CN116087018A - Abrasion detection method of coating machine - Google Patents
Abrasion detection method of coating machine Download PDFInfo
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- CN116087018A CN116087018A CN202211616338.0A CN202211616338A CN116087018A CN 116087018 A CN116087018 A CN 116087018A CN 202211616338 A CN202211616338 A CN 202211616338A CN 116087018 A CN116087018 A CN 116087018A
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- 238000000576 coating method Methods 0.000 title claims abstract description 64
- 239000011248 coating agent Substances 0.000 title claims abstract description 62
- 238000001514 detection method Methods 0.000 title claims abstract description 60
- 238000005299 abrasion Methods 0.000 title claims abstract description 44
- 238000000034 method Methods 0.000 claims abstract description 42
- 238000009826 distribution Methods 0.000 claims abstract description 10
- 230000000737 periodic effect Effects 0.000 claims abstract description 9
- 238000001914 filtration Methods 0.000 claims description 22
- 238000005070 sampling Methods 0.000 claims description 21
- 238000012360 testing method Methods 0.000 abstract description 5
- 238000001228 spectrum Methods 0.000 description 16
- 238000010586 diagram Methods 0.000 description 8
- 238000005259 measurement Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 230000015572 biosynthetic process Effects 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 238000007755 gap coating Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000005096 rolling process Methods 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 1
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 239000013543 active substance Substances 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005538 encapsulation Methods 0.000 description 1
- 239000011888 foil Substances 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 229910052744 lithium Inorganic materials 0.000 description 1
- 229910001416 lithium ion Inorganic materials 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000010349 pulsation Effects 0.000 description 1
- 239000002002 slurry Substances 0.000 description 1
- 238000003756 stirring Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000002344 surface layer Substances 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N5/00—Analysing materials by weighing, e.g. weighing small particles separated from a gas or liquid
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G17/00—Apparatus for or methods of weighing material of special form or property
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
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Abstract
A method of wear detection for a coater, comprising: and acquiring original weight data on the coated pole piece. Each data-bearing coated segment on the pole piece is stripped of head-to-tail data to obtain primary weight data on the pole piece. And acquiring the frequency and period of the to-be-measured piece on the coating machine. And carrying out periodic analysis by using the to-be-detected piece, and searching a plurality of effective interval sections in the primary weight data on the pole piece, wherein the effective interval sections are the number of the primary weight data which can completely reproduce one periodic fluctuation of the to-be-detected piece. And splicing the plurality of effective interval sections to form an effective pole piece. And calculating the data quantity to be tested according to the resolution ratio, and acquiring the weight data on the effective pole piece according to the data quantity. And putting the obtained weight data on the effective pole piece into an FFT algorithm to obtain corresponding frequency distribution and amplitude, and drawing a spectrogram of the to-be-measured piece. The designed abrasion detection method can efficiently determine the abrasion degree of the to-be-detected piece through the spectrogram, and reduces the test precision requirement of the detection instrument.
Description
Technical Field
The application relates to the technical field of lithium ion batteries, in particular to a wear detection method of a coating machine.
Background
The lithium battery manufacturing process is divided into a front-stage process (pole piece manufacturing), a middle-stage process (battery cell synthesis) and a back-stage process (formation and encapsulation). The main process flow of the front-stage procedure is as follows: stirring, coating, rolling, slitting, flaking and die cutting are used as core links of the front-stage working procedure, and the execution quality of the coating working procedure deeply influences the consistency, the safety and the service life of the finished battery. The rolling is to further compact the coated pole piece, thereby improving the energy density of the battery. The flatness of the rolled pole piece can directly influence the processing effect of the subsequent slitting process, and the uniformity of the pole piece active substance can also indirectly influence the performance of the battery cell. The battery manufacturer produces the pole piece, and the thick liquids of pole piece are pressed and are coated on the foil through the screw pump, and in whole coating process, the pole piece is rotated by the backing roll and is conveyed. The screw pump and the back roller are worn in the use process, so that the coating quantity of the pole piece slurry is deviated and the coating is uneven.
The existing abrasion detection method for the screw pump and the back roller in the coating machine is to weigh the pole pieces before and after coating or to detect the thickness of the pole pieces before and after coating. Such conventional detection methods require that the detection instrument have high detection accuracy, such as micrometer, ten-thousandth. In the detection process, the weight data or the thickness data are acquired one by taking the detection instrument manually, and then the acquired data are calculated and compared to obtain a detection conclusion, so that the problem of low abrasion detection efficiency exists.
Disclosure of Invention
The application provides a wear detection method of a coating machine, which is mainly aimed at reducing the instrument precision requirement of wear detection and improving the wear detection efficiency.
