Intelligent evaluation method for health state of main driving system of shield tunneling machine

Abstract

The invention provides an intelligent evaluation method for the health state of a main driving system of a shield tunneling machine. Initial values of all the driving systems are obtained, and the multiple initial values are converted into parameter data used for evaluating all the driving systems. And according to the initial numerical value and the parameter data, obtaining a weight value of each parameter data of each driving system. And according to the plurality of weight values and the initial numerical value, adopting an analytic hierarchy process and an entropy weight method to obtain the weight value of each parameter data of the main driving system. And obtaining a membership function value of each driving system according to the parameter data. And according to the membership function value and the main parameter weight value, performing health evaluation on the health state of the main driving system by using a fuzzy comprehensive evaluation algorithm. The fuzzy comprehensive evaluation means that the health state of the driving system is comprehensively evaluated on the basis of a fuzzy set theory and in combination with a strict theoretical system of the driving system, so that the operation state of the shield tunneling machine is conveniently mastered in real time, and the shield tunneling machine is kept in a safe operation working state.

Description

Technical Field

[0001] The invention relates to the technical field of shield machine health assessment, and in particular to an intelligent assessment method for the health status of a main drive system of a shield machine. Background Art

[0002] Although with the rapid development of my country's equipment manufacturing industry, the probability of hard failures in the motor body of the main drive system of the shield machine and other power transmission devices such as reducers and gears in the drive system during excavation is relatively low, due to the complexity of tunnel design and operating conditions, the cutterhead still often gets stuck or trapped due to insufficient drive torque, resulting in reduced construction efficiency. In addition, if the main drive system operates in an unreasonable load range for a long time, it is likely to cause the reducer and the motor itself to gradually degrade in performance.

[0003] Once the main drive system of the shield machine fails, it will directly affect the safe and reliable operation of the entire shield machine, which may reduce work efficiency or cause serious loss of life and property. Therefore, in order to ensure the safe and reliable operation of the shield machine, scientific and effective fault diagnosis must be performed to determine the location, severity and development trend of the fault.

[0004] Therefore, it is necessary to conduct a comprehensive assessment of the operating health status of the shield machine's drive system on a regular basis. As the main means of prevention, the comprehensive health status assessment technology can ensure the safe operation of the drive system and improve the comprehensive safety performance of the shield machine. Summary of the invention

[0005] In view of the above problems, the present invention is proposed to provide an intelligent health status assessment method for the main drive system of a shield machine that overcomes the above problems or at least partially solves the above problems, which can solve the problem that the main drive system of the shield machine is prone to failure and achieve the effect of keeping the shield machine in a safe operating state.

[0006] Specifically, the present invention provides a method for intelligently evaluating the health status of a main drive system of a shield machine, and the method for intelligently evaluating the health status of a main drive system of a shield machine comprises:

[0007] Acquire initial values ​​of each drive system, and convert a plurality of the initial values ​​into parameter data for evaluating each drive system;

[0008] According to the initial value and the parameter data, obtaining a weight value of each parameter data of each drive system;

[0009] According to the plurality of weight values ​​and the initial value, the weight value of each parameter data of the main drive system is obtained by using the hierarchical analysis method and the entropy weight method, and recorded as the main parameter weight value;

[0010] Acquire the membership function value of each of the drive systems according to the parameter data;

[0011] According to the membership function value and the main parameter weight value, a fuzzy comprehensive evaluation algorithm is used to perform a health assessment on the health status of the main drive system.

[0012] Optionally, the step of converting the plurality of initial values ​​into parameter data for evaluating each of the drive systems includes:

[0013] The initial values ​​are preprocessed by using a normalization method so as to convert the initial values ​​into dimensionless data of [0, 1]; the dimensionless data after conversion is the parameter data.

[0014] Optionally, in the step of obtaining the weight value of each parameter data of each drive system from the initial value and the parameter data, the following steps are included:

[0015] The first weight value of the drive system is obtained by using the hierarchical analysis method, which is recorded as The entropy weight method is used to obtain the second weight value of the drive system, which is recorded as

[0016] The main parameter weight value is denoted as ω j , (j=1, 2, ..., m);

[0017]

[0018] Among them, θ is the proportion of the combined weights obtained by the hierarchical analysis method; (1-θ) is the proportion of the combined weights obtained by the entropy weight method.

