CN111811847A - Fault detection method and system for roll-to-roll system and storage medium - Google Patents
Fault detection method and system for roll-to-roll system and storage medium Download PDFInfo
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Abstract
The invention discloses a fault detection method, a fault detection system and a storage medium of a roll-to-roll system, wherein the method comprises the following steps: acquiring current roller vibration data through a vibration sensor; extracting current characteristic parameters from the current roller vibration data; calculating the deviation value of the distribution of the current characteristic parameters and the distribution of the normal characteristic parameters; and judging whether the roll-to-roll system has faults or not according to the deviation trends obtained by the deviation values at different moments. The fault of the roller-to-roller system can be quickly judged and accurately positioned, and the maintenance efficiency is improved.
Description
Technical Field
The invention relates to the field of machine fault detection, in particular to a fault detection method and system of a roller-to-roller system and a storage medium.
Background
Roll-to-roll systems are widely used in manufacturing applications such as papermaking, textile forming, bleaching, mercerizing, film making, metal coating, and the like. During the use of the roll-to-roll system, the roll shaft and the bearing are the most problematic components, and once the problems occur, the production efficiency and the product quality are seriously affected. Moreover, the trouble-shooting process of the roll-to-roll system is rather complicated, and it is difficult to determine the position of a roll having a trouble problem among a plurality of rolls of the roll-to-roll system in a short time.
Disclosure of Invention
The present invention is directed to solve at least one of the problems of the prior art, and provides a method and a system for detecting a failure of a roll-to-roll system, and a storage medium.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect of the present invention, a method for detecting a failure in a roll-to-roll system comprises the steps of:
a data acquisition step: acquiring current roller vibration data through a vibration sensor, wherein the vibration sensor is arranged on a bearing seat of the roller-to-roller system, which is provided with a roller shaft;
and (3) data processing: inputting the current roller vibration data into a data processing network, wherein the data processing network performs the following processing on the current roller vibration data:
extracting current characteristic parameters from the current roller vibration data;
calculating deviation values of the distribution of the current characteristic parameters and the distribution of normal characteristic parameters, wherein the normal characteristic parameters are characteristic parameters extracted according to normal roller vibration data collected in the normal running state of the roller-to-roller system;
repeating the data acquisition step and the data processing step to obtain the deviation values at a plurality of different moments so as to obtain a deviation trend;
and judging whether the roll-to-roll system has faults or not according to the deviation trend.
According to the first aspect of the present invention, the offset value is calculated according to the following formula:
wherein L2 is the euclidean distance between the distribution of the current feature parameter and the distribution of the normal feature parameter; h (X) is the distribution of the normal characteristic parameters, denoted as { X }11,X12,…,X1k}; g (X) is the distribution of the current characteristic parameter, denoted as { X }21,X22,…,X2k}；
According to the first aspect of the present invention, the determining whether the roll-to-roll system has a fault according to the deviation trend specifically includes: and if the deviation trend is that the deviation value has an increasing trend, judging that the roll-to-roll system has a fault.
According to the first aspect of the present invention, the current characteristic parameters extracted from the current roller vibration data include a current roller shaft characteristic parameter and a current bearing characteristic parameter.
According to the first aspect of the present invention, the extracting of the current characteristic parameter from the current roller vibration data includes the steps of:
carrying out low-pass filtering on the current roller vibration data to obtain a low-frequency signal;
performing fast Fourier transform on the low-frequency signal;
extracting the low-frequency signals of the frequency multiplication of the rotating speed 1 of the roll shaft and the frequency multiplication of the rotating speed 2 of the roll shaft as the characteristic parameters of the current roll shaft;
carrying out high-pass filtering on the current roller vibration data to obtain a high-frequency signal;
demodulating the envelope of the high-frequency signal;
and extracting the effective value and the peak-to-peak value of the envelope time domain signal as the current bearing characteristic parameters.