An embodiment of the present application provides a method for detecting wear of a coater, including:
acquiring original weight data on the coated pole piece;
removing head data and tail data from each data-bearing coating segment on the pole piece to obtain primary weight data on the pole piece;
acquiring the frequency and period of a piece to be tested on a coating machine;
carrying out periodic analysis by the piece to be detected, and searching a plurality of effective interval sections in the primary weight data on the pole piece, wherein the effective interval sections are the number of the primary weight data which can completely reproduce one periodic fluctuation of the piece to be detected, and the primary weight data in the effective interval sections are not zero;
splicing a plurality of effective interval sections obtained on the pole piece together to form an effective pole piece;
calculating the data volume to be tested according to the set resolution, and acquiring weight data on the effective pole piece according to the data volume;
and putting the obtained weight data on the effective pole piece into an FFT algorithm to obtain frequency distribution and amplitude corresponding to the weight data on the pole piece, drawing a spectrogram of the piece to be detected, and determining the abrasion degree of the piece to be detected according to the spectrogram of the piece to be detected.
In one embodiment, the number of the primary weight data in the effective interval is equal to the product of a sampling frequency and the period of the part to be measured, and the sampling frequency is a frequency corresponding to a machine for collecting the original weight data.
In one embodiment, the amount of data is equal to the sampling frequency divided by the resolution.
In one embodiment, the wear detection method further includes setting a reference piece, wherein the reference piece is an element with a frequency higher than that of the piece to be detected in the coating machine, and performing mean value filtering on the original weight data on the pole piece through the reference piece; and removing head data and tail data of each data coating section on the pole piece after mean value filtering to obtain primary weight data on the pole piece.
In one embodiment, a mean-filtered window is calculated from the product of the period of the reference and the sampling frequency, and the raw weight data on the pole piece is mean-filtered according to the mean-filtered window.
In one embodiment, the effective interval segment is divided into N unit data segments, and the N unit data segments are sequentially labeled as a 1 st segment, a 2 nd segment, an..the (N-1) th segment, and an nth segment; sequentially obtaining corresponding unit data segments from the primary weight data on the pole piece according to the natural arrangement sequence of the N unit data segments; and splicing the acquired plurality of unit data segments according to a natural arrangement sequence by taking the N unit data segments as a period to form an effective interval segment, and splicing the acquired plurality of effective interval segments to form the effective pole piece.
In one embodiment, the resolution is not less than 0.03HZ.
In one embodiment, the amount of data is a power of 2 to M.
In one embodiment, the amount of data on the header data is 5% -27% of the amount of data on each coated segment with data, and the amount of data on the trailer data is 5% -27% of the amount of data on each coated segment with data.
In one embodiment, the method further comprises setting a comparison spectrogram, wherein the comparison spectrogram is obtained in an unworn state of the piece to be detected; the method for acquiring the contrast spectrogram is the same as the method for acquiring the spectrogram of the to-be-detected piece, and the wear degree of the to-be-detected piece is determined by comparing the spectrogram of the to-be-detected piece with the contrast spectrogram.
According to the abrasion detection method of the coating machine, the original weight data of the coated pole piece is obtained, and the original weight data of the pole piece is processed to obtain the primary weight data of the pole piece. And the head data and the tail data of each data coating section are removed because the head data and the tail data of each data coating section are obtained under the condition that the operation of a coating machine is unstable, so that the accuracy of the abrasion detection of the piece to be detected is conveniently ensured. And acquiring the frequency and the period of the to-be-detected piece on the coating machine, carrying out period analysis on the to-be-detected piece, and searching a plurality of effective interval sections in the primary weight data on the pole piece. And the effective interval section does not include data in which the primary weight data is zero. And splicing a plurality of effective interval sections on the pole piece together to form the effective pole piece. Because the spectrogram of the part to be measured is obtained through the FFT algorithm, and the FFT algorithm requires continuous data to be imported, the effective interval section comprising the primary weight data of zero is removed, so that the primary weight data on the effective pole piece are all continuous data. For the FFT algorithm, the more the complete period is, the better the accuracy is, and the frequency accuracy of the piece to be tested can be ensured. Through the disassembly and assembly of the primary weight data on the pole piece, more effective interval sections can be obtained, namely more complete cycles are obtained, and the abrasion detection accuracy of the piece to be detected is guaranteed. And finally, putting the obtained weight data on the effective pole piece into an FFT algorithm to obtain frequency distribution and amplitude corresponding to the weight data on the pole piece, drawing a spectrogram of the to-be-measured piece, and determining the abrasion degree of the to-be-measured piece according to the spectrogram of the to-be-measured piece. By adopting the wear detection method designed by the application, the wear degree of the piece to be detected can be rapidly and efficiently determined through the spectrogram of the piece to be detected, and the wear detection efficiency of the piece to be detected is improved. And the method for determining the abrasion degree of the to-be-detected piece through the spectrogram can reduce the test precision requirement of the detection instrument.
