CN116175281A - Vibration abnormality detection method for spindle system of machining center - Google Patents
Vibration abnormality detection method for spindle system of machining center Download PDFInfo
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- CN116175281A CN116175281A CN202310456937.9A CN202310456937A CN116175281A CN 116175281 A CN116175281 A CN 116175281A CN 202310456937 A CN202310456937 A CN 202310456937A CN 116175281 A CN116175281 A CN 116175281A
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- 230000005856 abnormality Effects 0.000 title claims abstract description 11
- 238000001514 detection method Methods 0.000 title description 2
- 238000011156 evaluation Methods 0.000 claims abstract description 45
- 230000036541 health Effects 0.000 claims abstract description 45
- 238000000034 method Methods 0.000 claims abstract description 26
- 239000013598 vector Substances 0.000 claims abstract description 23
- 239000011159 matrix material Substances 0.000 claims abstract description 22
- 230000002159 abnormal effect Effects 0.000 claims abstract description 17
- 238000012544 monitoring process Methods 0.000 abstract description 4
- 230000009471 action Effects 0.000 description 3
- 238000012423 maintenance Methods 0.000 description 2
- 238000013021 overheating Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000008358 core component Substances 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
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- 230000004048 modification Effects 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
- B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
- B23Q17/12—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring vibration
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention relates to the field of equipment performance monitoring, and discloses a method for detecting vibration abnormality of a main shaft system of a machining center, which comprises the steps of constructing a random matrix by utilizing basic data of the main shaft system of the machining center; calculating to obtain a eigenvalue vector of the random matrix; sorting absolute values of all feature values corresponding to the feature value vector, and selecting a front-stage feature value; constructing a health evaluation value according to the front-section characteristic value; calculating the absolute value of the error percentage of the health evaluation value at the initial moment and the current moment; comparing the absolute value of the error percentage with a set threshold value, and judging whether the vibration of a main shaft system of the machining center is abnormal at the current moment; the method has the advantages of small calculated amount and low complexity, a matrix is constructed according to the vibration signals, health evaluation indexes are constructed through the characteristic values and the contribution rates thereof based on the weighted thought, and then a judgment rule is constructed according to the absolute value of the error percentage, so that the vibration of the main shaft system of the machining center is detected, and whether the main shaft fails or not can be timely found.
Description
Technical Field
The invention relates to the field of equipment performance monitoring, in particular to a method for detecting vibration abnormality of a main shaft system of a machining center.
Background
The main shaft is used as a core component of a machining center, and the performance of the main shaft has a decisive influence on the machining precision and the productivity of the whole machine tool. With increasingly severe requirements on the reliability and the service life of the main shaft, the monitoring of working conditions is very important, and the running state of the main shaft is observed periodically or continuously, so that abnormal conditions such as abnormal wear, overheating, accidental damage and the like can be prevented.
Disclosure of Invention
Therefore, in order to timely identify the state of the main shaft of the machine tool and discover early symptoms of faults, the invention provides a method for detecting the vibration abnormality of the main shaft system of the machining center.
Specifically, the method for detecting vibration abnormality of the spindle system of the machining center comprises the following steps of
S100, constructing a random matrix by utilizing basic data of a main shaft system of a machining center;
s200, obtaining a eigenvalue vector of the random matrix through calculation; the step can obtain the eigenvalue and eigenvector of the random matrix. The eigenvalue vector refers to a vector composed of all eigenvalues.
S300, after the absolute values of all the characteristic values in the characteristic value vector are sequenced, selecting a front-stage characteristic value according to the accumulated contribution rate of the characteristic values and engineering experience;
s400, taking a contribution rate as a weight based on a weighted thought, and taking a weighted sum of the inverse squares of the characteristic values of the front section as a health evaluation value;
s500, respectively taking vibration data of a main shaft at the initial moment and the current moment as the basic data, and sequentially passing through the steps S100 to S400 to construct an initial moment health evaluation value and a current moment health evaluation value;
s600, calculating an error percentage absolute value of the initial time health evaluation value and the current time health evaluation value;
s700, comparing the absolute value of the error percentage with a set threshold value, and judging whether the vibration of the main shaft system of the machining center is abnormal at the current moment.
The invention has the following beneficial effects:
the method has the advantages of small calculated amount and low complexity, a matrix is constructed according to the vibration signals of the main shaft in the main shaft system of the machining center, health evaluation indexes are constructed through the characteristic values and the contribution rates thereof based on the weighted thought, and then a judgment rule is constructed according to the absolute value of the error percentage, so that the vibration condition of the main shaft system of the machining center is judged, whether the vibration of the main shaft system of the machining center is abnormal or not can be timely found, the fault hidden danger can be conveniently and timely eliminated by staff, and the intelligent maintenance of equipment is realized.
