equipment health management system solutions and integrating them with a health management system performance evaluation system, this method is established to optimize health management system design solutions. This invention can be applied to optimizing the design of any health management system solution. Background Art

[0002] With the increasing complexity and degree of electrification of equipment, the cost of equipment maintenance and support is increasing day by day. Traditional scheduled maintenance can no longer meet the requirements of high equipment availability and low operating costs. The health management system has gradually developed into a key subsystem of the equipment. The health management system is responsible for data management, status monitoring, fault prediction and other equipment operating status control, and can provide technical support for equipment maintenance based on the situation. The health management system involves multiple functions such as data collection, data communication, fault diagnosis, status assessment, performance prediction and fault alarm. Evaluating the design scheme of the health management system is a complex engineering problem. At present, the selection of health management system schemes usually adopts empirical methods for subjective evaluation. In this way, when optimizing multiple schemes, it is very easy to cause evaluation bias due to personal experience bias, which affects the selection results. Research on the optimization method of health management system schemes based on performance evaluation is of great significance to the design and optimization of health management system schemes.

[0003] After searching relevant patents and literature at home and abroad, a method for evaluating equipment information assurance capability was found (CN118396480 B), which proposed an equipment information assurance capability evaluation method based on an equipment information assurance capability evaluation index system and principal component analysis. The 11th issue of Ship Electronic Engineering in 2023, "Effectiveness Evaluation of Unmanned Combat Systems Based on Principal Component Analysis," proposed a method for evaluating unmanned combat effectiveness based on unmanned combat system effectiveness indicators and principal component analysis. These two comparative data have the following problems: 1. Only the principal components of the bottom-level indicators are considered during principal component analysis, and the influence weights of the upper-level indicators are not considered. When the weight factors of the upper-level indicators are inconsistent, it will cause evaluation bias; 2. The system function loss corresponding to the bottom-level indicators is not considered, which can easily cause the selected results to have function loss items, resulting in evaluation errors. In response to the technical defects existing in the comparative documents, the present invention combines the core function evaluation requirements of the health management system to establish a health management system effectiveness evaluation index system and a health management system solution optimization method, solving the problem of health management system design solution optimization. Summary of the Invention

[0004] (1) Technical issues to be resolved

[0005] The technical problem to be solved by the present invention is: how to provide an equipment health management system solution optimization method based on performance evaluation, which can be applied to any health management system solution design optimization, realize the optimization of equipment health management system design solutions, and improve the efficiency of health management system development.

[0006] (2) Technical solution

[0007] To solve the above technical problems, the present invention provides a method for optimizing equipment health management system solutions based on performance evaluation, the method comprising the following steps:

[0008] Step S1: Constructing an equipment health management system effectiveness evaluation system;

[0009] Step S2: Setting the weight of the first-level capability indicator of the equipment health management system performance evaluation system;

[0010] Step S3: Establishing quantitative criteria for the secondary capability indicators of the effectiveness evaluation system;

[0011] Step S4: Quantitatively evaluate the secondary capability indicators of each scheme of the equipment health management system;

[0012] Step S5: Eliminate equipment health management system solutions with secondary capability deficiencies;

[0013] Step S6: Analyze the principal components of the secondary capability indicators of the equipment health management system effectiveness evaluation system;

[0014] Step S7: Comprehensively evaluate each solution of the equipment health management system;

[0015] Step S8: Optimize the equipment health management system solution.

[0016] Wherein, in said step S1, an equipment health management system performance evaluation system is constructed;

[0017] Based on the principle of constructing a hierarchical indicator system, and in accordance with the evaluation requirements of equipment core functions and the requirements for simple optimization of equipment health management system solutions, an equipment health management system effectiveness evaluation system is constructed, including:

[0018] Three first-level capability indicators: information perception and interaction capability A, information processing and evaluation capability B, and maintenance and support capability C;

[0019] As well as ten secondary capability indicators including information perception coverage, information perception effectiveness, information display integrity, information interaction convenience, fault detection rate, fault isolation rate, status assessment accuracy, performance prediction accuracy, maintenance plan coverage, and maintenance plan rationality.

[0020] Wherein, in said step S2, the weight of the first-level capability index of the equipment health management system performance evaluation system is set;

[0021] According to the core functional requirements of the equipment, the first-level capability indicators of the effectiveness evaluation system are set, and the weights of the information perception and interaction capability A, information processing and evaluation capability B, and maintenance and support capability C are α1, α2, and α3 respectively.