Drawings
FIG. 1 is a schematic diagram of a method for detecting wear of a coater according to one embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a method for detecting wear of a coater according to another embodiment of the present disclosure;
FIG. 3 is a graph of raw weight data for a coated pole piece when neither the screw pump nor the backing roll are damaged;
FIG. 4 is a graph of the spectrum obtained in the unworn state of the screw pump of FIG. 3;
FIG. 5 is a spectrum diagram of a screw pump in example 1;
FIG. 6 is a graph of raw weight data for a coated pole piece with a damaged backing roll of the screw pump undamaged;
FIG. 7 is a spectrum of the damaged screw pump of FIG. 6;
FIG. 8 is a spectrum diagram of a back roll in example 2;
FIG. 9 is a graph of a spectrum of a known damaged backing roll;
FIG. 10 is a graph of the spectrum obtained with the backing roll of FIG. 3 in an unworn state;
fig. 11 is a spectrum diagram of the back roller obtained without the average filtering operation in example 2.
Detailed Description
The present application is described in further detail below with reference to the accompanying drawings by way of specific embodiments. Wherein like elements in different embodiments are numbered alike in association. In the following embodiments, numerous specific details are set forth in order to provide a better understanding of the present application. However, one skilled in the art will readily recognize that some of the features may be omitted, or replaced by other elements, materials, or methods in different situations. In some instances, some operations associated with the present application have not been shown or described in the specification to avoid obscuring the core portions of the present application, and may not be necessary for a person skilled in the art to describe in detail the relevant operations based on the description herein and the general knowledge of one skilled in the art.
Furthermore, the features, operations, or characteristics described in the specification may be combined in any suitable manner to form various embodiments, and the operational steps involved in the embodiments may be sequentially exchanged or adjusted in a manner apparent to those skilled in the art. Accordingly, the description and drawings are merely for clarity of describing certain embodiments and are not necessarily intended to imply a required composition and/or order.
The numbering of the components itself, e.g. "first", "second", etc., is used herein merely to distinguish between the described objects and does not have any sequential or technical meaning. The terms "coupled" and "connected," as used herein, are intended to encompass both direct and indirect coupling (coupling), unless otherwise indicated.
When the surface density measuring machine measures the pole piece after coating, the measured data is found to float beyond the normal range, the fault source is analyzed, fault factors which can be checked on the surface layer of the element in the coating machine, such as nozzle blockage and the like are eliminated, the problem is still not solved, and the deep analysis is started. The deep analysis is carried out by adopting the abrasion detection method of the coating machine, and the specific scheme is as follows.
As shown in fig. 1, in one embodiment, a method for detecting wear of a coater includes:
and acquiring original weight data on the coated pole piece.
The head data and tail data are removed from each data-bearing coating segment on the pole piece to obtain primary weight data on the pole piece.
And acquiring the frequency and period of the to-be-measured piece on the coating machine.
And carrying out periodic analysis by using the to-be-detected piece, searching a plurality of effective interval sections in the primary weight data on the pole piece, wherein the effective interval sections are the number of primary weight data which can completely reproduce one periodic fluctuation of the to-be-detected piece, and the primary weight data in the effective interval sections are not zero.
And splicing a plurality of effective interval sections obtained on the pole piece together to form the effective pole piece.
And calculating the data quantity to be tested according to the set resolution, and acquiring the weight data on the effective pole piece according to the data quantity.
And putting the obtained weight data on the effective pole piece into an FFT algorithm to obtain frequency distribution and amplitude corresponding to the weight data on the pole piece, drawing a spectrogram of the piece to be detected, and determining the wear degree of the piece to be detected according to the spectrogram of the piece to be detected.
The coating machine adopts gap coating, so that the coating sections of the pole pieces with data along the transmission direction of the back roller are distributed at intervals one by one, and gaps without coating exist between the adjacent coating sections with data. The weight data on the uncoated gap on the pole piece was zero. The primary weight data on the pole piece does not include the head data and the tail data of the data coating sections, but still includes the gaps between the adjacent data coating sections without coating, namely, the gaps in the primary weight data, including the weight data on the pole piece, are zero. If the primary weight data in the effective interval section is zero, the effective interval section becomes an ineffective interval section, and the effective interval section is eliminated. After the invalid section is removed, all the valid sections are spliced to form the valid pole piece.
The wear detection method (abbreviated as wear detection method) of the coating machine in the above embodiment is adopted to obtain the original weight data on the pole piece after coating, and the original weight data on the pole piece is processed to obtain the primary weight data on the pole piece. And the head data and the tail data of each data coating section are removed because the head data and the tail data are obtained under the condition that the operation of the coating machine is unstable (for example, the head data are in an acceleration stage of starting and the tail data are in a deceleration stage of ending), so that the accuracy of the abrasion detection of the to-be-detected part is conveniently ensured. And acquiring the frequency and the period of the to-be-detected piece on the coating machine, carrying out period analysis on the to-be-detected piece, and searching a plurality of effective interval sections in the primary weight data on the pole piece. And the effective interval section does not include data in which the primary weight data is zero. And splicing a plurality of effective interval sections on the pole piece together to form the effective pole piece. Because the spectrogram of the part to be measured is obtained through an FFT algorithm (fast Fourier transform algorithm), and the FFT algorithm can only be performed after continuous data is required to be imported, an effective interval section comprising zero primary weight data is removed, so that the primary weight data on the effective pole piece are all continuous data. For the FFT algorithm, the more the complete period is, the better the accuracy is, and the frequency accuracy of the piece to be tested can be ensured. Through the disassembly and assembly of the primary weight data on the pole piece, more effective interval sections can be obtained, namely more complete cycles are obtained, and the abrasion detection accuracy of the piece to be detected is guaranteed. And finally, putting the obtained weight data on the effective pole piece into an FFT algorithm to obtain frequency distribution and amplitude corresponding to the weight data on the pole piece, drawing a spectrogram of the to-be-measured piece, and determining the abrasion degree of the to-be-measured piece according to the spectrogram of the to-be-measured piece. By adopting the wear detection method designed by the application, the wear degree of the piece to be detected can be rapidly and efficiently determined through the spectrogram of the piece to be detected, and the wear detection efficiency of the piece to be detected is improved. And the method for determining the abrasion degree of the to-be-detected piece through the spectrogram can reduce the test precision requirement of the detection instrument.