In the above method, the random matrix is constructed because one variable cannot be a fixed value, but has a certain randomness, for example, fluctuates in a certain range, and a matrix constructed by the history data of these variables is called a random matrix.
The ranking in the above method is based on the absolute values of all eigenvalues in the eigenvalue vector, because the larger the absolute value of the eigenvalue, the larger its impact on the result is explained. The purpose of selecting the front-stage characteristic value is to select the characteristic value with larger influence on the result, delete the characteristic value with smaller influence on the result, and reduce the calculated amount.
In the above method, according to the former-stage feature value, in order to increase the influence of the feature value with a large contribution rate and the feature value with a small attenuation contribution rate on the health evaluation result, the feature value is inverted, and based on the weighted thought, the weighted sum of the inverse squares of the feature values is taken as the health evaluation value with the contribution rate as the weight.
The absolute value of the error percentage is selected for comparison with the threshold value in the above method because the error percentage corresponds to a degree reflecting the deviation of the current health evaluation value from the initial health evaluation value. The larger the absolute value of the error percentage, the larger the difference between the current health evaluation value and the initial health evaluation value, and the less healthy the system. The smaller the absolute value of the error percentage, the smaller the difference between the current health evaluation value and the initial health evaluation value, and the system is healthier.
Drawings
Fig. 1 is a schematic flow chart of a method for detecting vibration abnormality of a spindle system of a machining center according to the present invention.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
In the following description of the embodiment of the present application with reference to fig. 1, since the requirements on the reliability and the service life of the spindle in the machining center are increasingly stringent, the monitoring of the working condition is very important, and the running state of the spindle needs to be periodically or continuously observed to prevent abnormal situations such as abnormal wear, overheating, unexpected damage, and the like; the invention provides a method for detecting vibration abnormality of a main shaft system of a machining center, which comprises the following steps:
s100, constructing a random matrix by utilizing basic data of a main shaft system of a machining center;
s200, obtaining a eigenvalue vector of the random matrix through calculation;
s300, after the absolute values of all the characteristic values in the characteristic value vector are sequenced, selecting a front-stage characteristic value according to the accumulated contribution rate of the characteristic values and engineering experience;
s400, taking a contribution rate as a weight based on a weighted thought, and taking a weighted sum of the inverse squares of the characteristic values of the front section as a health evaluation value;
s500, respectively taking vibration data of a main shaft at the initial moment and the current moment as the basic data, and sequentially passing through the steps S100 to S400 to construct an initial moment health evaluation value and a current moment health evaluation value;
s600, calculating an error percentage absolute value of the initial time health evaluation value and the current time health evaluation value;
s700, comparing the absolute value of the error percentage with a set threshold value, and judging whether the vibration of the main shaft system of the machining center is abnormal at the current moment.
Specifically, when vibration data of a spindle at an initial time of a spindle system of a machining center is used as basic data, the method for constructing the initial time health evaluation value is as follows:
obtaining vibration data of initial moment in the main shaft historical data of the main shaft system of the machining center, wherein the main shaft at the initial moment belongs to a normal state, the vibration data at the initial moment is also normal or standard data, and constructing the initial moment according to the vibration data at the initial moment
Random matrix->
；
In the above-mentioned formula(s),
for the initial time +.>
Vibration signal of the spindle.
The random matrix at the initial time is calculated by the following formula
Characteristic value vector +.>
；
Is a random matrix->
Middle->
The value of the characteristic is a value of,
wherein ,
to satisfy the above formula +.>
A non-0 column vector is maintained.
According to the eigenvalue vector
Vector +.>
All characteristic values of (2) are ordered from big to small to obtain
And selecting the pre +/according to the following formula>
Personal characteristic value->
，
wherein ,
is->
Contribution rate of individual characteristic values, +.>
Can be determined according to engineering experience>
Is->
And characteristic values.
The initial time health evaluation value is constructed by the following formula
That is, based on the weighted thought, the contribution ratio is used as the weight, and the weighted sum of the inverse squares of the feature values of the former stage is used as the time health evaluation value.
Specifically, when vibration data of the spindle at the current moment is taken as basic data, the method for constructing the health evaluation value at the current moment is as follows:
vibration data of the main shaft system of the machining center at the current moment is obtained, and the current moment is constructed
Random matrix->
；
wherein ,
above-mentionedIn the formula (i),
is->
Vibration signal of the spindle at the current moment.