[0022] Wherein, in said step S3, a quantitative criterion for the secondary capability index of the performance evaluation system is established;

[0023] Quantify the ten secondary capability indicators in the equipment health management system effectiveness evaluation system;

[0024] 1) Information perception coverage β1; refers to the information T that the equipment health management system can perceive and the information T that the equipment needs to perceive req The quantitative calculation formula is as follows:

[0025]

[0026] 2) Information perception effectiveness β2 refers to the authenticity and effectiveness of the information obtained by the equipment health management system. The quantitative calculation formula is as follows:

[0027]

[0028] Where L1 is the information frame loss rate, L low L is the minimum frame loss rate that fully meets the information requirements. high The maximum frame loss rate that the information can meet the requirements;

[0029] 3) Information display integrity β3; refers to the information that the equipment health management system can display I and the information that needs to be displayed I req The quantitative calculation formula is as follows:

[0030]

[0031] 4) Information interaction convenience β4: refers to the convenience of entering and querying equipment information when using the equipment health management system, expressed as a percentage, with a value range of [0, 1];

[0032] 5) Fault detection rate β5; refers to the number of faults that the equipment health management system can correctly detect V d Total number of failures V t The quantitative calculation formula is as follows:

[0033]

[0034] 6) Fault isolation rate β6; refers to the number of faults correctly isolated to replaceable units by the equipment health management system V lThe number of correctly detected faults V d The quantitative calculation formula is as follows:

[0035]

[0036] 7) Status assessment accuracy β7 refers to the accuracy of the equipment health management system's assessment of the equipment's core performance. The quantitative calculation formula is as follows:

[0037]

[0038] Where C1 is the accuracy of state assessment, C low is the lower limit of state assessment accuracy, C high The upper limit of the accuracy of the state assessment;

[0039] 8) Performance prediction accuracy β8 refers to the accuracy of the equipment health management system in predicting the degradation trend of the equipment's core performance. The quantitative calculation formula is as follows:

[0040]

[0041] Where P1 is the performance prediction accuracy, P low is the lower limit of performance prediction accuracy, P high is the upper limit of performance prediction accuracy;

[0042] 9) Maintenance plan coverage β9; refers to the difference between the maintenance plan Q that can be generated by the equipment health management system and the maintenance plan Q that needs to be generated req The quantitative calculation formula is as follows:

[0043]

[0044] 10) Reasonableness of maintenance plan β 10 ; Refers to whether the maintenance plan generated by the equipment health management system can meet the maintenance needs, displayed as a percentage, and the value range is [0, 1].

[0045] Wherein, in said step S4, a quantitative evaluation of the secondary capability indicators of each scheme of the equipment health management system is performed;

[0046] According to the secondary capability index quantification criteria of the equipment health management system effectiveness evaluation system, the secondary capability index quantitative evaluation of each scheme of the health management system is carried out, and the secondary capability index quantitative value is marked as β mp , β mp Represents the quantitative value of the pth secondary capability indicator of the mth solution.

[0047] Wherein, in said step S5, the equipment health management system scheme with secondary capability deficiency is excluded;

[0048] The quantitative values ​​of the secondary capability indicators of each device health management system solution are analyzed, and the health management system solution with a quantitative value of 0 is eliminated. The quantitative value of the secondary capability indicator after the solution is eliminated is marked as β np , β np Represents the quantitative value of the pth secondary capability indicator of the nth solution.

[0049] Wherein, in said step S6, the principal components of the secondary capability indicators of the equipment health management system effectiveness evaluation system are analyzed;

[0050] According to the weights of the first-level capability indicators of the performance evaluation system and the quantitative values ​​of the second-level capability indicators of each scheme, the principal components of the second-level capability indicators of the preferred scheme are analyzed and determined.

[0051] Wherein, the step S6 includes:

[0052] Step S61: Determine the quantitative evaluation value of the secondary capability indicator of each scheme; determine the quantitative evaluation value γ of the secondary capability indicator of each scheme based on the weight of the primary capability indicator and the quantitative value of the secondary capability indicator of each scheme ij , γ ij Represents the quantitative evaluation value of the jth secondary capability indicator of the i-th scheme;

[0053]

[0054] Step S62: Establishing a secondary capability indicator matrix for the equipment health management system; establishing a secondary capability indicator matrix M of the equipment health management system for n equipment health management system solutions after eliminating the functional deficiency solutions and p secondary capability indicators based on the quantified values ​​of the secondary capability indicators;

[0055]

[0056] Step S63: Perform dimensionless processing on the secondary capability indicator matrix; use the standard score method to perform dimensionless transformation on the secondary capability indicator matrix, and obtain the matrix M * :

[0057]

[0058] Where,

[0059] Step S64: Determine the correlation coefficient matrix of the dimensionless matrix of the secondary capability index; calculate M * The correlation coefficient matrix R of the matrix:

[0060]