Specifically, the number of primary weight data in the effective interval is equal to the product of the sampling frequency and the period of the to-be-detected piece, and the sampling frequency is the frequency corresponding to the machine for collecting the original weight data. The amount of data is equal to the sampling frequency divided by the resolution. The resolution is not lower than 0.03HZ, and based on the requirement of FFT algorithm, the data size is the power of 2M, and M is an integer. The data amount on the head data accounts for 5% -27% of the data amount on each data-bearing coating segment, and the data amount on the tail data accounts for 5% -27% of the data amount on each data-bearing coating segment. The amount of data on the header data is in the range of the amount of data on each segment with data coating, and the amount of data on the trailer data is in the range of the amount of data on each segment with data coating, as determined by the specific coating process and pole piece. For example, the amount of data on the header data is 7%, 9%, 12% or 17% of the amount of data on each segment with data, and the amount of data on the trailer data is 8%, 10%, 13% or 18% of the amount of data on each segment with data.
More preferably, the wear detection method further comprises setting a reference piece, wherein the reference piece is an element with a frequency higher than that of the piece to be detected in the coating machine, and carrying out mean value filtering on the original weight data on the pole piece through the reference piece. And removing head data and tail data of each data-containing coating section on the pole piece after the mean value filtration to obtain primary weight data on the pole piece. Specifically, a window of mean filtering is calculated through the product of the period of the reference piece and the sampling frequency, and the mean filtering is carried out on the original weight data on the pole piece according to the window of mean filtering. Through carrying out the mean value filtering to original weight data, can effectively filter high-frequency interference, be convenient for obtain the more accurate spectrogram of piece that awaits measuring to be convenient for carry out more accurate wearing and tearing analysis. If the high-frequency interference exists, the average value filtering is not carried out on the original weight data, and after the pole pieces are disassembled and assembled to obtain the effective pole pieces, the interference of other high frequencies is amplified, so that the spectrograms of the to-be-detected pieces are more irregularly distributed, and the abrasion detection analysis is not facilitated. For example, in addition to the part to be measured, three parts of the coater having frequencies higher than the part to be measured are known, and the highest frequency of the three parts can be used as a reference part to perform the mean value filtering operation.
When the FFT algorithm is used in the wear detection method, a large amount of data is required due to resolution or accuracy requirements. For the to-be-measured piece with lower frequency, the period is relatively larger, and the number of primary weight data which can completely reproduce one period fluctuation of the to-be-measured piece in the corresponding effective interval section is also larger. At this time, if the effective sections are directly spliced and combined, sufficient data cannot be obtained. Therefore, it is preferable that the effective interval section is divided into N unit data sections, and the N unit data sections are sequentially marked as 1 st section, 2 nd section, the (N-1) th section, and the nth section. And acquiring corresponding unit data segments from the primary weight data on the pole piece according to the natural arrangement sequence of the N unit data segments. And splicing the acquired plurality of unit data segments according to a natural arrangement sequence to form an effective interval segment by taking the N unit data segments as a period, and splicing the acquired plurality of effective interval segments to form an effective pole piece. Since the effective interval section does not include the data with the primary weight data being zero, each unit data section does not include the data with the primary weight data being zero. And if the unit data segment comprises data with zero primary weight data, the unit data segment is regarded as an invalid unit data segment, and the unit data segment is rejected. Through further periodically disassembling and assembling the effective interval sections, more useful effective interval sections can be obtained, and further the effective pole pieces formed by assembling the useful effective interval sections comprise enough weight data.
For a part to be measured determined in a coater, the larger the amplitude on the spectrum of the part to be measured is with the increase of the service time. If the amplitude corresponding to the frequency spectrogram of the to-be-detected piece is known to be undamaged (namely, in an undamaged state or when the to-be-detected piece is just put into use as a new element), the amplitude corresponding to the frequency of the to-be-detected piece in the frequency spectrogram of the to-be-detected piece obtained by the abrasion detection method can be directly compared with the amplitude in the undamaged frequency spectrogram of the to-be-detected piece. If the amplitude value phase difference is smaller, the abrasion degree of the to-be-tested piece tested by the method is lower, and if the amplitude value phase difference is larger, the abrasion degree of the to-be-tested piece tested by the method is higher.