[0019] Optionally, the step of obtaining the membership function value of each drive system according to the initial value includes:

[0020] A membership function is established, and the parameter data is brought into the membership function to obtain the membership function value of each of the drive systems.

[0021] Optionally, the step of using the fuzzy comprehensive evaluation algorithm to perform health assessment on the health status of the main drive system includes:

[0022] In the fuzzy critical evaluation algorithm, an evaluation index factor set U = (u1, u2, ---, u n ), and the judgment set V = (v1, v2, ..., v m );

[0023] Mapping:

[0024] T R:F(U)→F(V)

[0025] A→T R (A) = B∈F(V)

[0026] B is called A in fuzzy transformation T R The image below, A is the original image of B;

[0027] Assume A, B∈F(U), if fuzzy transformation;

[0028] T R :F(U)→F(V)

[0029] satisfy:

[0030] (1)T R (A∪B)=T R (A)∪T R (B)

[0031] (2)T R (λA)=λT R (A), λ∈[0,1]

[0032] T R It is a fuzzy linear transformation from U to V;

[0033] Assume R∈F(U×V) is a given fuzzy relation, then R uniquely determines the fuzzy linear transformation from U to V. R :F(U)→F(V) makes Both have:

[0034]

[0035] In the indicator factor set U = (u1, u2, ..., u n ) and the judgment set V = (v1, v2, ..., v m ) are all finite theoretical domain values, so that A is a fuzzy vector on U, denoted by A = (a1, a2, ..., a n ), R=(r ij ) m×m is a fuzzy relation matrix on U×V (where a≥0, r ij ≤1), we get an m-dimensional fuzzy vector B, namely:

[0036] is a fuzzy operator;

[0037] The factor set B is used to determine the health assessment of the main driven system.

[0038] Optionally, the step of using the factor set B to determine the health assessment of the main drive system includes:

[0039] The fuzzy operators include:

[0040] Operator 1: Main factor determination type, that is, M (∨, ∧) type.

[0041] This operator highlights the main factors in the evaluation and ignores the influence of other indicators. The calculation process is:

[0042]

[0043] Among them, "∨" represents taking the larger value, and "^" represents taking the smaller value;

[0044] Operator 2: main factor prominent type, i.e. M(·,∨) type;

[0045]

[0046] Where, “·” represents multiplication, j = 1, 2, …, 5;

[0047] Operator 3: weighted average type, i.e., M(·,+) type;

[0048] Each evaluation indicator has a certain contribution to the evaluation target according to its weight, and the calculation process is:

[0049]

[0050] Among them, "+" represents addition, j = 1, 2, ---, 5;

[0051] Operator 4: Main factor determination type, that is type;

[0052]

[0053] Optionally, the intelligent health status assessment method of the shield machine main drive system also includes:

[0054] The health status level of each of the drive systems is determined according to the health assessment results of the drive systems.

[0055] In the intelligent health status assessment method of the main drive system of the shield machine of the present invention, the weight of the drive system obtained by the hierarchical analysis method is biased towards subjectivity, while the weight of the drive system obtained by the entropy weight method is biased towards objectivity; weights with subjective and objective significance are obtained by effectively combining and weighting the two methods. The application of this method can not only enable the advantages of the two weighting methods to be normally exerted to a certain extent, but also greatly eliminate the adverse factors of the two weight determination methods, making the required weights more scientific and reasonable.

[0056] Furthermore, fuzzy comprehensive evaluation refers to the interpretation of the evaluation results based on certain principles by making fuzzy inferences based on a predetermined set of rules on the basis of single-indicator evaluation of multiple fuzzy indicators. Fuzzy comprehensive evaluation refers to the comprehensive evaluation of the health status of the drive system based on fuzzy set theory and its own rigorous theoretical system. When the health evaluation of the drive system of the shield machine is carried out in the subsequent stage, the evaluation structure data obtained is more accurate, so as to facilitate the real-time grasp of the operating status of the shield machine, so as to keep the shield machine in a safe working state.