According to the first aspect of the present invention, when the current characteristic parameter is the current roller shaft characteristic parameter, the fault detection method specifically includes the steps of:
calculating a first deviation value of the distribution of the current roll shaft characteristic parameters and the distribution of normal roll shaft characteristic parameters, wherein the normal roll shaft characteristic parameters are roll shaft characteristic parameters extracted according to normal roll vibration data collected in a normal running state of the roll-to-roll system;
obtaining a plurality of first deviation values at different moments so as to obtain a first deviation trend;
and judging whether a roller shaft of the roller-to-roller system has a fault according to the first deviation trend.
According to the first aspect of the present invention, when the current characteristic parameter is the current bearing characteristic parameter, the fault detection method specifically includes the following steps:
calculating a second deviation value of the distribution of the current bearing characteristic parameters and the distribution of normal bearing characteristic parameters, wherein the normal bearing characteristic parameters are extracted according to normal roller vibration data collected in the normal running state of the roller-to-roller system;
obtaining a plurality of second deviation values at different moments so as to obtain a second deviation trend;
and judging whether the bearing of the roll-to-roll system has a fault according to the second deviation trend.
According to the first aspect of the present invention, before inputting the current roll vibration data to the data processing network, the method further comprises the steps of: preprocessing the current roll vibration data.
A failure detection system to which the failure detection method of a roll-to-roll system according to the first aspect of the present invention is applied is characterized by comprising:
the data acquisition module is used for acquiring current roller vibration data and comprises a vibration sensor arranged on a bearing seat of the roller-to-roller system, wherein the bearing seat is provided with a roller shaft;
a data processing module, the data processing module comprising:
a parameter extraction module for extracting current characteristic parameters from the current roller vibration data,
the deviant calculation module is used for calculating deviant of the distribution of the current characteristic parameters and the distribution of normal characteristic parameters, wherein the normal characteristic parameters are characteristic parameters extracted according to normal roller vibration data collected in the normal running state of the roller-to-roller system; and
and the fault judging module is used for judging whether the roll-to-roll system has faults or not according to the offset trend, wherein the offset trend is obtained according to the offset values at a plurality of different moments obtained in the data processing step.
In a third aspect of the present invention, a storage medium stores executable instructions that are executable by a computer to cause the computer to perform the method of fault detection in a roll-to-roll system according to the first aspect of the present invention.
The scheme at least has the following beneficial effects: the current characteristic parameters are extracted from the current roller vibration data, the distribution of the current characteristic parameters is compared with the distribution of the normal characteristic parameters to obtain deviation values, whether the roller-to-roller system has faults or not is judged according to the deviation trend obtained by the deviation values, and which roller with the fault problem is in the roller-to-roller system can be accurately judged.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a schematic view of a roll-to-roll system;
FIG. 2 is a flow chart of a method of fault detection for a roll-to-roll system in accordance with an embodiment of the present invention;
FIG. 3 is a graph of a distribution of current characteristic parameters versus a distribution of normal characteristic parameters;
fig. 4 is a block diagram of a fault detection system of a roll-to-roll system according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the present preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like elements throughout.
In the description of the present invention, it should be understood that the orientation or positional relationship referred to in the description of the orientation, such as the upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
Referring to fig. 1 and 2, certain embodiments of the present invention provide a method of fault detection for a roll-to-roll system, comprising the steps of:
s100, data acquisition: acquiring current roller vibration data through a vibration sensor 43, wherein the vibration sensor 43 is arranged on a bearing seat 41 of a roller-to-roller system, which is provided with a roller shaft 42, and each roller is provided with one vibration sensor 43;
step S200, data processing step: inputting the vibration data of the current roller into a data processing network, wherein the data processing network is a deep neural network;
the data processing network performs the following processing on the current roller vibration data:
step S210, extracting the current characteristic parameter of each roller from the current roller vibration data collected by each vibration sensor 43;
step S220, calculating deviation values of the distribution of the current characteristic parameters and the distribution of normal characteristic parameters, wherein the normal characteristic parameters are characteristic parameters extracted according to a large amount of normal roller vibration data collected in a roller normal running state of a roller-to-roller system, and the distribution of the final normal characteristic parameters for comparison is an average value of the distribution of a plurality of normal characteristic parameters;
step S300, repeating the step S100 and the step S200 to obtain a plurality of deviation values at different moments so as to obtain a deviation trend;
and S400, judging whether the roll-to-roll system has faults or not according to the offset trend.