If the abrasion degree of the to-be-detected piece is judged, no known underworn spectrogram of the to-be-detected piece is used for amplitude comparison, and the abrasion detection method further comprises the step of setting a comparison spectrogram which is obtained in an unworn state of the to-be-detected piece. The method for acquiring the reference spectrogram is the same as the method for acquiring the spectrogram of the to-be-measured piece, so that the description is omitted. And comparing the spectrogram of the to-be-detected piece with the comparison spectrogram to determine the abrasion degree of the to-be-detected piece.
The to-be-detected piece detected by the abrasion detection method can be a to-be-detected piece in an unworn state, for example, the to-be-detected piece which is newly used in the coating machine is subjected to abrasion detection, and the to-be-detected piece can also be a to-be-detected piece which is used on the coating machine for a period of time. When the service time of the to-be-measured piece is not known, the spectrogram of the to-be-measured piece obtained through the abrasion detection method is compared with the contrast spectrogram, and the actual service time of the to-be-measured piece on the coating machine can be reversely estimated. The abrasion detection method can detect abrasion of any element with frequency in the coating machine, for example, the abrasion detection is respectively carried out on a screw pump and a back roller on the coating machine. The abrasion detection method of the coating machine is specifically applied to the following examples. The test piece in example 1 is exemplified by a screw pump. The test piece in example 2 is exemplified by a back roller.
Example 1
As shown in fig. 1, a wear detection method of a coater includes:
step S11: and acquiring original weight data on the coated pole piece through laser fixed-point measurement. In addition to the laser spot measurement, raw weight data can also be obtained by an areal density meter, a thickness gauge, or the like. In this embodiment, taking laser fixed-point measurement as an example, when the original weight data is actually obtained, a plurality of original weight data distributed linearly in the length direction of the pole piece or along the transmission direction of the back roller are obtained according to a certain sampling frequency.
Step S12: the head data and tail data are removed from each data-bearing coating segment on the pole piece to obtain primary weight data on the pole piece. The amount of data on the header data is 10% of the amount of data on each coated segment with data, and the amount of data on the trailer data is 10% of the amount of data on each coated segment with data.
Step S13: the frequency and period of the part to be measured (screw pump) on the coater are obtained. Screw pulsation frequency (Hz) =pump rotation speed (r/min)/60(s), the reciprocal of the screw pump frequency is the screw pump period, and the pump speed 110r/min is taken as an example, the converted screw pump frequency is 1.83Hz, and the period is 0.54s.
Step S14: and (3) carrying out periodic analysis by using a piece to be detected (a screw pump), and searching a plurality of effective interval sections in the primary weight data on the pole piece. Specifically, the number of primary weight data in the effective interval is equal to the product of the sampling frequency and the period of the to-be-detected piece, and the sampling frequency is the frequency corresponding to the machine for collecting the original weight data. Taking 1000HZ as an example, the number of primary weight data in the effective interval is 1000×0.54=540, i.e. 540 continuous primary weight data form an effective interval.
Step S15: and splicing a plurality of effective interval sections obtained on the pole piece together to form the effective pole piece. The specific operation is that 540 primary weight data are taken as an effective interval section, a pole piece is equally divided into a plurality of effective interval sections, the effective interval section containing primary weight data of zero is taken as an ineffective interval section, and the effective interval section is removed. And after the invalid section is removed, splicing the obtained plurality of effective sections together along the length direction of the pole piece or the transmission direction of the back roller to form the effective pole piece.
Step S16: and calculating the data quantity to be tested according to the set resolution, and acquiring the weight data on the effective pole piece according to the data quantity. To be used forFor example, a resolution of 0.03HZ, a sampling frequency of 1000HZ, the amount of data is equal to the sampling frequency divided by the resolution. And because the data volume is the power of 2 to the power of M, M is an integer. So 2 M =1000/0.03. Calculated M is 15, and the data amount is 2 15 ＝32768。
Step S17: and putting the obtained 32768 weight data on the effective pole piece into an FFT algorithm to obtain frequency distribution and amplitude corresponding to the weight data on the pole piece, and drawing a spectrogram of the screw pump.
The abrasion detection method further comprises the step of setting a comparison spectrogram, wherein the comparison spectrogram is obtained in an unworn state of the screw pump. The method for obtaining the reference spectrogram is the same as the method for obtaining the spectrogram of the screw pump, and is also obtained by adopting the steps S11 to S17.
As shown in FIG. 3, the values on the abscissa represent the Y-th number, e.g., 13000 on the abscissa represent the 13000-th number and there are 12999 raw weight data before it, with the units on the ordinate being in mg/cm 2 As an example. The method for obtaining the effective pole piece corresponding to the screw pump in the unworn state is described with reference to fig. 3. Removing head data and tail data from each data-containing coating section in the original weight data distribution diagram, wherein gaps with zero weight data still exist between adjacent coating sections after the head data and the tail data are removed. And (3) according to the effective interval sections determined in the step (S14), combining the method of the step (S15), and splicing the plurality of finally obtained effective interval sections to form corresponding effective pole pieces in the unworn state of the screw pump.