[0057] Based on the following detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings, those skilled in the art will become more aware of the above and other objects, advantages and features of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Hereinafter, some specific embodiments of the present invention will be described in detail in an exemplary and non-limiting manner with reference to the accompanying drawings. The same reference numerals in the accompanying drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the accompanying drawings:

[0059] Figure 1 is a schematic flow chart of a method for intelligently evaluating the health status of a main drive system of a shield machine according to an embodiment of the present invention;

[0060] Figure 2 It is a data table chart after the normalization of the health status evaluation indicators of the drive system;

[0061] Figure 3 It is a judgment matrix form diagram;

[0062] Figure 4 It is a table diagram of the health status evaluation results of each main drive system;

[0063] Figure 5 It is a table of drive system health status assessment results. DETAILED DESCRIPTION

[0064] Refer to the following Figures 1 to 5To describe the intelligent assessment method for the health status of the main drive system of a shield machine according to an embodiment of the present invention. In the description of this embodiment, it should be understood that the terms "first" and "second" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features, that is, include one or more of the features. In the description of the present invention, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. When a feature "includes or contains" one or some of the features it covers, unless otherwise specifically described, this indicates that other features are not excluded and may further include other features.

[0065] Unless otherwise clearly defined and limited, the terms "set", "install", "connect", "connect", "fix", "couple" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. A person skilled in the art should be able to understand the specific meanings of the above terms in the present invention according to the specific circumstances.

[0066] In addition, in the description of this embodiment, the first feature being "above" or "below" the second feature may include the first and second features being in direct contact, or may include the first and second features not being in direct contact but being in contact through another feature between them. That is, in the description of this embodiment, the first feature being "above", "above", and "above" the second feature includes the first feature being directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. The first feature being "below", "below", or "below" the second feature may mean that the first feature is directly below or obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0067] In the description of the present embodiment, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0068] Figure 1 This is a schematic diagram of the intelligent health status assessment method for the main drive system of a shield machine. Figure 1 As shown, and refer to Figures 2 to 5 The embodiment of the present invention provides a method for intelligently evaluating the health status of a main drive system of a shield machine. The method for intelligently evaluating the health status of a main drive system of a shield machine includes:

[0069] S100, obtaining initial values ​​of each drive system, and converting the multiple initial values ​​into parameter data for evaluating each drive system;

[0070] S200, obtaining weight values ​​of various parameter data of various drive systems according to the initial values ​​and parameter data;

[0071] S300, using the hierarchical analysis method and the entropy weight method according to the multiple weight values ​​and the initial value, obtaining the weight value of each parameter data of the main drive system, and recording it as the main parameter weight value;

[0072] S400, obtaining the membership function value of each drive system according to the parameter data;

[0073] S500 , based on the membership function value and the main parameter weight value, a fuzzy comprehensive evaluation algorithm is used to perform a health assessment on the health status of the main drive system.

[0074] Specifically, the initial value is the value displayed by various data of the shield machine in normal working state. Further, the initial value can be used for various working values ​​of the drive system when the shield machine is in healthy working state. Therefore, the initial value is converted into parameter data, and the healthy state of the drive system can be directly compared through the parameter data.

[0075] Specifically, the parameter data weights of each drive system can distinguish the primary and secondary drive systems. The parameter weight values ​​are positively correlated with the importance of the relevant parameters of the drive system. In other words, the higher the parameter weight values, the more important the parameters of the drive system are in the working process of the shield machine, and the parameter data of the drive system needs to be focused on. Furthermore, based on the parameter weight values, the failure mechanism of the drive system of the tunnel shield machine is analyzed and investigated in detail, and the hierarchical structure of the comprehensive evaluation indicators of the drive system is established.

[0076] Furthermore, the weight of the driving system obtained by the analytic hierarchy process is more subjective, while the weight of the driving system obtained by the entropy weight method is more objective; by effectively combining the two methods to assign weights, weights with subjective and objective significance are obtained. To a certain extent, the application of this method can not only enable the advantages of the two weighting methods to be normally exerted, but also greatly eliminate the adverse factors of the two weight determination methods, making the required weights more scientific and reasonable.

[0077] Furthermore, fuzzy comprehensive evaluation refers to the interpretation of the evaluation results based on certain principles by making fuzzy inferences based on a predetermined set of rules on the basis of single-indicator evaluation of multiple fuzzy indicators. Fuzzy comprehensive evaluation refers to the comprehensive evaluation of the health status of the drive system based on fuzzy set theory and its own rigorous theoretical system. When the health evaluation of the drive system of the shield machine is carried out in the subsequent health evaluation, the evaluation structure data obtained is more accurate, which is convenient for real-time grasp of the operating status of the shield machine, thereby improving the working status of the shield machine.

