CN115640940A - Shield machine main bearing performance evaluation method based on spider web diagram-grey correlation degree analysis - Google Patents
Shield machine main bearing performance evaluation method based on spider web diagram-grey correlation degree analysis Download PDFInfo
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Abstract
The invention discloses a performance evaluation method of a main bearing of a shield machine based on spider web diagram-grey correlation analysis, which comprises the steps of firstly measuring performance index factors of the main bearing of the shield machine in an actual use state for multiple times, calculating by using a grey correlation method to obtain the strength of a friction coefficient and the correlation between all relevant performance index factors, multiplying a conversion matrix of a performance index test result by the correlation to obtain an integration matrix of correlation evaluation data, and displaying the integration matrix in the form of a spider web diagram; the average area and the average perimeter of the spider web graph are selected as characteristic quantities, the ratio of the area of the spider web graph to the perimeter of the spider web graph is calculated and the coordination degree is reflected on the evaluation data of the main bearing of the shield machine, and then performance evaluation data are obtained. The invention integrates multiple indexes to analyze simultaneously, establishes a reliable method for evaluating the performance of the main bearing of the shield machine, and meets the requirement that the main bearing of the shield machine manufactured in China can smoothly complete a whole tunneling task without serious breakdown faults.
Description
Technical Field
The invention belongs to the field of bearing performance evaluation, and particularly relates to a shield machine main bearing performance evaluation method based on spider web diagram-grey correlation analysis.
Background
The main bearing of the shield machine is the most precise part in the main drive of the shield machine, and plays a role in driving the cutter head to rotate and bearing huge torque of the cutter head. In the construction, if the main bearing lubrication system fails or the bearing is distorted, the main bearing is easily broken down rapidly. Once the main bearing is out of work, the main bearing must be replaced, the replacement difficulty of the main bearing is very high, the project period can be seriously delayed, and the loss is huge. At present, the main bearing of the shield machine is mostly imported from foreign countries and is expensive, and the domestic main bearing has the problems of short service life and low reliability. Therefore, in order to meet the requirement that the main bearing of the domestic shield machine can smoothly complete a whole tunneling task without serious breakdown fault, the delivery performance evaluation is carried out to ensure the bearing quality.
At present, the performance evaluation of the rolling bearing can be realized by analyzing vibration signals, sample oil sample ferrography, temperature conditions and the like, wherein the analysis and the processing of the vibration signals account for about 70% of the sample type analysis, are the most common methods in the performance evaluation of the bearing, and are one of the most adopted methods. However, the main bearing of the shield machine is different from a common bearing, is an ultra-low-speed heavy-load bearing and is large in size. There is not a set of method suitable for evaluating the performance of the main bearing of the shield machine. Therefore, the performance evaluation of the main bearing of the shield machine needs to be carried out by simultaneously analyzing multiple indexes (radial vibration, axial vibration, temperature, friction torque and oil analysis) so as to establish a reliable method for evaluating the performance of the main bearing of the shield machine.
And analyzing the numerical relationship among the factors by using the grey correlation degree, using the selected index factor data influencing the performance of the main bearing of the shield tunneling machine to construct a decision matrix, using the selected performance index set as an attribute set, and using the correlation degree between each index and the main index performance as an evaluation weight. And establishing and calculating a spider web diagram evaluation function model according to the obtained associated data of the evaluation performance test indexes, wherein in the establishing and calculating processes of the model, the area and the perimeter of the spider web diagram are selected as characteristic quantities, an evaluation function is established, and the spider web diagram evaluation function calculation is performed, so that the purpose of evaluating and analyzing the comprehensive performance of the main bearing of the shield machine is achieved.
Disclosure of Invention
The invention aims to provide a shield machine main bearing performance evaluation method based on spider web diagram-gray correlation analysis, aiming at the current situation that the existing shield machine bearing performance evaluation method is deficient.