The random matrix at the current moment is calculated by the following formula
Characteristic value vector +.>
；
Is a random matrix->
Middle->
The value of the characteristic is a value of,
wherein ,
to satisfy the above formula +.>
A non-0 column vector is maintained. />
According to the eigenvalue vector
Vector +.>
All the characteristic values are sequenced from big to small to obtain
And selecting the pre +/according to the following formula>
Personal characteristic value->
，
wherein ,
is->
Contribution rate of individual characteristic values, +.>
Can be determined according to engineering experience>
Is->
And characteristic values.
The initial time health evaluation value is constructed by the following formula
Namely, based on a weighting thought, taking a contribution rate as a weight, and taking a weighted sum of the inverse squares of the characteristic values of the front section as a health evaluation value at the current moment;
at the initial time, health evaluation value is obtained
And the current time health evaluation value +.>
After that, the absolute value of the error percentage of the initial time health evaluation value and the current time health evaluation value is calculated +.>
；
Comparing the absolute value of the error percentage with a set threshold value, and judging whether the main shaft of a main shaft system of the machining center is abnormal at the current moment or not, wherein the absolute value of the error percentage is specifically as follows:
when (when)
When the vibration of the main shaft is abnormal, namely the vibration of a main shaft system of the machining center is abnormal;
when (when)
When the vibration of the main shaft is not abnormal, namely the vibration of a main shaft system of the machining center is not abnormal;
wherein ,
is the set threshold, which is determined empirically through engineering practice.
In the above method, according to the former-stage feature value, in order to increase the influence of the feature value with a large contribution rate and the feature value with a small attenuation contribution rate on the health evaluation result, the feature value is inverted, and based on the weighted thought, the weighted sum of the inverse squares of the feature values is taken as the health evaluation value with the contribution rate as the weight.
According to the invention, the matrix is constructed according to the vibration signals of the main shaft in the main shaft system of the machining center, the health evaluation index is constructed based on the weighted thought through the characteristic value and the contribution rate thereof, and then the judgment rule is constructed according to the absolute value of the error percentage, so that the vibration condition of the main shaft system of the machining center is judged, whether the vibration of the main shaft system of the machining center is abnormal or not can be timely found, the calculated amount is small, the complexity is low, the fault hidden danger can be conveniently and timely eliminated by staff, and the intelligent maintenance of equipment is realized.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. The method for detecting the vibration abnormality of the spindle system of the machining center is characterized by comprising the following steps of:
s100, constructing a random matrix by utilizing basic data of a main shaft system of a machining center;
s200, obtaining a eigenvalue vector of the random matrix through calculation;
s300, after the absolute values of all the characteristic values in the characteristic value vector are sequenced, selecting a front-stage characteristic value according to the accumulated contribution rate of the characteristic values;
s400, taking a contribution rate as a weight based on a weighted thought, and taking a weighted sum of the inverse squares of the characteristic values of the front section as a health evaluation value;
s500, respectively taking vibration data of a main shaft at the initial moment and the current moment as the basic data, and sequentially passing through the steps S100 to S400 to construct an initial moment health evaluation value and a current moment health evaluation value;
s600, calculating an error percentage absolute value of the initial time health evaluation value and the current time health evaluation value;
s700, comparing the absolute value of the error percentage with a set threshold value, and judging whether the vibration of the main shaft system of the machining center is abnormal at the current moment.
2. The method for detecting vibration anomalies of a spindle system of a machining center according to claim 1, wherein the method for ordering absolute values of all characteristic values is: ordering from large to small is used.
3. According to claim 1A method for detecting vibration abnormality of a spindle system of a machining center is characterized by comprising the steps of
Is the absolute value of the error percentage of the initial time health evaluation value and the current time health evaluation value, let +.>
Is the set threshold, which is determined through engineering practical experience;
when (when)
When the vibration of the main shaft system of the processing center at the current moment is abnormal;
when (when)
And when the vibration of the main shaft system of the processing center at the current moment is not abnormal.
4. The method for detecting vibration anomalies of a spindle system of a machining center according to claim 1, wherein eigenvalue vectors of the random matrix are calculated by the following formula:
wherein ,
is->
Random matrix of moments>
Is a eigenvector of a random matrix,>
is +.>
A vector other than 0 is maintained.
5. The method for detecting vibration anomalies of a machining center spindle system according to claim 1, wherein the front-end eigenvalues are selected by the following formula:
wherein ,
is->
Contribution rate of individual characteristic values, +.>
Is the dimension of the random matrix,/->
Is the moment of->
Is at->
All eigenvalues in eigenvector are ordered +.>
A characteristic value; />
Is->
Absolute value of feature vector +_>
Is a feature vector of a random matrix;
6. The method for detecting vibration abnormality of machining center spindle system according to claim 5, wherein a weighted sum of the inverse squares of the characteristic values of the former stage is used as a health evaluation value based on a weighted thought, and the health evaluation value is constructed by using the following formula:
wherein ,
is a health evaluation value. />
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