[0078] In summary, according to the above principles, the comprehensive evaluation index system of the health status of the shield machine system is established to ensure that the constructed evaluation index system can reasonably and accurately reflect the health status of the shield machine drive system, and the constructed index system is used to comprehensively evaluate the drive system status to obtain the comprehensive evaluation results of the health status of the shield machine main drive system.

[0079] In some embodiments of the present invention, Figure 1 As shown, in the step of converting a plurality of initial values ​​into parameter data for evaluating each drive system, the steps include:

[0080] S110, preprocessing the initial values ​​using a normalization method, so as to convert the initial values ​​into dimensionless data of [0, 1]; the converted dimensionless data is parameter data.

[0081] Specifically, the normalization method converts the initial value into a decimal between [0, 1], that is, converts the dimensioned expression into a dimensionless expression. This makes data processing easier, and also makes it easier to calculate the weight values ​​of the drive system parameters in subsequent steps, thereby quickly evaluating the health status of the drive system.

[0082] In some embodiments of the present invention, Figure 1 As shown, in the step of obtaining the weight value of each parameter data of each drive system from the initial numerical value and parameter data, it includes:

[0083] S310, using the hierarchical analysis method to obtain the first weight value of the parameter data of the drive system, denoted as The second weight value of the parameter data of the drive system is obtained by using the entropy weight method, which is denoted as

[0084] The main parameter weight value is denoted as ω j , (j=1,,2,…,m);

[0085]

[0086] Among them, θ is the proportion of the combined weights obtained by the hierarchical analysis method; (1-θ) is the proportion of the combined weights obtained by the entropy weight method.

[0087] In some embodiments of the present invention, Figure 1 As shown, in the step of obtaining the membership function value of each drive system according to the initial value, it includes:

[0088] S410, establishing a membership function, and bringing parameter data into the membership function to obtain membership function values ​​of each drive system.

[0089] In some embodiments of the present invention, Figure 1 As shown, the steps of using the fuzzy comprehensive evaluation algorithm to conduct health assessment on the health status of the main drive system include:

[0090] In the fuzzy critical evaluation algorithm, the evaluation index factor set U = (u1, u2, ..., u n ), and the judgment set V = (v1, v2, ..., v m );

[0091] Mapping:

[0092] T R :F(U)→F(V)

[0093] A→T R (A) = B∈F(V)

[0094] B is called A in fuzzy transformation T R The image below, A is the original image of B;

[0095] Assume A, B∈F(U), if fuzzy transformation;

[0096] T R :F(U)→F(V)

[0097] satisfy:

[0098] (1)T R (A∪B)=T R (A)∪T R (B)

[0099] (2)T R (λA)=λT R (A), λ∈[0,1]

[0100] T R It is a fuzzy linear transformation from U to V;

[0101] Assume R∈F(U×V) is a given fuzzy relation, then R uniquely determines the fuzzy linear transformation from U to V. R:F(U)→F(V) makes Both have:

[0102]

[0103] In the indicator factor set U = (u1, u2, ..., u n ) and the judgment set V = (v1, v2, ..., v m ) are all finite theoretical domain values, so that A is a fuzzy vector on U, denoted by A = (a1, a2, ---, a n ), R=(r ij ) n×m is a fuzzy relation matrix on U×V (where a>0, r y <1), we get an m-dimensional fuzzy vector B, namely:

[0104] is a fuzzy operator;

[0105] Factor set B is used to determine the health assessment of the driven system.

[0106] In some embodiments of the present invention, Figure 1 As shown, in the health assessment step of factor set B for determining the main driven system, it includes:

[0107] Fuzzy operators include:

[0108] Operator 1: Main factor determination type, that is, M (∨, ∧) type.

[0109] This operator highlights the main factors in the evaluation and ignores the influence of other indicators. The calculation process is:

[0110]

[0111] Among them, "∨" represents taking the larger value, and "^" represents taking the smaller value;

[0112] Operator 2: main factor prominent type, i.e. M(·,∨) type;

[0113]

[0114] Where, “·” represents multiplication, j=1, 2, ---, 5;

[0115] Operator 3: weighted average type, i.e., M((·,+) type;

[0116] Each evaluation indicator has a certain contribution to the evaluation target according to its weight, and the calculation process is:

[0117]

[0118] Among them, "+" represents addition, j = 1, 2, ---, 5;

[0119] Operator 4: Main factor determination type, that is type.