The purpose of the invention is realized by the following technical scheme: a shield machine main bearing performance evaluation method based on spider web diagram-grey correlation degree analysis comprises the following steps:
step 1, measuring performance index factors of a main bearing of the shield machine in an actual use state for multiple times. Synthesizing each group of measurement data into an original matrix M, and carrying out normalization processing on the original matrix to obtain a conversion matrix X;
step 2, when the grey correlation degree method is used for calculation, the specific calculation process of index assignment of each performance index is as follows:
calculating corresponding absolute difference values by using a difference sequence matrix general formula to obtain a difference matrix, and calculating a maximum difference value and a minimum difference value:
Δi(k)＝|x 0 (k)-x i (k)| (k＝1,2.....,m i＝1,....n)
in the formula: x is the number of 0 (k) And x i (k) For measuring any two different data in the original data, Δ i (k) is the difference between the two different data, hmax is the maximum difference obtained by calculation, and Hmin is the minimum difference obtained by calculation. Calculating a difference matrix according to the general correlation coefficient formula to obtain a correlation coefficient matrix:
in the formula: x is a numerical value corresponding to the transformation matrix; rho is a resolution coefficient, the resolution coefficient reflects the distinguishing capability of each correlation coefficient through the magnitude of the value of the resolution coefficient, the value of the resolution coefficient is within (0, 1), and the distinguishing capability is enhanced along with the reduction of the correlation coefficient; xi is the i row of the comparative series in index factors of the main bearing of the shield machine; xi shape ij The gray correlation coefficient is a numerical value which reflects subjective and objective analysis, and the similarity between the index factor and the performance of the set reference index is larger, so that the objective preference and the subjective preference of the index factor are more similar to the reference index.
Calculating the correlation degree between each evaluation performance object and the reference performance to obtain the friction coefficient intensity and the correlation degree R between each related performance index factor i The formula is as follows:
in the formula: xi shape i (k) Is the kth correlation coefficient of the ith column;
and 3, multiplying the conversion matrix of the performance index test result by the correlation degree to obtain an integration matrix of the correlation degree evaluation data, correspondingly generating a spider web diagram based on each group of data measured in the step 1, and displaying the integration matrix data obtained by calculation in the form of the spider web diagram.
Step 4, selecting the average area and the average perimeter of the spider web graph as characteristic quantities, and establishing a calculation formula for evaluating the average area and the average perimeter of the model as follows:
in the formula:
to evaluate the average area of the spider web plot of the data;
mean perimeter to evaluate spider web images of data; h is the number of index factors, and the numerical value of the current evaluation model is 5; p represents the p index in the index factors; q represents the qth index in the index factors; theta is the included angle between two adjacent axes in the spider web diagram of the evaluation data, and the angle of the current evaluation model is 72 degrees.
Step 5, the evaluation vector of the evaluation object is E i ＝(t i1 ,t i2 ) Wherein t is i1 The relative value of the area is mainly used for reflecting the relative area of the corresponding spider web diagram of the main bearing of the shield machine to be tested; t is t i2 The meaning represented by the method is that the evaluation data among all index factors in a spider web diagram is reflected, and the evaluation data of the main bearing of the shield is subjected to ratio calculation of the area of the spider web diagram and the perimeter of the spider web diagramThe degree of coordination. The formula is as follows:
wherein G is the maximum area of the spider web plot of the evaluation data.
At the currently established evaluation vector E i The method belongs to two-dimensional vectors, and comprises the following steps of calculating the geometric mean value of two evaluation vectors, and then establishing and calculating an evaluation function to obtain performance evaluation data:
in the formula: and f represents an evaluation function value, and the larger the numerical value of the evaluation function value, the more excellent the comprehensive performance of the main bearing of the shield machine under test.
Further, in step 1, the performance index factors include five performance indexes, specifically, radial vibration, axial vibration, temperature, friction torque and oil analysis.
Further, in step 1, the normalization process specifically includes: performing dispersion standardization processing on an original data matrix M, normalizing data corresponding to each factor, and performing linear transformation on the original data to ensure that the sizes of all factors participating in construction in the matrix are in a [0,1] interval, wherein a calculation formula of index data in the original data matrix M is as follows:
in the formula: x is a corresponding data value after the original data is processed; x' is corresponding data in the original data matrix M; min represents the minimum value of sample data and max represents the maximum value of sample data.
The calculated data is represented by X as a transformation matrix. The data in the matrix is in the [0,1] interval.