[0061] Step S65: Determine the eigenvalues ​​and eigenvectors of the correlation coefficient matrix; perform eigenvalue decomposition on the correlation coefficient matrix R to obtain the eigenvalues ​​of the matrix R λ1≥λ2≥…≥λ p ≥0 and the corresponding orthogonal unit eigenvectors t1, t2, ...t p ;

[0062] Step S66: Determine the principal component contribution rate of the secondary capability index (S66); the jth principal component y in the secondary capability index j for:

[0063] y j =(x * ) T ×t j (j=1,2,…,p)

[0064] Where x * =(x1 * , x2 * …,x p * ) T is the standardized sample value;

[0065] Principal component y j Contribution rate C j for:

[0066]

[0067] The cumulative contribution rate of the principal component Q j for:

[0068]

[0069] Step S67: Determine the principal component of the secondary capability index (S67); select the orthogonal unit eigenvectors corresponding to q eigenvalues ​​with cumulative contribution rates greater than 85% as the principal components, and the principal component eigenvalues ​​are λ1, λ2, ..., λ q , the orthogonal unit eigenvectors are t1, t2, ...t q .

[0070] Wherein, in said step S7, a comprehensive evaluation is performed on each scheme of the equipment health management system;

[0071] Determine the comprehensive score of each equipment health management system scheme based on the main components of the secondary capability indicators;

[0072] The step S7 comprises:

[0073] Step S71: Determine the principal component score of each secondary capability indicator: i for:

[0074] Fi =w i1 M1+w i2 M2+…+w in M n

[0075] Where, is the weight of each variable in the principal component, θ j is the coefficient corresponding to each variable of the principal component;

[0076] Step S72: Determine the comprehensive score of each solution of the equipment health management system; the comprehensive score F of each solution of the health management system is:

[0077] F=μ1F1+μ2F2+…+μ n F n

[0078] Where μ i is the percentage of variance of the i-th principal component.

[0079] Among them, in the step S8, the health management system solution is preferred; the comprehensive scores of the equipment health management system solutions are ranked, and the solution with the highest score is the preferred solution.

[0080] (3) Beneficial effects

[0081] Compared with the prior art, the present invention has the following effects:

[0082] This health management system solution optimization method establishes a health management system effectiveness evaluation system, combines the elimination of functionally deficient solutions, high-level evaluation weight assignment and principal component analysis methods, and achieves a comprehensive score for each health management system solution, successfully solving the technical problems of health management system solution optimization. This method can be applied to the solution optimization of any equipment health management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 This is a flow chart of the preferred embodiment of the health management system of the present invention;

[0084] Figure 2 Schematic diagram of the health management system effectiveness evaluation system of the present invention;

[0085] Figure 3 This is a flow chart of principal component analysis of secondary capability indicators of the present invention;

[0086] Figure 4 This is a flow chart for comprehensive scoring of various solutions of the health management system of the present invention. DETAILED DESCRIPTION

[0087] In order to make the purpose, content, and advantages of the present invention more clear, the specific implementation methods of the present invention are further described in detail below with reference to the accompanying drawings and examples.

[0088] To solve the above technical problems, the present invention provides a method for optimizing equipment health management system solutions based on performance evaluation, the method comprising the following steps:

[0089] Step S1: Constructing an equipment health management system effectiveness evaluation system;

[0090] Step S2: Setting the weight of the first-level capability indicator of the equipment health management system performance evaluation system;

[0091] Step S3: Establishing quantitative criteria for the secondary capability indicators of the effectiveness evaluation system;

[0092] Step S4: Quantitatively evaluate the secondary capability indicators of each solution of the equipment health management system;

[0093] Step S5: Eliminate equipment health management system solutions with secondary capability deficiencies;

[0094] Step S6: Analyze the principal components of the secondary capability indicators of the equipment health management system effectiveness evaluation system;

[0095] Step S7: Comprehensively evaluate each solution of the equipment health management system;

[0096] Step S8: Optimize the equipment health management system solution.

[0097] Wherein, in said step S1, an equipment health management system performance evaluation system is constructed;

[0098] Based on the principle of constructing a hierarchical indicator system, and in accordance with the evaluation requirements of equipment core functions and the requirements for simple optimization of equipment health management system solutions, an equipment health management system effectiveness evaluation system is constructed, including:

[0099] Three first-level capability indicators: information perception and interaction capability A, information processing and evaluation capability B, and maintenance and support capability C;

[0100] As well as ten secondary capability indicators including information perception coverage, information perception effectiveness, information display integrity, information interaction convenience, fault detection rate, fault isolation rate, status assessment accuracy, performance prediction accuracy, maintenance plan coverage, and maintenance plan rationality.

