CN116412973A - Method, system and equipment for detecting tightness of flexible package seal - Google Patents
Method, system and equipment for detecting tightness of flexible package seal Download PDFInfo
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- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
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Abstract
The invention belongs to the technical field of detection, and particularly relates to a method, a system and equipment for detecting tightness of a flexible package seal. The method for detecting the sealing property of the soft package seal comprises the following steps: step S1, obtaining vibration signals of a soft package passing through rolling; s2, extracting the initial multiple groups of vibration signals and manufacturing standard signal samples; s3, preprocessing a standard signal sample and a signal to be detected; step S4, calculating a nonlinear similarity value and a spatial distance value of the preprocessed standard signal sample and the signal to be detected; s5, judging that the tightness of the soft package seal is qualified when the nonlinear similarity value is more than or equal to 0.84 and the space distance value is less than or equal to 0.90; otherwise, the test result is disqualified. The method is simple and easy to operate, has good adaptability, is based on a high-precision sensor, has better stability, higher precision and accurate data, and aims to realize high-efficiency, stable and rapid real-time qualification rate detection of flexible package products.
Description
Technical Field
The invention belongs to the technical field of detection of sealing performance of flexible package seals, and particularly relates to a method, a system and equipment for detecting the sealing performance of a flexible package seal.
Background
Along with the rapid development of economy, the consumption level of the public is obviously improved, the use of the flexible packaging bag occupies a large proportion in the whole industries of foods, medicines, agricultural products and the like in the process of purchasing commodities, so that the sealing performance of the flexible packaging bag seal is particularly important, the poor sealing performance of the flexible packaging bag is mainly caused by impurities, bubbles and the like at the sealing position in the heating moment in the heat sealing process, the quality and the use effect of products are seriously influenced by the poor sealing packaging, and at present, the commercial sealing performance detection method is mainly a sampling detection method such as a coloring penetration method, an air pressure detection method and the like, the real-time monitoring of the quality of the products cannot be realized, the efficiency is lower, the precision and the reliability are also to be improved, so that the method, the system and the equipment for the real-time detection of the sealing performance of the flexible packaging are very important.
Disclosure of Invention
The invention aims to provide a method, a system and equipment for detecting tightness of a soft package seal.
In order to solve the technical problems, the invention provides a method for detecting the tightness of a soft package seal, which comprises the following steps:
s1, controlling a vibration sensor to receive signals according to the condition that an ultrasonic ranging sensor monitors the up-down displacement of a rolling cylinder, and determining a threshold value for starting and receiving the vibration sensor according to the installation position of the ultrasonic sensor; when the current value of the ultrasonic ranging sensor is smaller than the threshold value, the vibration sensor starts to receive the vibration signal of the roller; when the vibration sensor receives signals and the current value of the ultrasonic ranging sensor is larger than or equal to a threshold value, the vibration sensor stops receiving signals, and vibration signal acquisition is completed;
s2, extracting initial ten groups of vibration signal data, and storing the data in a matrix format of 10xN (N is the data length); after the maximum value and the minimum value of each column of data are removed from the sample array, sequentially carrying out average value processing on each column of data to obtain a standard sample template X;
s3, carrying out smoothing treatment on the standard signal sample and the signal to be detected so as to remove abnormal points in the standard signal sample and the signal to be detected; carrying out wavelet denoising treatment on the standard signal sample and the signal to be detected after the smoothing treatment to remove noise points and interference points in the standard signal sample and the signal to be detected, carrying out normalization treatment on the standard signal sample and the signal to be detected after the wavelet denoising treatment to eliminate the adverse effect of the singular sample and optimize parameters at the same time, and reducing the calculated amount;
s4, calculating a nonlinear similarity value and a spatial distance value of the preprocessed standard signal sample and the signal to be detected;
s5, judging that the tightness of the soft package seal is qualified when the nonlinear similarity value is more than or equal to 0.84 and the space distance value is less than or equal to 0.90; otherwise, the test result is disqualified.
In a preferred embodiment, the present invention may be further configured such that the expression of the element included in the vector X is:
the k-th value of the i-th column of the sample matrix is expressed in +.>
Representing the sample matrix column i data.