[0120]

[0121] In some embodiments of the present invention, Figure 1 As shown, the intelligent assessment method for the health status of the main drive system of the shield machine also includes:

[0122] S600. Determine the health status level of each drive system according to the health assessment result of the drive system. Specifically, the health status of the drive system is divided into five levels: "healthy", "sub-healthy", "usable", "faulty", and "scrapped". The division of the five health status levels can ensure that the health status of the drive system is obtained quickly and accurately, and can also reduce the cumbersome characteristics of the original division.

[0123] In some embodiments of the present invention, the step of determining the health status level of each drive system according to the health assessment result of the drive system includes:

[0124] S610, based on the health assessment results, create a comprehensive evaluation matrix of the drive system, and then determine the main system weight value of each main system by using the hierarchical analysis method and the entropy weight method, which is recorded as ω;

[0125] S620. According to the combination of the fuzzy judgment matrix and the main system weight value, the fuzzy comprehensive evaluation method is used to evaluate the health status of the drive system, and the comprehensive evaluation results of the health status of the drive system are obtained for comparison. The health status level corresponding to the largest one is the drive system status level.

[0126] In some embodiments of the present invention, Figure 1 and Figure 2 As shown in the figure, the main drive system includes a torque converter, a planetary transmission mechanism, a pump group, a hydraulic clutch, a hydraulic control system, a steering pump motor, a front transmission, an oil supply system and an auxiliary transmission device. The characteristic parameter vector Y = {Y1, Y2, Y3, Y4, Y5, Y6, Y7, T8, Y9} of the corresponding evaluation index is established, where Y contains nine key components.

[0127] Let Y1 = {pump wheel lubrication pressure D1, guide wheel torsion peak value D2, turbine speed threshold D3, housing speed threshold D4, input gear rotation frequency vibration amplitude D5} as the evaluation index of the transmission device component hydraulic torque converter;

[0128] Y2={speed gear transmission oil temperature D6, friction plate transmission oil temperature D7, gear ring vibration peak value D8, spindle torque threshold D9, piston cylinder vibration peak value D 10 , Sealing ring oil pressure threshold D 11}As an evaluation index for the planetary speed change mechanism of the transmission component;

[0129] Y3={speed gear transmission oil temperature D 12 , gear block vibration signal kurtosis value D 13 , filter flow threshold D 14}As an evaluation indicator for the pump group of the transmission component;

[0130] Y4={Friction plate fluid viscosity pressure D 15 , piston static pressure D 16 , oil sleeve fluid viscosity pressure D 17 , the frequency amplitude of the outer hub vibration signal D 18}As an evaluation index for the hydraulic clutch of transmission components;

[0131] Y5={Main operating pressure of main constant pressure valve D 19 , reversing valve component operating pressure D 20 , buffer valve component operating pressure D 21 , reversing diaphragm pressure D 22}As an evaluation indicator of the hydraulic control system of transmission components;

[0132] Y6={High pressure valve group turns to high pressure D 23 , servo system servo pressure D 24 , rotor component oil filling pressure D 25}As an evaluation indicator for the steering pump motor of the transmission component;

[0133] Y7={Front transmission gear shaft torque D 26 , front transmission bearing torque D 27}As an evaluation index for the front transmission of the transmission components;

[0134] Y8={pump group control valve group flow rate D 28 , oil return unloading valve flow D 29 , brake pressure pipe pressure D 30 , oil filling pressure pipe pressure D 31 , P4P6 pump flow rate D 32}As an evaluation indicator of the oil supply system of transmission components;

[0135] Y9={Vibration peak value of auxiliary transmission gear D 33 , auxiliary transmission bearing vibration kurtosis D 34}As an evaluation indicator of the auxiliary transmission mechanism of the transmission device components.

[0136] Since the scale types and dimensions of the indicators that can reflect the health status of key components of the transmission device are different, the original data needs to be normalized to facilitate the comparison of the indicators. Assume that the data results after normalization are as follows Figure 2 As shown in the table.