The invention has the beneficial effects that: the invention provides a performance evaluation method of a main bearing of a shield machine, which aims at the problem that the existing single performance evaluation of a rolling bearing is not suitable for the factory performance evaluation of the main bearing of the shield machine, and is based on the analysis of a spider web diagram-grey correlation degree. The method needs to synthesize multiple indexes for simultaneous analysis (radial vibration, axial vibration, temperature, friction torque and oil analysis) so as to establish a reliable method for evaluating the performance of the main bearing of the shield machine. The requirement that the main bearing of the domestic shield machine can smoothly complete a whole tunneling task without serious breakdown is met.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of a shield machine main bearing performance evaluation method based on spider web diagram-grey correlation analysis.
FIG. 2 is a spider web diagram of a shield machine main bearing performance evaluation calculation case.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
As shown in FIG. 1, the invention provides a shield machine main bearing performance evaluation method based on spider web diagram-gray correlation analysis, which comprises the following specific steps:
step 1, five performance index factors (radial vibration, axial vibration, temperature, friction torque and oil analysis) of a main bearing of the shield machine in an actual use state are measured for multiple times. Synthesizing each group of measurement data into an original matrix M;
and 2, in order to simplify the standardization process of model calculation and avoid errors caused by unit and quantity differences of various factors of a main bearing of the shield machine, normalizing decision matrix data, performing deviation standardization on an original data matrix M, normalizing corresponding data of various factors, and performing linear transformation on the original data to ensure that the sizes of all factors participating in construction in the matrix are in a [0,1] interval, wherein a forward index is the index which represents the performance of the matrix when the numerical value is larger, and a reverse forward index is the index which represents the performance of the matrix when the numerical value is smaller. All the selected indexes are reverse and forward indexes. The formula for the inverse forward index is as follows:
in the formula: x is a corresponding data value after the original data is processed; x' is corresponding data in the original data matrix M; min represents the minimum value of sample data and max represents the maximum value of sample data.
The calculated data is represented by X as a transformation matrix. When the data in the matrix are all in the interval of [0,1 ];
step 3, when the grey correlation method is used for calculation, the specific calculation of index assignment of each performance index is carried out according to the following steps, in order to obtain the conversion matrix X, the data is subjected to standardization processing according to a standardization processing mode, and then the correlation of the conversion matrix X is calculated according to the following formula:
and calculating corresponding absolute difference values by using the friction torque corresponding coefficient as reference data and applying a difference sequence matrix general formula to obtain a difference matrix, and calculating a maximum difference value and a minimum difference value:
Δi(k)＝|x 0 (k)-x i (k)| (k＝1,2.....,m i＝1,....n)
in the formula: x is a radical of a fluorine atom 0 (k) And x i (k) For measuring any two different data in the original data, Δ i (k) is the difference between the two different data, hmax is the maximum difference obtained by calculation, and Hmin is the minimum difference obtained by calculation. Calculating a difference matrix according to the general correlation coefficient formula to obtain a correlation coefficient matrix:
in the formula: x is a numerical value corresponding to the transformation matrix; rho is a resolution coefficient, the resolution coefficient reflects the distinguishing capability of each correlation coefficient through the magnitude of the value of the resolution coefficient, the value of the resolution coefficient is within (0, 1), and the distinguishing capability is enhanced along with the reduction of the correlation coefficient; xi is the i row of the comparative series in index factors of the main bearing of the shield machine; xi ij The gray correlation coefficient is a numerical value which reflects subjective and objective analysis, and the similarity between the index factor and the performance of the set reference index is larger, so that the objective preference and the subjective preference of the index factor are more similar to the reference index.
Calculating the correlation degree between each evaluation performance object and the reference performance to obtain the friction coefficient intensity and the correlation degree R between each related performance index factor i The formula is as follows:
in the formula: xi i (k) Is the kth correlation coefficient of the ith column;
and 4, after obtaining the relevance R among the index factors, multiplying the conversion matrix of the performance index test result by the relevance to obtain an integration matrix of relevance evaluation data, and displaying the evaluation data obtained by calculation in a spider web diagram mode (each group of data measured in the step 1 correspondingly generates a spider web diagram).