In a preferred embodiment, the present invention is further configured such that the length of the standard signal sample and the signal to be detected is N, the smoothing method used is a five-point three-time smoothing method, and the input sequence
Outputting the sequence +.>
Wherein->
The expression of (2) is:
in the middle of
Is the sequence->
The calculation formula is y (i) when i is between (2, N-1) and the ith data point included in the data.
The present invention may be further configured in a preferred embodiment, the wavelet denoising includes three steps of wavelet decomposition, thresholding and wavelet inverse transformation; the wavelet decomposition adopts a Malet algorithm, and input data is a smooth processed sequence
The orthogonal wavelet transform decomposition expression is: />
/>
In (1) the->
，/>
For the scale factor>
Is a wavelet coefficient; h. g is a pair of quadrature mirror filter banks (QMF); j is the number of decomposition layers, wherein the number of decomposition layers is 5; n is the number of sampling points;
the wavelet coefficient obtained by decomposition is subjected to threshold processing to remove irrelevant parameters such as noise points, and the threshold processing method adopts a hard threshold method, and the expression is as follows:
wherein, the threshold t is 2.5;
performing wavelet inverse transformation on the wavelet coefficient subjected to the threshold processing, wherein the expression of the reconstruction process is as follows:
in (1) the->
For the scale factor>
Is a wavelet coefficient; j is the number of decomposition layers, wherein the number of decomposition layers is 5; h. g is a pair of quadrature mirror filter banks (QMF);
the de-noised vibration signal is obtained after wavelet reconstruction;
carrying out normalization processing on the denoised standard signal sample and the signal to be detected, wherein the normalization adopts a Z-score normalization method, and the expression is as follows:
wherein mu is the average value of all vibration signal sample data, and sigma is the standard deviation of all vibration signal sample data; x is a selected vibration signal sample data point;
and after normalization treatment, obtaining a standard signal sample and a signal to be detected after pretreatment.
In a preferred embodiment, the calculating the nonlinear similarity value between the preprocessed standard signal sample and the signal to be detected in S4 may further include:
s401, setting a pre-processed standard signal sample as X, setting a pre-processed signal to be detected as Y, and calculating a cross-correlation coefficient of the pre-processed standard signal sample and the pre-processed signal to be detected as Y, wherein the formula is as follows:
in (1) the->
Is the covariance between X and Y, +.>
Variance of X>
Variance of Y; the cross-correlation coefficient has a value range of [ -1,1]Between, if->
Then the two sets of vibration signals are positively correlated, if +.>
The two sets of vibration signals are uncorrelated, if +.>
The two sets of vibration signals are inversely related; uncorrelated here means that there is no linear relationship between the two sets of signals, other relationships cannot be excluded;
s402, calculating a mutual information coefficient according to a standard signal sample X and a signal to be detected Y, wherein the formula is as follows:
in (1) the->
For joint probability density function, +.>
And->
As a marginal probability density function; the mutual information coefficient ranges from +.>
The larger the value of the mutual information coefficient is, the higher the correlation degree of the two groups of data is represented;
s403, carrying out normalization processing on the calculated mutual information coefficient, and further quantifying a correlation index, wherein the formula is as follows:
in (1) the->
Is the normalization result of mutual information, and the value range is from +.>
Normalized to
Unifying measurement indexes and->
Meanwhile, the linear relation and the nonlinear relation between the two groups of vibration signals are included, and compared with the cross correlation coefficient, the mutual information measurement index is wider;
s404, calculating the nonlinear correlation degree of the standard signal sample X and the signal to be detected Y according to the cross-correlation coefficient and the normalized mutual information coefficient, wherein the formula is as follows
In (1) the->
Normalized results for mutual information, ++>
；/>
The direct nonlinear relation of the vibration signals is characterized, and the method can be used for indicating whether nonlinear relation or nonlinear correlation degree exists between variables, wherein the larger the value is, the higher the nonlinear correlation degree is represented;
s405, according to the method for calculating the nonlinear correlation, the nonlinear correlation among the initial ten groups of sample data is obtained, the lowest correlation minus the error value is taken as a detection threshold of the nonlinear correlation, and the error value is taken as 0.02;
s406, adopting a Marshall distance as a calculation method of a space distance value, judging the similarity of two groups of vibration signals from a vector space angle, and enabling quality detection to be more accurate through multi-index judgment, wherein the expression is as follows:
wherein x and y are vectors of dimensions of the standard signal sample and the signal to be detected respectively,
a covariance matrix of x and y;
s407, according to the method for calculating the space distance, the space distance between the first ten groups of sample data is obtained, the lowest Markov distance is taken to be used as a detection threshold value of the space distance value after subtracting the error value, and the error value is taken to be 0.04.