[0101] Wherein, in said step S2, the weight of the first-level capability index of the equipment health management system performance evaluation system is set;

[0102] According to the core functional requirements of the equipment, the first-level capability indicators of the effectiveness evaluation system are set, and the weights of the information perception and interaction capability A, information processing and evaluation capability B, and maintenance and support capability C are α1, α2, and α3 respectively.

[0103] Wherein, in said step S3, a quantitative criterion for the secondary capability index of the performance evaluation system is established;

[0104] Quantify the ten secondary capability indicators in the equipment health management system effectiveness evaluation system;

[0105] 1) Information perception coverage β1; refers to the information T that the equipment health management system can perceive and the information T that the equipment needs to perceive req The quantitative calculation formula is as follows:

[0106]

[0107] 2) Information perception effectiveness β2 refers to the authenticity and effectiveness of the information obtained by the equipment health management system. The quantitative calculation formula is as follows:

[0108]

[0109] Where L1 is the information frame loss rate, L low L is the minimum frame loss rate that fully meets the information requirements. high The maximum frame loss rate that the information can meet the requirements;

[0110] 3) Information display integrity β3; refers to the information that the equipment health management system can display I and the information that needs to be displayed I req The quantitative calculation formula is as follows:

[0111]

[0112] 4) Information interaction convenience β4: refers to the convenience of entering and querying equipment information when using the equipment health management system, expressed as a percentage, with a value range of [0, 1];

[0113] 5) Fault detection rate β5; refers to the number of faults that the equipment health management system can correctly detect V d Total number of failures V t The quantitative calculation formula is as follows:

[0114]

[0115] 6) Fault isolation rate β6; refers to the number of faults correctly isolated to replaceable units by the equipment health management system V l The number of correctly detected faults V d The quantitative calculation formula is as follows:

[0116]

[0117] 7) Status assessment accuracy β7 refers to the accuracy of the equipment health management system's assessment of the equipment's core performance. The quantitative calculation formula is as follows:

[0118]

[0119] Where C1 is the accuracy of state assessment, C low is the lower limit of state assessment accuracy, C high The upper limit of the accuracy of the state assessment;

[0120] 8) Performance prediction accuracy β8 refers to the accuracy of the equipment health management system in predicting the degradation trend of the equipment's core performance. The quantitative calculation formula is as follows:

[0121]

[0122] Where P1 is the performance prediction accuracy, P low is the lower limit of performance prediction accuracy, P high is the upper limit of performance prediction accuracy;

[0123] 9) Maintenance plan coverage β9; refers to the difference between the maintenance plan Q that can be generated by the equipment health management system and the maintenance plan Q that needs to be generated req The quantitative calculation formula is as follows:

[0124]

[0125] 10) Reasonableness of maintenance plan β 10 ; Refers to whether the maintenance plan generated by the equipment health management system can meet the maintenance needs, displayed as a percentage, and the value range is [0, 1].

[0126] Wherein, in said step S4, a quantitative evaluation of the secondary capability indicators of each scheme of the equipment health management system is performed;

[0127] According to the secondary capability index quantification criteria of the equipment health management system effectiveness evaluation system, the secondary capability index quantitative evaluation of each scheme of the health management system is carried out, and the secondary capability index quantitative value is marked as β mp , β mp Represents the quantitative value of the pth secondary capability indicator of the mth solution.

[0128] Wherein, in said step S5, the equipment health management system scheme with secondary capability deficiency is excluded;

[0129] The quantitative values ​​of the secondary capability indicators of each device health management system solution are analyzed, and the health management system solution with a quantitative value of 0 is eliminated. The quantitative value of the secondary capability indicator after the solution is eliminated is marked as βnp , β np Represents the quantitative value of the pth secondary capability indicator of the nth solution.

[0130] Wherein, in said step S6, the principal components of the secondary capability indicators of the equipment health management system effectiveness evaluation system are analyzed;

[0131] According to the weights of the first-level capability indicators of the performance evaluation system and the quantitative values ​​of the second-level capability indicators of each scheme, the principal components of the second-level capability indicators of the preferred scheme are analyzed and determined.

[0132] Wherein, the step S6 includes:

[0133] Step S61: Determine the quantitative evaluation value of the secondary capability indicator of each scheme; determine the quantitative evaluation value γ of the secondary capability indicator of each scheme based on the weight of the primary capability indicator and the quantitative value of the secondary capability indicator of each scheme ij , γ ij Represents the quantitative evaluation value of the jth secondary capability indicator of the i-th scheme;

[0134]

[0135] Step S62: Establishing a secondary capability indicator matrix for the equipment health management system; establishing a secondary capability indicator matrix M of the equipment health management system for n equipment health management system solutions after eliminating the functional deficiency solutions and p secondary capability indicators based on the quantified values ​​of the secondary capability indicators;

[0136]