And 5, selecting the area and the perimeter of the spider web map as characteristic quantities, establishing an evaluation function and calculating the evaluation function of the spider web map so as to achieve the purpose of evaluating and analyzing the comprehensive performance of the main bearing of the shield machine. When perimeter and area calculation is carried out, the non-unique phenomenon of perimeter and area data caused by different index sequencing can be generated, in order to avoid the phenomenon, calculation is carried out by using a mode of average area and average perimeter so as to obtain characteristic quantities in the process of establishing and calculating a model, and the calculation formula of the average area and the average perimeter is as follows:
in the formula:
to evaluate the average area of the spider web plot of the data;
mean perimeter to evaluate spider web images of data; h is the number of index factors, and the numerical value of the current evaluation model is 5; representing the p index in the index factors; q represents the qth index in the index factors; theta is the included angle between two adjacent axes in the spider web diagram of the evaluation data, and the angle of the current evaluation model is 72 degrees.
Step 6. Evaluation vector E of evaluation object i ＝(t i1 ,t i2 ) Wherein t is i1 The relative value of the area is mainly used for reflecting the relative area of the corresponding spider web diagram of the main bearing of the shield machine to be tested; t is t i2 The meaning represented by the method is that the evaluation data among all index factors in a spider web diagram is reflected, and the coordination degree is reflected by calculating the ratio of the spider web diagram area to the spider web diagram perimeter of the evaluation data of the main bearing of the shield machine. The formula is as follows:
wherein G is the maximum area of the spider web plot of the evaluation data.
The currently established evaluation vector E belongs to a two-dimensional vector, so in the process of establishing an evaluation function of an evaluation data spider web diagram, the performance evaluation data is obtained by calculating the geometric mean of the two evaluation vectors and then establishing and calculating the evaluation function:
in the formula: and f represents an evaluation function value, and the larger the numerical value of the evaluation function value, the more excellent the comprehensive performance of the main bearing of the shield machine under test.
In summary, the present invention is only a case where the friction torque is used as a main reference index to perform comprehensive performance evaluation analysis, and the analysis result after integrating various factors changes due to the difference of the main reference index, for example, when the high temperature resistance of the main bearing of the shield machine is used as the most important index, the temperature is required to be used as the main reference index. Therefore, the comprehensive performance analysis model can analyze and evaluate the comprehensive performance of the main bearing of the shield machine in various ways according to different performance requirements.
The following data are used as a calculation case to perform performance evaluation calculation on the main bearing of the shield tunneling machine to obtain a spider web diagram shown in FIG. 2, and the specific process is as follows: the raw data obtained by the test are shown in table 1;
TABLE 1
The transformation matrix can be obtained by subjecting the raw data to a standardized processing formula, as shown in table 2.
TABLE 2
| Transformation matrix | First group | Second group | Third group | Fourth group |
| Axial vibration | 0 | 0.023543 | 0.004484 | 1 |
| Radial vibration | 0 | 0.171275 | 0.163758 | 1 |
| Temperature of | 1 | 0.785714 | 0 | 0.714286 |
| Frictional torque | 0.909091 | 1 | 0 | 0.272727 |
| Oil analysis | 0.833333 | 0.666667 | 1 | 0 |
Using coefficient of friction torque correspondence as reference data, X 0 ＝[0.909091 1 0 0.272727]. And calculating absolute difference formulas of corresponding elements of each evaluated object index sequence and the reference sequence one by one to obtain corresponding absolute differences after calculation, wherein the absolute differences are specifically shown in table 3.
TABLE 3
| Matrix of difference values | First group | Second group | Third group | Fourth group |
| Axial vibration | 0.909091 | 0.976457 | 0.004484 | 0.727273 |
| Radial vibration | 0.909091 | 0.828725 | 0.163758 | 0.727273 |
| Temperature of | 0.090909 | 0.214286 | 0 | 0.441558 |
| Oil analysis | 0.075758 | 0.333333 | 1 | 0.272727 |
The maximum and minimum values were confirmed, with the maximum value being 1 and the minimum value being 0. And calculating the correlation coefficient, and calculating the correlation coefficient of each element corresponding to the comparison sequence and the reference sequence respectively. Wherein rho is a resolution coefficient and is taken within (0, 1), if rho is smaller, the difference between the relation coefficients is larger, the distinguishing capability is stronger, and the text is 0.6. And respectively calculating the mean value of the association coefficients of each index of the comparison sequence corresponding to each evaluated performance object and the corresponding element of the reference performance sequence to reflect the association relationship between each evaluated performance object and the reference performance, wherein the calculation result of the association degree is shown in table 4.