The control spectrum is shown in fig. 4. Taking 10 weight data in 32768 weight data as an example, a spectrogram of the screw pump is obtained as shown in fig. 5, and the 10 weight data correspond to 10 different series of line diagrams in fig. 5. The spectrogram of the screw pump formed by the 10 weight data in fig. 5 has higher data repetition accuracy, which indicates that the spectrogram of the screw pump has high reliability, and is used for comparing with a comparison spectrogram to judge the abrasion degree of the screw pump. The frequency of the screw pump was 1.83HZ, so the amplitude corresponding to the 1.83HZ frequency in fig. 5 was compared with the amplitude corresponding to the 1.83HZ frequency in fig. 4. The corresponding amplitude in fig. 4 is less than 0.05, and the corresponding amplitude in fig. 5 is about higher than 1.2, which is obviously higher than the amplitude in fig. 4, which indicates that the abrasion degree of the screw pump detected in the embodiment 1 is more serious.
As shown in fig. 6, the original weight data profile of the coated pole piece is that the screw pump damaged the back roller and was not damaged. As shown in fig. 7, a spectrum of the damaged screw pump is obtained from the raw weight data distribution map of fig. 6. In fig. 7, the amplitude corresponding to the screw pump 1.83HZ frequency was found to be about 1.2. The accuracy of the wear detection method of the present application can be further verified by fig. 7.
Example 2
As shown in fig. 2, a wear detection method of a coater includes:
step S21: and acquiring original weight data on the coated pole piece through laser fixed-point measurement.
Step S22: the reference piece is set, and the reference piece is an element with the frequency higher than the frequency of the piece to be measured (back roller) in the coating machine. For example, the screw pump in example 1 was set as a reference, and the raw weight data on the pole piece was mean filtered by the screw pump. Specifically, a window of mean filtering is calculated by a product of a period of the screw pump and a sampling frequency of the laser fixed point measuring machine, the sampling frequency of the laser fixed point measuring machine is exemplified by 1000HZ, namely 0.54×1000=540, a data quantity 540 required by the screw pump is taken as the window of mean filtering, and the raw weight data on the pole piece is subjected to mean filtering according to the window of mean filtering, so that the influence of high frequency is effectively filtered.
Step S23: and removing head and tail data of each data coating section on the pole piece after the mean value filtration to obtain primary weight data on the pole piece. The amount of data on the header data is 10% of the amount of data on each coated segment with data, and the amount of data on the trailer data is 10% of the amount of data on each coated segment with data.
Step S24: the frequency and period of the part to be measured (back roll) on the coater are obtained. Frequency of back roll = coating speed (mm/s)/(back roll diameter (mm) ×3.14), with a back roll having a coating speed of 416.67mm/s and a diameter of 294.75mm as an example, the frequency of the back roll was calculated to be 0.45HZ, and the period was 2.222s.
Step S25: and (3) periodically analyzing by using a piece to be detected (a back roller) and searching a plurality of effective interval sections in the primary weight data on the pole piece. The number of primary weight data in the effective interval is equal to the product of the sampling frequency and the back roller period, and the number of primary weight data in the effective interval is 1000×2.222=2222, namely 2222 continuous primary weight data form an effective interval.
Step S26: because the frequency of the back roller is lower, namely the back roller rule needs more data to reproduce, if the pole pieces are split directly by using the effective interval sections formed by 22222 primary weight data, the number of the obtained effective interval sections is limited, and the data volume requirement of the back roller abrasion detection cannot be met. In this case, the effective section of the back roller needs to be disassembled and assembled further to make up enough cycles to meet the required data size. Specifically, the effective interval section is divided into 4 unit data sections, and the 4 unit data sections are marked as a 1 st section, a 2 nd section, a 3 rd section and a 4 th section in sequence. Segment 1 includes primary weight data from 1 st to 500 th, segment 2 includes primary weight data from 501 st to 1000 th, segment 3 includes primary weight data from 1001 st to 1600 th, and segment 4 includes primary weight data from 1601 th to 2222 nd. The total number of primary weight data of the 4 unit data segments is equal to the number of primary weight data contained in the effective interval segment. The components may be equally divided or unequal divided according to actual conditions.
Step S27: and acquiring a plurality of corresponding unit data segments from the primary weight data on the pole piece according to the natural arrangement sequence of the 4 unit data segments. For example, the pole pieces are sequentially divided along the length direction of the pole pieces according to the 1 st, 2 nd, 3 rd, 4 th, 1 st, 2 nd, 3 rd, and 4 th sections.
Step S28: and regarding the unit data segment containing the primary weight data of zero as an invalid data segment, and rejecting. After invalid data segments are removed, the rest unit data segments are combined into a period by 4 unit data segments formed according to a natural arrangement sequence, and the obtained 4 unit data segments are spliced according to the natural arrangement sequence to form an effective interval segment, namely the 4 unit data segments are spliced into the effective interval segment of a period according to the sequence of the 1 st segment, the 2 nd segment, the 3 rd segment and the 4 th segment. And then splicing the obtained effective interval sections to form an effective pole piece.