[0137] Step S63: Perform dimensionless processing on the secondary capability indicator matrix; use the standard score method to perform dimensionless transformation on the secondary capability indicator matrix, and obtain the matrix M * :

[0138]

[0139] Where,

[0140] Step S64: Determine the correlation coefficient matrix of the dimensionless matrix of the secondary capability index; calculate M * The correlation coefficient matrix R of the matrix:

[0141]

[0142] Step S65: Determine the eigenvalues ​​and eigenvectors of the correlation coefficient matrix; perform eigenvalue decomposition on the correlation coefficient matrix R to obtain the eigenvalues ​​of the matrix R λ1≥λ2≥…≥λ p ≥0 and the corresponding orthogonal unit eigenvectors t1, t2, ...t p ;

[0143] Step S66: Determine the principal component contribution rate of the secondary capability index (S66); the jth principal component y in the secondary capability index j for:

[0144] y j =(x * ) T ×t j (j=1,2,…,p)

[0145] Where x * =(x1 * , x2 * …,x p * ) T is the standardized sample value;

[0146] Principal component y j Contribution rate C j for:

[0147]

[0148] The cumulative contribution rate of the principal component Q j for:

[0149]

[0150] Step S67: Determine the principal component of the secondary capability index (S67); select the orthogonal unit eigenvectors corresponding to q eigenvalues ​​with cumulative contribution rates greater than 85% as the principal components, and the principal component eigenvalues ​​are λ1, λ2, ..., λ q , the orthogonal unit eigenvectors are t1, t2, ...t q .

[0151] Wherein, in said step S7, a comprehensive evaluation is performed on each scheme of the equipment health management system;

[0152] Determine the comprehensive score of each equipment health management system scheme based on the main components of the secondary capability indicators;

[0153] The step S7 comprises:

[0154] Step S71: Determine the principal component score of each secondary capability indicator: i for:

[0155] F i =w i1 M1+w i2 M2+…+w in M n

[0156] Where, is the weight of each variable in the principal component, θ j is the coefficient corresponding to each variable of the principal component;

[0157] Step S72: Determine the comprehensive score of each solution of the equipment health management system; the comprehensive score F of each solution of the health management system is:

[0158] F=μ1F1+μ2F2+…+μ n F n

[0159] Where μ i is the percentage of variance of the i-th principal component.

[0160] Among them, in the step S8, the health management system solution is preferred; the comprehensive scores of the equipment health management system solutions are ranked, and the solution with the highest score is the preferred solution.

[0161] Example 1

[0162] In order to better understand the present invention, the following is a detailed description of the present invention. Figure 1 Health management system solution optimization process, attachment Figure 2 Health management system effectiveness evaluation system, Figure 3 Secondary capability index principal component analysis process, attached Figure 4 The comprehensive scoring process of each scheme of the health management system is described in detail.

[0163] (1) Construct a health management system effectiveness evaluation system; the equipment health management system effectiveness evaluation system includes three first-level capability indicators: information perception and interaction capability (A), information processing and evaluation capability (B), and maintenance and support capability (C), as well as ten second-level capability indicators: information perception coverage, information perception effectiveness, information display integrity, information interaction convenience, fault detection rate, fault isolation rate, status assessment accuracy, performance prediction accuracy, maintenance plan coverage, and maintenance plan rationality.

[0164] (2) Set the weights of the first-level capability indicators of the health management system effectiveness evaluation system; based on the core functional requirements of the equipment, adopt the expert experience method and set the weights of the first-level capability indicators of the effectiveness evaluation system, namely, information perception and interaction capability (A), information processing and evaluation capability (B), and maintenance and support capability (C), as α1, α2, and α3 respectively;

[0165] (3) Establish quantitative criteria for the secondary capability indicators of the effectiveness evaluation system; quantify the ten secondary capability indicators in the equipment health management system effectiveness evaluation system;

[0166] (301) Information perception coverage; refers to the information T that the equipment health management system can perceive and the information T that the equipment needs to perceive. reqThe quantitative calculation formula is as follows:

[0167]

[0168] (302) Information perception validity refers to the authenticity and validity of information obtained by the equipment health management system. The quantitative calculation formula is as follows:

[0169]

[0170] Where L1 is the information frame loss rate, L low L is the minimum frame loss rate that fully meets the information requirements. high The maximum frame loss rate that the information can meet the requirements.

[0171] (303) Information display integrity; refers to the equipment health management system can display information I and need to display information I req The quantitative calculation formula is as follows:

[0172]

[0173] (304) Information interaction convenience: refers to the convenience of entering and querying equipment information when using the equipment health management system. Experts assign β4 based on experience, and the assignment range is [0, 1].