In the embodiment, the current characteristic parameters are extracted from the current roller vibration data, the distribution of the current characteristic parameters is compared with the distribution of the normal characteristic parameters to obtain the deviation value, whether the roller-to-roller system has faults or not is judged according to the deviation trend obtained by the deviation value, and which roller with the fault problem in the roller-to-roller system is can be accurately judged, so that the quick judgment and the accurate positioning are realized, and the maintenance efficiency is improved.
In addition, because the transmission system of the roll-to-roll manufacturing system is simple, and the interference of other external vibration is very small, the signal collected from the vibration sensor 43 sufficiently reflects the working state of the roll-to-roll system, and the effectiveness of fault detection of the roll-to-roll manufacturing system is ensured. The bearing blocks 41 at both ends of the roll shaft 42 are provided with vibration sensors 43, and the sampling rate of the rotation speed of the vibration sensors 43 can be 30-40 times of that of the roll shaft 42.
For step S100, when the roll-to-roll system is started, operated, and stopped, the difference between the effective values of the vibration signals is large, and a threshold value is selected as a working start-stop judgment standard of the roll-to-roll system. The shutdown data is invalid data, so only startup and operational data is collected in the data collection step.
Referring to fig. 3, further, the offset value is calculated according to the following formula:
wherein L2 is the euclidean distance between the distribution of the current characteristic parameter and the distribution of the normal characteristic parameter; h (X) is the distribution of normal characteristic parameters, denoted as { X }11,X12,…,X1kAnd each element X1kEach contains m eigenvalues; g (X) is the distribution of the current characteristic parameter, denoted as { X }21,X22,…,X2kAnd each element X2kAll contain n bitsA characteristic value;
further, judging whether the roll-to-roll system has a fault according to the offset trend specifically comprises: if the offset trend is that the offset value has an increasing trend, the roll-to-roll system is judged to have a fault. For example, offset values at a plurality of different time points are arranged in time order as follows: 1,2,4,3,4,5,8,7,5, 7; although the offset value in the middle part is smaller than the previous offset value, the overall reflected offset trend is still that the offset value has an increasing trend.
Further, the current characteristic parameters extracted from the current roller vibration data include a current roller shaft characteristic parameter and a current bearing characteristic parameter. The current roll shaft characteristic parameters are used for judging whether the roll shaft 42 in the roll-to-roll system has a fault problem, and the current bearing characteristic parameters are used for judging whether the bearing in the roll-to-roll system has a fault problem.
Further, the step 210 of extracting the current characteristic parameter from the current roller vibration data specifically includes the following steps:
carrying out low-pass filtering on the vibration data of the current roller to obtain a low-frequency signal; the low-frequency signal is a signal with the frequency below 1 kHz;
carrying out fast Fourier transform on the low-frequency signal;
extracting low-frequency signals of the frequency multiplication of the rotating speed 1 of the roll shaft 42 and the frequency multiplication of the rotating speed 2 of the roll shaft 42 as current roll shaft characteristic parameters;
carrying out high-pass filtering on the vibration data of the current roller to obtain a high-frequency signal; the high-frequency signal is a signal having a frequency of 1kHz or more;
demodulating the envelope of the high-frequency signal;
and extracting the effective value and the peak-to-peak value of the envelope time domain signal as the current bearing characteristic parameters.
According to the imbalance of the roll shafts 42 and the bending mechanism of the roll shafts 42, the low-frequency signals corresponding to the frequency multiplication of the rotating speed 1 of the roll shafts 42 and the frequency multiplication of the rotating speed 2 of the roll shafts 42 can reflect the characteristics of the roll shafts. The failure of the bearing usually occurs in a high frequency stage, so the effective value and peak-to-peak value of the envelope time domain signal can reflect the bearing characteristics.
In one aspect, for the current roll shaft characteristic parameters, the process is as follows:
calculating a first deviation value of the distribution of the current roll shaft characteristic parameters and the distribution of normal roll shaft characteristic parameters, wherein the normal roll shaft characteristic parameters are roll shaft characteristic parameters extracted according to normal roll vibration data collected in a normal running state of a roll-to-roll system;
obtaining a plurality of first deviation values at different moments so as to obtain a first deviation trend;
whether the roll shaft 42 of the roll-to-roll system has a fault is judged according to the first deviation trend.