Taking three effective interval sections as an example, if the 1 st unit data section in the first effective interval section is an invalid data section, the 2 nd unit data section in the second effective interval section is an invalid data section, and the 3 rd unit data section in the third effective interval section is an invalid data section. If the three effective sections are directly taken for splicing, the three effective sections are regarded as invalid sections because the three effective sections all contain invalid data sections, and the effective pole pieces cannot be spliced when the three effective sections are equivalent to the invalid sections. If the three effective sections are respectively subjected to the operation of dividing the unit data sections, after invalid data sections are removed, the 1 st unit data section in the second effective section can be replaced and supplemented in the first effective section, and the 3 rd unit data section in the second effective section can be replaced and supplemented in the third effective section. Thus, at least two useful effective interval sections can be finally obtained, and the two effective interval sections can be spliced to form an effective pole piece.
As shown by the analysis, in step S28, although a plurality of complete effective interval sections cannot be found directly, a part of the complete effective interval sections can be found, so that a plurality of 1 st sections, a plurality of 2 nd sections, a plurality of 3 rd sections, and a plurality of 4 th sections can be found in the original effective interval sections. After enough sections 1, 2, 3 and 4 are found, the materials are integrated. And splicing a plurality of new effective interval sections according to the natural arrangement sequence of the 1 st section, the 2 nd section, the 3 rd section and the 4 th section, and finally splicing the plurality of new effective interval sections to obtain the effective pole piece. Although the plurality of unit data segments in the new effective interval segment may come from different places, the arrangement sequence of the 4 unit data segments in the analysis effective interval segment is not disturbed, and the use of the effective pole piece is not affected. One exemplary application in which 4 unit data segments are N unit data segments is not to be construed as limiting the present application.
Step S29: and calculating the data quantity to be tested according to the set resolution, and acquiring the weight data on the effective pole piece according to the data quantity. Taking a resolution of 0.03HZ, a sampling frequency of 1000HZ as an example, the amount of data is equal to the sampling frequency divided by the resolution. And because the data volume is the power of 2 to the power of M, M is an integer. So 2 M =1000/0.03. Calculated M is 15, and the data amount is 2 15 =32768. The resolution is set according to the actual requirement, for example, the resolution is set to be 0.015, and the corresponding data amount is 2 16 ＝65536。
Step S30: and putting the obtained 32768 weight data on the effective pole piece into an FFT algorithm to obtain frequency distribution and amplitude corresponding to the weight data on the pole piece, and drawing a spectrogram of the to-be-measured piece.
The abrasion detection method further comprises setting a comparison spectrogram, wherein the comparison spectrogram is shown in fig. 10 and is obtained in the state that the back roller is not abraded. The method for acquiring the reference spectrogram is the same as the method for acquiring the spectrogram of the back roller, and is also obtained by adopting the steps S21-S30.
Taking 10 weight data of 32768 weight data as an example, a spectrogram of the back roller is obtained as shown in fig. 8, and the 10 weight data corresponds to 10 different series of line diagrams in fig. 8. The spectrogram of the back roller formed by the 10 weight data in fig. 8 has higher data repetition accuracy, which indicates that the spectrogram of the back roller has high reliability, and is used for comparing with a comparison spectrogram to judge the abrasion degree of the back roller. Because the maximum range of the spectrum amplitude in fig. 8 is smaller than the maximum range of the spectrum amplitude in fig. 5, the fold line coincidence ratio of the 10 weight data of the spectrum in fig. 8 is relatively lower than that in fig. 5, but this does not affect the judgment of the abrasion degree of the back roller, so long as the coincidence ratio of the 10 fold lines at the corresponding frequency of the back roller is ensured.
According to the frequency of the back roller being 0.45HZ, as shown in fig. 10, the corresponding amplitude in the unworn state of the back roller is less than 0.1. As shown in fig. 9, when the back roller is worn and damaged, the amplitude of the back roller at the frequency of 0.45HZ is significantly higher than the corresponding amplitude of the back roller in the unworn state of the back roller. Correspondingly, as shown in fig. 8, the amplitude of the back roller, which is the piece to be measured, is also less than 0.1. Comparing the comparative spectrum of the backing roll of fig. 10 with the spectrum of the backing roll of fig. 8, it can be seen that the backing roll tested in example 2 is also approximately unworn.
As shown in fig. 11, the spectrum of the back roller obtained in example 2 without the mean value filtering operation is significantly more sharp corners in fig. 11 than in fig. 8, which is disadvantageous for the abrasion analysis of the back roller. It is necessary to perform averaging to exclude high frequency interference of components having relatively high frequencies.