[0174] (305) Fault detection rate: refers to the number of faults that the equipment health management system can correctly detect. d Total number of failures V t The quantitative calculation formula is as follows:

[0175]

[0176] (306) Fault isolation rate: refers to the number of faults correctly isolated to replaceable units by the equipment health management system V l The number of correctly detected faults V d The quantitative calculation formula is as follows:

[0177]

[0178] (307) Status assessment accuracy refers to the accuracy of the equipment health management system's assessment of the core performance of the equipment. The quantitative calculation formula is as follows:

[0179]

[0180] Where C1 is the accuracy of state assessment, C low is the lower limit of state assessment accuracy, C high The upper limit of the accuracy of the state assessment;

[0181] (308) Performance prediction accuracy refers to the accuracy of the equipment health management system in predicting the degradation trend of the core performance of the equipment. The quantitative calculation formula is as follows:

[0182]

[0183] Where P1 is the performance prediction accuracy, P low is the lower limit of performance prediction accuracy, P high is the upper limit of performance prediction accuracy;

[0184] (309) Maintenance plan coverage; refers to the maintenance plan Q that can be generated by the equipment health management system and the maintenance plan Q that needs to be generated req The quantitative calculation formula is as follows:

[0185]

[0186] (310) Rationality of maintenance plan: refers to whether the maintenance plan generated by the equipment health management system can meet the maintenance needs, and is assigned by experts based on experience. 10 , the value range is [0, 1];

[0187] (4) Quantitatively evaluate the secondary capability indicators of each scheme of the health management system; Based on the quantification criteria of the secondary capability indicators of the health management system effectiveness evaluation system, quantitatively evaluate the secondary capability indicators of each scheme of the health management system, and the quantitative value of the secondary capability indicator is marked as β mp , β mp Represents the quantitative value of the pth secondary capability indicator of the mth solution;

[0188] (5) Eliminate health management system solutions that lack secondary capabilities; analyze the quantitative values ​​of the secondary capability indicators of each health management system solution, and eliminate the health management system solution with a quantitative value of 0. The quantitative value of the secondary capability indicator after the solution is eliminated is marked as β np , β np Represents the quantitative value of the pth secondary capability indicator of the nth solution;

[0189] (6) Analyze the principal components of the secondary capability indicators of the health management system effectiveness evaluation system; based on the weights of the primary capability indicators of the effectiveness evaluation system and the quantitative values ​​of the secondary capability indicators of each scheme, analyze and determine the principal components of the secondary capability indicators of the preferred scheme;

[0190] (601) Determine the quantitative evaluation value of the secondary capability indicator of each scheme; Based on the weight of the primary capability indicator and the quantitative value of the secondary capability indicator of each scheme, determine the quantitative evaluation value γ of the secondary capability indicator of each scheme ij , γ ij Represents the quantitative evaluation value of the jth secondary capability indicator of the i-th scheme;

[0191]

[0192] (602) Establishing a secondary capability indicator matrix for the health management system; establishing a secondary capability indicator matrix M for the health management system with n health management system schemes after eliminating the functional deficiency schemes and p secondary capability indicators based on the quantified values ​​of the secondary capability indicators;

[0193]

[0194] (603) The secondary capability index matrix is ​​dimensionless processed; the secondary capability index matrix is ​​dimensionless transformed using the standard score method, and the matrix M is obtained. * :

[0195]

[0196] Where,

[0197] (604) Determine the correlation coefficient matrix of the dimensionless matrix of the secondary capability index; calculate M * The correlation coefficient matrix R of the matrix:

[0198]

[0199] (605) Determine the eigenvalues ​​and eigenvectors of the correlation coefficient matrix; perform eigenvalue decomposition on the correlation coefficient matrix R to obtain the eigenvalues ​​of the matrix R λ1≥λ2≥…≥λ p ≥0 and the corresponding orthogonal unit eigenvectors t1, t2, ...t p ;

[0200] (606) Determine the contribution rate of the principal component of the secondary capability index; the jth principal component y in the secondary capability index j for:

[0201] y j =(x * ) T ×t j (j=1,2,…,p)

[0202] Where x * =(x1 * , x2 * …,x p * ) T is the standardized sample value;

[0203] Principal component y j Contribution rate C j for:

[0204]

[0205] The cumulative contribution rate of the principal component Q j for:

[0206]

[0207] (607) Determine the principal components of the secondary capability index; select the orthogonal unit eigenvectors corresponding to q eigenvalues ​​with cumulative contribution rates greater than 85% as the principal components, and the principal component eigenvalues ​​are λ1, λ2, ..., λ q , the orthogonal unit eigenvectors are t1, t2, ...t q ;

[0208] (7) Comprehensively evaluate each scheme of the health management system; determine the comprehensive score of each scheme of the health management system based on the principal components of the secondary capability indicators;

[0209] (701) Determine the principal component score of each secondary capability indicator; the principal component score of each secondary capability indicator F i for:

[0210] F i =w i1 M1+w i2 M2+…+w in M n

[0211] Where, is the weight of each variable in the principal component, θ j is the coefficient corresponding to each variable of the principal component;

[0212] (702) Determine the comprehensive score of each scheme of the health management system; the comprehensive score F of each scheme of the health management system is:

[0213] F=μ1F1+μ2F2+…+μ n F n

[0214] Where μ i is the variance percentage of the i-th principal component;

[0215] (8) Optimize the health management system solution; rank the comprehensive scores of the health management system solutions, and the one with the highest score will be the preferred solution.