[0137] Figure 2 Normalized data of drive system health status assessment indicators

[0138]

[0139] In this embodiment, if Figure 3 As shown in the figure, the hierarchical analysis method is used to determine the weights of each item. According to the main implementation steps of the hierarchical analysis method. Specifically, taking the row pump group as an example, the importance scale of each parameter when compared with each other can be quantitatively given through expert experience, which can be written as follows: Figure 3 The form of the table judgment matrix is:

[0140]

[0141] First, the consistency check of the judgment matrix is ​​performed, and then the maximum eigenvalue of the judgment matrix and its corresponding eigenvector are determined. The obtained eigenvector is recorded as the weight vector, so that the weights of the parameter characteristics of the nine drive systems (i.e., the first weight value) can be obtained:

[0142]

[0143] Furthermore, in order to calculate the characteristic weights of each parameter of the main drive system, the above formula can be used to obtain the characteristic parameter index weights of each drive system (i.e., the second weight):

[0144] ω′1[0.0465, 0.5537, 0.3063, 0.0388, 0.0547];

[0145] ω′2=[0.0722,0.0013,0.3254,0,3187,0.1468,0.1356];

[0146] ω′3=[0.1011,0.7989,0.1000];

[0147] ω′4=[0.6213,0.0018,0.0016,0.3754];

[0148] ω′5=[0.1812,0.3881,0.1937,0.2370];

[0149] ω′6=[0.1121,0.0469,0.8410];

[0150] ω′7=[0.5061,0.4939];

[0151] ω′8=[0.6233, 0.1607, 0.0652, 0.1492, 0.0016];

[0152] ω′9=[0.5185,0.4815].

[0153] Further, in step S310, the above two weights are combined. When θ is 0.3, the subjective and objective weights can be well combined, and the influence of unfavorable factors in the weights determined by the subjective and objective weighting method can be greatly weakened. Thus, the weights of the characteristic parameters of the transmission box, torque converter, steering pump motor, and planetary transmission mechanism after combined weighting (i.e., the main weight values) are:

[0154] ω1=[0.0453,0.4058,0.2455,0.0811,0.2223];

[0155] ω2=[0.0597,0.0170,0.2495,0.2607,0.1732,0.2398];

[0156] ω3=[0.0923,0.6429,0.2647];

[0157] ω4=[0.4483, 0.1759, 0.0415, 0.3342];

[0158] ω5=[0.1425,0.2991,0.2202,0.3381];

[0159] ω6=[0.1028, 0.0894, 0.8079];

[0160] ω7=[0.4293,0.5707];

[0161] ω8=[0.4504, 0.1350, 0.0759, 0.1770, 0.1617];

[0162] ω9=[0.4129,0.5871].

[0163] It should be noted that before evaluating the health status of the drive system, the main drive system must be evaluated first, and then, based on the health status of the main drive system, a comprehensive evaluation of the health status of the entire drive system is conducted.

[0164] Will Figure 4 Substituting the data in the table into the membership function formula, the values ​​of each membership function can be obtained.

[0165] Substituting the obtained membership function value and the weight value of each characteristic parameter of each key component of the transmission device into the above formula, the comprehensive evaluation results of each key component can be obtained, such as Figure 4 The table shows:

[0166] Figure 4 Evaluation results of health status of each main drive system

[0167]

[0168] Will Figure 4 The data in the table constructs a fuzzy judgment matrix for the health assessment of the drive system, which is combined into a matrix form, and the weights of each key component are obtained using the hierarchical analysis method:

[0169]

[0170] At the same time, the entropy weight method is used to obtain the weights of each key component:

[0171] ω′=[0.1474,0.0848,0.0921,0.0847,0.0850,0.1474,0.1474,0.0638,0.1474],

[0172] Finally, the weight value after combining the two weights using the combined weighting method is:

[0173] ω=[0.1087,0.0667,0.0750,0.0745,0.0816,0.1354,0.1498,0.1114,0.1968].

[0174] The weighted average model is used to use the fuzzy comprehensive evaluation method to obtain the health status of the transmission device. Figure 5 As shown in the table.

[0175] Figure 5 Drive system health status assessment results

[0176]

[0177] In summary, using the health assessment model constructed above, the comprehensive assessment results of the health status of the drive system can be obtained, and the health level status of each main drive system can be obtained through the assessment results. Then, the health level of the entire shield machine drive system can be evaluated through the health level status of the main drive system components.

[0178] Through the above analysis, the created health assessment model can realize a comprehensive assessment of the health status of the drive system. The obtained results have good accuracy and objectivity and can realize timely status monitoring.

[0179] At this point, those skilled in the art should recognize that, although multiple exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications that conform to the principles of the present invention can still be directly determined or derived based on the content disclosed in the present invention without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention should be understood and recognized as covering all these other variations or modifications.