The quick judgment and the accurate positioning of the faults of the roll shaft 42 are realized, and the maintenance efficiency is improved.
In another aspect, for the current bearing characteristic parameter, the process is as follows:
calculating a second deviation value of the distribution of the current bearing characteristic parameters and the distribution of the normal bearing characteristic parameters, wherein the normal bearing characteristic parameters are extracted according to normal roller vibration data acquired in the normal running state of the roller-to-roller system;
obtaining a plurality of second deviation values at different moments so as to obtain a second deviation trend;
and judging whether the bearing of the roll-to-roll system has a fault according to the second deviation trend.
The bearing fault can be quickly judged and accurately positioned, and the maintenance efficiency is improved.
Further, before inputting the current roll vibration data into the data processing network, the method further comprises the following steps: preprocessing the current roller vibration data. Specifically, the preprocessing includes raising abnormal data and filling in missing data, thereby avoiding false alarms caused by abnormal data or missing data.
Referring to fig. 4, certain embodiments of the present invention provide a fault detection system employing a method of fault detection for a roll-to-roll system as described in method embodiments.
The fault detection system includes:
the data acquisition module 10 is used for acquiring current roller vibration data and comprises a vibration sensor 43 arranged on a bearing seat 41 of a roller-to-roller system, wherein the bearing seat is provided with a roller shaft 42;
a parameter extraction module 21 for extracting the current characteristic parameter from the current roller vibration data,
the deviant calculation module 22 is used for calculating deviant of the distribution of the current characteristic parameters and the distribution of normal characteristic parameters, wherein the normal characteristic parameters are characteristic parameters extracted according to normal roller vibration data collected in the normal running state of the roller-to-roller system; and
and a failure judging module 30, configured to judge whether the roll-to-roll system has a failure according to an offset trend, where the offset trend is obtained according to offset values at a plurality of different times obtained in the data processing step.
In this embodiment of the apparatus, the fault detection system can perform each step of the fault detection method by applying the fault detection method as described in the embodiment of the method, and has the same technical effect as the fault detection method, and will not be described in detail herein.
Certain embodiments of the present invention also provide a storage medium having stored thereon executable instructions that can be executed by a computer to cause the computer to perform a method of fault detection for a roll-to-roll system as described in method embodiments.
Examples of storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
The above description is only a preferred embodiment of the present invention, and the present invention is not limited to the above embodiment, and the present invention shall fall within the protection scope of the present invention as long as the technical effects of the present invention are achieved by the same means.
Claims (10)
1. The fault detection method of the roll-to-roll system is characterized by comprising the following steps:
a data acquisition step: acquiring current roller vibration data through a vibration sensor, wherein the vibration sensor is arranged on a bearing seat of the roller-to-roller system, which is provided with a roller shaft;
and (3) data processing: inputting the current roller vibration data into a data processing network, wherein the data processing network performs the following processing on the current roller vibration data:
extracting current characteristic parameters from the current roller vibration data;
calculating deviation values of the distribution of the current characteristic parameters and the distribution of normal characteristic parameters, wherein the normal characteristic parameters are characteristic parameters extracted according to normal roller vibration data collected in the normal running state of the roller-to-roller system;
repeating the data acquisition step and the data processing step to obtain the deviation values at a plurality of different moments so as to obtain a deviation trend;
and judging whether the roll-to-roll system has faults or not according to the deviation trend.
2. The method of fault detection of a roll-to-roll system according to claim 1, characterized in that the offset value is calculated according to the following formula:
wherein L2 is the euclidean distance between the distribution of the current feature parameter and the distribution of the normal feature parameter; h (X) is the distribution of the normal characteristic parameters, denoted as { X }11,X12,…,X1k}; g (X) is the distribution of the current characteristic parameter, denoted as { X }21,X22,…,X2k}；
3. The method for detecting the failure of the roll-to-roll system according to claim 2, wherein the determining whether the roll-to-roll system has the failure according to the deviation trend specifically comprises: and if the deviation trend is that the deviation value has an increasing trend, judging that the roll-to-roll system has a fault.