[0216] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for optimizing equipment health management system solutions based on performance evaluation, characterized in that: The method comprises the following steps: Step S1: Constructing an equipment health management system effectiveness evaluation system; Step S2: Setting the weight of the first-level capability indicator of the equipment health management system performance evaluation system; Step S3: Establishing quantitative criteria for the secondary capability indicators of the effectiveness evaluation system; Step S4: Quantitatively evaluate the secondary capability indicators of each scheme of the equipment health management system; Step S5: Eliminate equipment health management system solutions with secondary capability deficiencies; Step S6: Analyze the principal components of the secondary capability indicators of the equipment health management system effectiveness evaluation system; Step S7: Comprehensively evaluate each solution of the equipment health management system; Step S8: Optimize the equipment health management system solution.

2. The method for optimizing equipment health management system solutions based on performance evaluation according to claim 1, characterized in that: In the step S1, an equipment health management system performance evaluation system is constructed; Based on the principle of constructing a hierarchical indicator system, and in accordance with the evaluation requirements of equipment core functions and the requirements for simple optimization of equipment health management system solutions, an equipment health management system effectiveness evaluation system is constructed, including: Three first-level capability indicators: information perception and interaction capability A, information processing and evaluation capability B, and maintenance and support capability C; As well as ten secondary capability indicators including information perception coverage, information perception effectiveness, information display integrity, information interaction convenience, fault detection rate, fault isolation rate, status assessment accuracy, performance prediction accuracy, maintenance plan coverage, and maintenance plan rationality.

3. The method for optimizing equipment health management system solutions based on performance evaluation according to claim 2, characterized in that: In the step S2, the weight of the first-level capability index of the equipment health management system performance evaluation system is set; According to the core functional requirements of the equipment, the first-level capability indicators of the effectiveness evaluation system are set, and the weights of the information perception and interaction capability A, information processing and evaluation capability B, and maintenance and support capability C are α1, α2, and α3 respectively.

4. The method for optimizing equipment health management system solutions based on performance evaluation according to claim 3, characterized in that: In step S3, a quantitative criterion for the secondary capability index of the performance evaluation system is established; Quantify the ten secondary capability indicators in the equipment health management system effectiveness evaluation system; 1) Information perception coverage β1; refers to the information T that the equipment health management system can perceive and the information T that the equipment needs to perceive req The quantitative calculation formula is as follows: 2) Information perception effectiveness β2 refers to the authenticity and effectiveness of the information obtained by the equipment health management system. The quantitative calculation formula is as follows: Where L1 is the information frame loss rate, L low L is the minimum frame loss rate that fully meets the information requirements. high The maximum frame loss rate that the information can meet the requirements; 3) Information display integrity β3; refers to the information that the equipment health management system can display I and the information that needs to be displayed I req The quantitative calculation formula is as follows: 4) Information interaction convenience β4: refers to the convenience of entering and querying equipment information when using the equipment health management system, expressed as a percentage, with a value range of [0, 1]; 5) Fault detection rate β5; refers to the number of faults that the equipment health management system can correctly detect V d Total number of failures V t The quantitative calculation formula is as follows: 6) Fault isolation rate β6; refers to the number of faults correctly isolated to replaceable units by the equipment health management system V l The number of correctly detected faults V d The quantitative calculation formula is as follows: 7) Status assessment accuracy β7 refers to the accuracy of the equipment health management system's assessment of the equipment's core performance. The quantitative calculation formula is as follows: Where C1 is the accuracy of state assessment, C low is the lower limit of state assessment accuracy, C high The upper limit of the accuracy of the state assessment; 8) Performance prediction accuracy β8 refers to the accuracy of the equipment health management system in predicting the degradation trend of the equipment's core performance. The quantitative calculation formula is as follows: Where P1 is the performance prediction accuracy, P low is the lower limit of performance prediction accuracy, P high is the upper limit of performance prediction accuracy; 9) Maintenance plan coverage β9; refers to the difference between the maintenance plan Q that can be generated by the equipment health management system and the maintenance plan Q that needs to be generated req The quantitative calculation formula is as follows: 10) Reasonableness of maintenance plan β 10 ; Refers to whether the maintenance plan generated by the equipment health management system can meet the maintenance needs, displayed as a percentage, and the value range is [0, 1].