TABLE 4
After the influence weights among the index factors are obtained, the conversion matrix of the performance index test result is multiplied by the influence weights obtained by calculating the relevance to obtain relevance evaluation data, the evaluation data obtained by calculating is displayed in a spider web diagram mode, the data is displayed more visually, and a data integration matrix of the evaluation result is shown in a table 5.
TABLE 5
After an integration matrix participating in evaluation of the lubricating grease is obtained, a performance spider web diagram of the main bearing of the shield machine can be generated according to the matrix parameters, and as shown in fig. 2, the performance spider web diagram is a second group of spider web diagrams. According to a calculation formula in the spider web diagram evaluation model, average area and average perimeter calculation is carried out on the four groups respectively, wherein the average area calculation result is shown in table 6:
TABLE 6
| First group | Second group | Third group | Fourth group |
| 0.781702 | 0.730549 | 0.026807 | 0.637073 |
The average circumference calculation results are shown in table 7:
TABLE 7
| First group | Second group | Third group | Fourth group |
| 4.009737 | 3.645185 | 0.872209 | 2.353811 |
And calculating an evaluation data spider web diagram generated after calculation, carrying out spider web diagram evaluation function model calculation on the data through an average area, an average perimeter and an evaluation model formula, and sorting the obtained function index calculation values, which are shown in the following table. By the aid of the calculation method of the evaluation function, comprehensive performance of evaluation data corresponding to the spider web diagram can be reflected accurately, and further comprehensive performance evaluation can be performed on four groups of bearing data, and the comprehensive performance evaluation is shown in table 8.
TABLE 8
| t1 | t2 | f | |
| First group | 1 | 0.610969 | 0.781645 |
| Second group | 0.934563 | 0.690908 | 0.803553 |
| Third group | 0.034293 | 0.442811 | 0.123229 |
| Fourth group | 0.814982 | 1.44496 | 1.085181 |
And comparing the values obtained by calculation in the model, wherein the four groups are sorted according to the magnitude of the function value f, the function value can be regarded as the comprehensive performance score under the current condition, and the performance is sorted into the fourth group > the second group > the first group > the third group. Namely the fourth group with the most excellent performance under the condition of the current experimental data.
In the current situation, friction torque is used as a main reference index to perform comprehensive performance evaluation and analysis, and the analysis result after the various factors are integrated changes due to the difference of the main reference index, for example, when the high temperature resistance of a main bearing of a shield machine is used as the most important index, the temperature is required to be used as the main reference index. Therefore, the comprehensive performance analysis model can analyze and evaluate the comprehensive performance of the main bearing of the shield machine in various ways according to different performance requirements.
The above-described embodiments are intended to illustrate rather than to limit the invention, and any modifications and variations of the present invention are within the spirit of the invention and the scope of the appended claims.
Claims (3)
1. A shield machine main bearing performance evaluation method based on spider web diagram-grey correlation analysis is characterized by comprising the following steps:
step 1, measuring performance index factors of a main bearing of the shield machine in an actual use state for multiple times. Synthesizing each group of measurement data into an original matrix M, and carrying out normalization processing on the original matrix to obtain a conversion matrix X;
step 2, when the grey correlation degree method is used for calculation, the specific calculation process of index assignment of each performance index is as follows:
calculating corresponding absolute difference values by using a difference sequence matrix general formula to obtain a difference matrix, and calculating a maximum difference value and a minimum difference value:
Δi(k)＝|x 0 (k)-x i (k)|(k＝1，2.....，mi＝1，....n)
in the formula: x is the number of 0 (k) And x i (k) For measuring any two different data in the original data, Δ i (k) is the difference between the two different data, hmax is the maximum difference obtained by calculation, and Hmin is the minimum difference obtained by calculation. And calculating a difference matrix according to the general correlation coefficient formula to obtain a correlation coefficient matrix:
in the formula: x is a numerical value corresponding to the transformation matrix; rho is a resolution coefficient, the resolution coefficient reflects the distinguishing capability of each correlation coefficient through the magnitude of the value of the resolution coefficient, the value of the resolution coefficient is within (0, 1), and the distinguishing capability is enhanced along with the reduction of the correlation coefficient; xi is the i row of the comparative series in index factors of the main bearing of the shield machine; xi ij The gray correlation coefficient is a numerical value which reflects subjective and objective analysis, and the similarity between the index factor and the performance of the set reference index is larger, so that the objective preference and the subjective preference of the index factor are more similar to the reference index.