Claims

1. An intelligent health status assessment method for a main drive system of a shield machine, characterized in that: include: Acquire initial values ​​of each drive system, and convert a plurality of the initial values ​​into parameter data for evaluating each drive system; According to the initial value and the parameter data, obtaining a weight value of each parameter data of each drive system; According to the plurality of weight values ​​and the initial value, the weight value of each parameter data of the main drive system is obtained by using the hierarchical analysis method and the entropy weight method, and recorded as the main parameter weight value; Acquire the membership function value of each of the drive systems according to the parameter data; According to the membership function value and the main parameter weight value, a fuzzy comprehensive evaluation algorithm is used to perform a health assessment on the health status of the main drive system.

2. The intelligent health status assessment method of the main drive system of a shield machine according to claim 1 is characterized in that: The step of converting the plurality of initial values ​​into parameter data for evaluating each of the drive systems includes: The initial values ​​are preprocessed by using a normalization method so as to convert the initial values ​​into dimensionless data of [0, 1]; the dimensionless data after conversion is the parameter data.

3. The intelligent health status assessment method of the main drive system of a shield machine according to claim 2 is characterized in that: In the step of obtaining the weight value of each parameter data of each drive system from the initial value and the parameter data, the method includes: The first weight value of the drive system is obtained by using the hierarchical analysis method, which is recorded as The entropy weight method is used to obtain the second weight value of the drive system, which is recorded as The main parameter weight value is denoted as ω j , (j=1, 2, ..., m); Among them, θ is the proportion of the combined weights obtained by the hierarchical analysis method; (1-θ) is the proportion of the combined weights obtained by the entropy weight method.

4. The intelligent health status assessment method of the main drive system of a shield machine according to claim 3 is characterized in that: In the step of obtaining the membership function value of each drive system according to the initial value, it includes: A membership function is established, and the parameter data is brought into the membership function to obtain the membership function value of each of the drive systems.

5. The intelligent health status assessment method of the main drive system of a shield machine according to claim 4 is characterized in that: The step of using the fuzzy comprehensive evaluation algorithm to perform health assessment on the health status of the main drive system includes: In the fuzzy critical evaluation algorithm, an evaluation index factor set U = (u1, u2, ..., u n ), and the judgment set V = (v1, v2, ..., v m ); Mapping: T R :F(U)→F(V) A→T R (A)=B∈F(V) B is called A in fuzzy transformation T R The image below, A is the original image of B; Assume A, B∈F(U), if fuzzy transformation; T R :F(U)→F(V) satisfy: (1)T R (A∪B)=T R (A)∪T R (B) (2)T R (λA)=λT R (A),λ∈[0,1] T R It is a fuzzy linear transformation from U to V; Assume R∈F(U×V) is a given fuzzy relation, then R uniquely determines the fuzzy linear transformation from U to V. R :F(U)→F(V) makes Both have: In the indicator factor set U = (u1, u2, ..., u n ) and the judgment set V = (v1, v2, ..., v m ) are all finite theoretical domain values, so that A is a fuzzy vector on U, denoted by A = (a1, a2, ..., a n ), R=(r ij ) n×m is a fuzzy relation matrix on U×V (where a≥0, r ij ≤1), we get an m-dimensional fuzzy vector B, namely: is a fuzzy operator; The factor set B is used to determine the health assessment of the main driven system.

6. The intelligent health status assessment method of the main drive system of a shield machine according to claim 5 is characterized in that: The factor set B is used to determine the health assessment step of the main drive system, including: The fuzzy operators include: Operator 1: Main factor determination type, i.e. M (∨, ∧) type; This operator highlights the main factors in the evaluation and ignores the influence of other indicators. The calculation process is: Among them, "∨" represents taking the larger number, and "∧" represents taking the smaller number; Operator 2: main factor prominent type, i.e. M(·,∨) type; Wherein, "·" represents multiplication, j = 1, 2, ..., 5; Operator 3: weighted average type, i.e., M(·,+) type; Each evaluation indicator has a certain contribution to the evaluation target according to its weight, and the calculation process is: Wherein, "+" represents addition, j = 1, 2, ..., 5; Operator 4: Main factor determination type, that is type; 7. The intelligent health status assessment method of the main drive system of a shield machine according to claim 5 is characterized in that: Also includes: The health status level of each of the drive systems is determined according to the health assessment results of the drive systems.

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