5. The method for optimizing equipment health management system solutions based on performance evaluation according to claim 4, characterized in that: In step S4, a quantitative evaluation of the secondary capability indicators of each scheme of the equipment health management system is performed; According to the secondary capability index quantification criteria of the equipment health management system effectiveness evaluation system, the secondary capability index quantitative evaluation of each scheme of the health management system is carried out, and the secondary capability index quantitative value is marked as β mp , β mp Represents the quantitative value of the pth secondary capability indicator of the mth solution.

6. The method for optimizing equipment health management system solutions based on performance evaluation according to claim 5, characterized in that: In step S5, the equipment health management system solutions with secondary capability deficiency are excluded; The quantitative values ​​of the secondary capability indicators of each device health management system solution are analyzed, and the health management system solution with a quantitative value of 0 is eliminated. The quantitative value of the secondary capability indicator after the solution is eliminated is marked as β np , β np Represents the quantitative value of the pth secondary capability indicator of the nth solution.

7. The method for optimizing equipment health management system solutions based on performance evaluation according to claim 6, characterized in that: In the step S6, the principal components of the secondary capability indicators of the equipment health management system effectiveness evaluation system are analyzed; According to the weights of the first-level capability indicators of the performance evaluation system and the quantitative values ​​of the second-level capability indicators of each scheme, the principal components of the second-level capability indicators of the preferred scheme are analyzed and determined.

8. The method for optimizing equipment health management system solutions based on performance evaluation according to claim 7, characterized in that: The step S6 comprises: Step S61: Determine the quantitative evaluation value of the secondary capability indicator of each scheme; determine the quantitative evaluation value γ of the secondary capability indicator of each scheme based on the weight of the primary capability indicator and the quantitative value of the secondary capability indicator of each scheme ij , γ ij Represents the quantitative evaluation value of the jth secondary capability indicator of the i-th scheme; Step S62: Establishing a secondary capability indicator matrix for the equipment health management system; establishing a secondary capability indicator matrix M of the equipment health management system for n equipment health management system solutions after eliminating the functional deficiency solutions and p secondary capability indicators based on the quantified values ​​of the secondary capability indicators; Step S63: Perform dimensionless processing on the secondary capability indicator matrix; use the standard score method to perform dimensionless transformation on the secondary capability indicator matrix, and obtain the matrix M * : Where, Step S64: Determine the correlation coefficient matrix of the dimensionless matrix of the secondary capability index; calculate M * The correlation coefficient matrix R of the matrix: Step S65: Determine the eigenvalues ​​and eigenvectors of the correlation coefficient matrix; perform eigenvalue decomposition on the correlation coefficient matrix R to obtain the eigenvalues ​​of the matrix R λ1≥λ2≥…≥λ p ≥0 and the corresponding orthogonal unit eigenvectors t1, t2, ...t p ; Step S66: Determine the principal component contribution rate of the secondary capability index (S66); the jth principal component y in the secondary capability index j for: y j (x * ) T ×t j (j=1,2,…,p) Where x * =(x1 * , x2 * …,x p * ) T is the standardized sample value; Principal component y j Contribution rate C j for: The cumulative contribution rate of the principal component Q j for: Step S67: Determine the principal component of the secondary capability index (S67); select the orthogonal unit eigenvectors corresponding to q eigenvalues ​​with cumulative contribution rates greater than 85% as the principal components, and the principal component eigenvalues ​​are λ1, λ2, ..., λ q , the orthogonal unit eigenvectors are t1, t2, ...t q .

9. The method for optimizing equipment health management system solutions based on performance evaluation according to claim 8, characterized in that: In step S7, a comprehensive evaluation is performed on each scheme of the equipment health management system; Determine the comprehensive score of each equipment health management system scheme based on the main components of the secondary capability indicators; The step S7 comprises: Step S71: Determine the principal component score of each secondary capability indicator: i for: F i =w i1 M1+w i2 M2+…+w in M n Where, is the weight of each variable in the principal component, θ j is the coefficient corresponding to each variable of the principal component; Step S72: Determine the comprehensive score of each solution of the equipment health management system; the comprehensive score F of each solution of the health management system is: F=μ1F1+μ2F2+…+μ n F n Where μ i is the percentage of variance of the i-th principal component.

10. The method for optimizing equipment health management system solutions based on performance evaluation according to claim 9, characterized in that: In step S8, the health management system solution is selected first; the comprehensive scores of the equipment health management system solutions are ranked, and the solution with the highest score is selected as the preferred solution.

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