Calculating the correlation degree between each evaluation performance object and the reference performance to obtain the friction coefficient intensity and the correlation degree R between each related performance index factor i The formula is as follows:
in the formula: xi i (k) Is the kth correlation coefficient of the ith column;
and 3, multiplying the conversion matrix of the performance index test result by the correlation degree to obtain an integration matrix of the correlation degree evaluation data, correspondingly generating a spider web map based on each group of data measured in the step 1, and displaying the integration matrix data obtained by calculation in the form of the spider web map.
Step 4, selecting the average area and the average perimeter of the spider web graph as characteristic quantities, and establishing a calculation formula for evaluating the average area and the average perimeter of the model as follows:
in the formula:
mean area to evaluate data spider web images;
mean perimeter to evaluate spider web images of data; h is the number of index factors, and the numerical value of the current evaluation model is 5; p represents the p index in the index factors; q represents the qth index in the index factors; theta is the included angle between two adjacent axes in the spider web diagram of the evaluation data, and the angle of the current evaluation model is 72 degrees.
Step 5, the evaluation vector of the evaluation object is E i ＝(t i1 ,t i2 ) Wherein t is i1 The relative value of the area is mainly used for reflecting the relative area of the corresponding spider web diagram of the main bearing of the shield machine to be tested; t is t i2 The meaning represented by the method is that the evaluation data among all index factors in a spider web diagram is reflected, and the coordination degree is reflected by calculating the ratio of the spider web diagram area to the spider web diagram perimeter of the evaluation data of the main bearing of the shield machine. The formula is as follows:
wherein G is the maximum area of the spider web plot of the evaluation data.
At the currently established evaluation vector E i The method belongs to two-dimensional vectors, and comprises the following steps of calculating the geometric mean value of two evaluation vectors, and then establishing and calculating an evaluation function to obtain performance evaluation data:
in the formula: and f represents an evaluation function value, and the larger the numerical value of the evaluation function value, the more excellent the comprehensive performance of the main bearing of the shield machine under test.
2. The method for evaluating the performance of the main bearing of the shield tunneling machine based on the spider diagram-gray correlation degree analysis according to claim 1, wherein in the step 1, the performance index factors comprise five performance indexes, specifically, radial vibration, axial vibration, temperature, friction torque and oil analysis.
3. The method for evaluating the performance of the main bearing of the shield tunneling machine based on the spider web diagram-gray correlation degree analysis according to claim 1, wherein in the step 1, the specific process of normalization treatment is as follows: the method comprises the following steps of performing dispersion standardization on an original data matrix M, normalizing data corresponding to all factors, performing linear transformation on the original data to enable the sizes of all factors participating in construction in the matrix to be in a [0,1] interval, and performing index data calculation formula in the original data matrix M as follows:
in the formula: x is a corresponding data value after the original data is processed; x' is corresponding data in the original data matrix M; min represents the minimum value of sample data and max represents the maximum value of sample data.
The calculated data is represented by X as a transformation matrix. The data in the matrix is in the [0,1] interval.
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| CN116070103A (en) * | 2023-03-07 | 2023-05-05 | 天津汉云工业互联网有限公司 | Rotating equipment health identification method and equipment based on multiple measuring points and multiple indexes |
| CN117326435A (en) * | 2023-11-30 | 2024-01-02 | 中国特种设备检测研究院 | Staircase fault diagnosis method and diagnosis system |
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| CN116070103A (en) * | 2023-03-07 | 2023-05-05 | 天津汉云工业互联网有限公司 | Rotating equipment health identification method and equipment based on multiple measuring points and multiple indexes |
| CN117326435A (en) * | 2023-11-30 | 2024-01-02 | 中国特种设备检测研究院 | Staircase fault diagnosis method and diagnosis system |
| CN117326435B (en) * | 2023-11-30 | 2024-03-22 | 中国特种设备检测研究院 | Staircase fault diagnosis method and diagnosis system |
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