4. The method of fault detection for a roll-to-roll system of claim 3, wherein the current characteristic parameters extracted from the current roll vibration data include current roll shaft characteristic parameters and current bearing characteristic parameters.
5. The method of claim 4, wherein said extracting current characteristic parameters from current roll vibration data comprises the steps of:
carrying out low-pass filtering on the current roller vibration data to obtain a low-frequency signal;
performing fast Fourier transform on the low-frequency signal;
extracting the low-frequency signals of the frequency multiplication of the rotating speed 1 of the roll shaft and the frequency multiplication of the rotating speed 2 of the roll shaft as the characteristic parameters of the current roll shaft;
carrying out high-pass filtering on the current roller vibration data to obtain a high-frequency signal;
demodulating the envelope of the high-frequency signal;
and extracting the effective value and the peak-to-peak value of the envelope time domain signal as the current bearing characteristic parameters.
6. The method for detecting a failure of a roll-to-roll system according to claim 4, wherein when the current characteristic parameter is the current roll shaft characteristic parameter, the method specifically comprises the following steps:
calculating a first deviation value of the distribution of the current roll shaft characteristic parameters and the distribution of normal roll shaft characteristic parameters, wherein the normal roll shaft characteristic parameters are roll shaft characteristic parameters extracted according to normal roll vibration data collected in a normal running state of the roll-to-roll system;
obtaining a plurality of first deviation values at different moments so as to obtain a first deviation trend;
and judging whether a roller shaft of the roller-to-roller system has a fault according to the first deviation trend.
7. The method for detecting a failure of a roll-to-roll system according to claim 4, wherein when the current characteristic parameter is the current bearing characteristic parameter, the method specifically comprises the steps of:
calculating a second deviation value of the distribution of the current bearing characteristic parameters and the distribution of normal bearing characteristic parameters, wherein the normal bearing characteristic parameters are extracted according to normal roller vibration data collected in the normal running state of the roller-to-roller system;
obtaining a plurality of second deviation values at different moments so as to obtain a second deviation trend; and judging whether the bearing of the roll-to-roll system has a fault according to the second deviation trend.
8. The method of fault detection for a roll-to-roll system according to claim 1, characterized in that before inputting said current roll vibration data into a data processing network, it further comprises the steps of: preprocessing the current roll vibration data.
9. A failure detection system to which the failure detection method of the roll-to-roll system according to any one of claims 1 to 8 is applied, comprising:
the data acquisition module is used for acquiring current roller vibration data and comprises a vibration sensor arranged on a bearing seat of the roller-to-roller system, wherein the bearing seat is provided with a roller shaft;
a data processing module, the data processing module comprising:
a parameter extraction module for extracting current characteristic parameters from the current roller vibration data,
the deviant calculation module is used for calculating deviant of the distribution of the current characteristic parameters and the distribution of normal characteristic parameters, wherein the normal characteristic parameters are characteristic parameters extracted according to normal roller vibration data collected in the normal running state of the roller-to-roller system; and
and the fault judging module is used for judging whether the roll-to-roll system has faults or not according to the offset trend, wherein the offset trend is obtained according to the offset values at a plurality of different moments obtained in the data processing step.
10. Storage medium, characterized in that it stores executable instructions that can be executed by a computer, causing the computer to perform a method of fault detection of a roll-to-roll system according to any one of claims 1 to 8.
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Effective date of registration: 20230301 Address after: Units 103 and 203, Block B1, Hantian Science and Technology City, 17 Shenhai Road, Guicheng Street, Nanhai District, Foshan City, Guangdong Province, 528200 (residence application) Applicant after: Anmason Intelligent Technology (Guangdong) Co.,Ltd. Address before: Unit 1601, 16th floor, building 6, area a, Hantian science and Technology City, 17 Shenhai Road, Guicheng Street, Nanhai District, Foshan City, Guangdong Province, 528200 Applicant before: GUANGDONG GLOBAL SMART TECHNOLOGY CO.,LTD. |
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Application publication date: 20201023 |
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