According to the abrasion detection method of the coating machine, the original weight data on the coated pole piece is obtained through the machine (such as a laser fixed-point measuring machine), and the data are collected manually relatively, so that the consistency is good, and the accuracy and the efficiency are improved. Finally, a spectrogram of the piece to be detected is obtained through an FFT algorithm, the wear degree of the piece to be detected is analyzed according to the amplitude corresponding to the frequency of the piece to be detected, the precision requirement on a wear detection instrument can be reduced, and the piece to be detected can be subjected to depth detection. For the to-be-detected piece with relatively high frequency, the wear detection method shown in fig. 1 can be adopted, the validity of wear detection is ensured by removing the head and tail data of the data coating section on the pole piece, and meanwhile, the effective pole piece with continuous data is obtained by splicing the effective interval sections, so that the problem that the data on the gap coating pole piece cannot be analyzed by using the FFT algorithm intermittently is solved. For the to-be-detected part with relatively low frequency, the abrasion detection method shown in fig. 2 can be adopted, firstly, the mean filtering operation is creatively increased, the high-frequency interference of the relatively high-frequency element to the to-be-detected part is reduced, and the rapid and accurate analysis of the later spectrogram is facilitated. Secondly, for the problem of high data demand of the low-frequency to-be-detected pieces, the effective interval sections are creatively continuously disassembled and assembled to obtain more effective interval sections meeting the requirements, and further, enough data quantity is provided for researching the wear degree of the to-be-detected pieces. By adopting the abrasion detection method, the abrasion analysis of the to-be-detected piece can be efficiently and accurately carried out, and the detection method has the advantages of simplicity, easiness in operation and low cost, and even can simultaneously acquire the detection results of a plurality of to-be-detected pieces, such as the detection results of the screw pump and the back roller.
The foregoing description of the invention has been presented for purposes of illustration and description, and is not intended to be limiting. Several simple deductions, modifications or substitutions may also be made by a person skilled in the art to which the invention pertains, based on the idea of the invention.
Claims (10)
1. A method for detecting wear of a coater, comprising:
acquiring original weight data on the coated pole piece;
removing head data and tail data from each data-bearing coating segment on the pole piece to obtain primary weight data on the pole piece;
acquiring the frequency and period of a piece to be tested on a coating machine;
carrying out periodic analysis by the piece to be detected, and searching a plurality of effective interval sections in the primary weight data on the pole piece, wherein the effective interval sections are the number of the primary weight data which can completely reproduce one periodic fluctuation of the piece to be detected, and the primary weight data in the effective interval sections are not zero;
splicing a plurality of effective interval sections obtained on the pole piece together to form an effective pole piece;
calculating the data volume to be tested according to the set resolution, and acquiring weight data on the effective pole piece according to the data volume;
and putting the obtained weight data on the effective pole piece into an FFT algorithm to obtain frequency distribution and amplitude corresponding to the weight data on the pole piece, drawing a spectrogram of the piece to be detected, and determining the abrasion degree of the piece to be detected according to the spectrogram of the piece to be detected.
2. The method according to claim 1, wherein the number of the primary weight data in the effective interval is equal to a product of a sampling frequency corresponding to a machine that collects the raw weight data and the period of the part to be measured.
3. The method of detecting wear of a coater according to claim 2, wherein the data amount is equal to the sampling frequency divided by the resolution.
4. The method for detecting wear of a coater according to claim 2, further comprising setting a reference member which is an element of the coater having a frequency higher than that of the member to be detected, and average filtering the raw weight data on the pole piece by the reference member; and removing head data and tail data of each data coating section on the pole piece after mean value filtering to obtain primary weight data on the pole piece.
5. The method of detecting wear of a coater according to claim 4, wherein a window for mean filtering is calculated by a product of the period of the reference member and the sampling frequency, and the raw weight data on the pole piece is mean filtered according to the window for mean filtering.
6. The wear detection method of a coater according to claim 1, wherein the effective interval section is divided into N unit data sections, and N unit data sections are sequentially marked as 1 st section, 2 nd section, an..once again, an (N-1) th section, an nth section; sequentially obtaining corresponding unit data segments from the primary weight data on the pole piece according to the natural arrangement sequence of the N unit data segments: and splicing the acquired plurality of unit data segments according to a natural arrangement sequence by taking the N unit data segments as a period to form an effective interval segment, and splicing the acquired plurality of effective interval segments to form the effective pole piece.
7. The method for detecting wear of a coater according to claim 1, wherein the resolution is not lower than 0.03HZ.
8. The method for detecting wear of a coater according to claim 1, wherein the data amount is the power of 2M.
9. The method of claim 1, wherein the amount of data on the header data is 5% -27% of the amount of data on each of the coated segments with data, and the amount of data on the tail data is 5% -27% of the amount of data on each of the coated segments with data.
10. The method for detecting wear of a coater according to claim 1, further comprising setting a reference spectrogram, the reference spectrogram being a spectrogram obtained in a state where the member to be detected is not worn; the method for acquiring the contrast spectrogram is the same as the method for acquiring the spectrogram of the to-be-detected piece, and the wear degree of the to-be-detected piece is determined by comparing the spectrogram of the to-be-detected piece with the contrast spectrogram.
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