In still another aspect, the present invention further provides a system for detecting tightness of a flexible package seal, including:
the vibration signal acquisition module receives the displacement condition of the roller through the ultrasonic ranging sensor, receives the vibration signal of the roller through the vibration sensor, and determines a threshold value for starting the vibration sensor to receive according to the installation position of the ultrasonic sensor;
the vibration signal preprocessing module is used for extracting an initial plurality of groups of signals to manufacture standard signal samples of vibration signals, obtaining the standard signal samples and the signal samples to be detected of the vibration signals, and carrying out smoothing, denoising and normalization preprocessing on the two signal samples;
the soft package tightness judging module is used for calculating the nonlinear similarity and the spatial distance value of the preprocessed standard signal sample and the signal sample to be detected and judging whether the soft package tightness is qualified or not.
In still another aspect, the present invention further provides a device for detecting tightness of a flexible package seal, including: the device comprises a conveyor belt for transporting soft packaging bags, wherein at least 3 groups of rollers which are equidistantly arranged are arranged at the inlet of the conveyor belt, brackets are arranged at two sides of the middle section of the conveyor belt, test rollers are arranged on the brackets, vibration amplitude vibration sensors are arranged at two shaft ends of each test roller and are connected and fixed by an ultrasonic reflection plane, vibration data are collected, an ultrasonic ranging sensor is connected above the vibration amplitude vibration sensors and used for monitoring the up-down displacement of the vibration amplitude vibration sensors, and the receiving time point of vibration signals is controlled; the amplitude vibration sensor and the ultrasonic ranging sensor are electrically connected with the industrial personal computer, so that real-time communication between the sensor and the upper computer is realized, and meanwhile, the acquired signals are processed through the industrial personal computer, and the real-time display of the quality of the flexible package is performed on the display.
In a preferred embodiment, the invention can be further configured that springs are arranged at two ends of the roller, and the roller is supported to move up and down through the springs.
Compared with the prior art, the method for detecting the sealing property of the flexible package has the beneficial effects that the signal acquisition technology of the amplitude vibration sensor is utilized to convert the sealing property of the flexible package into a digital vibration signal, the sealing state of the flexible package is intuitively displayed by waveforms, the use of the templates is well simplified by improving the implementation mode of the traditional algorithm and combining the waveform sample templates, the calculated amount of the algorithm is reduced, and meanwhile, interference signals caused by external factors such as machine vibration are solved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention.
In order to make the above objects, advantages and features more clear and intuitive, preferred embodiments of the present invention and the related drawings are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the prior art, the following description of the related drawings of the embodiments of the present invention will be apparent, in which the drawings described below are some examples of the present invention and other drawings may be made by those skilled in the art without inventive work.
Fig. 1 is a schematic flow chart of an embodiment of a method for detecting tightness of a flexible package seal.
Fig. 2 is a schematic diagram of a device for detecting tightness of a flexible package seal according to the present invention.
FIG. 3 is a diagram of a qualified sample of a leak tightness waveform in accordance with an embodiment of the present invention.
Fig. 4 is a diagram of a seal waveform inspection failure pattern according to an embodiment of the present invention.
In the figure: 1. a roller; 2. a spring; 3. a conveyor belt; 4. an amplitude vibration sensor; 5. an ultrasonic ranging sensor; 6. a display; 7. an ultrasonic reflection plane; 8. an industrial personal computer; 9. soft packaging bags; 10. and (3) a bracket.
Detailed Description
For more clearly illustrating the objects, technical solutions and advantages of the embodiments of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. It is apparent that the examples described represent only some examples of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 2, the soft package closure sealability detection device comprises a conveyor belt 3 for transporting soft package bags 9; three equidistant cylinders 1 used for leveling pretreatment to the flexible packaging bag 9, a bracket 10 used for fixing the cylinders 1, a spring 2 used for supporting the cylinders 1 to move up and down, an amplitude vibration sensor 4 installed at the shaft end of the cylinders 1 and connected and fixed by an ultrasonic reflection plane 7, vibration data acquisition, an ultrasonic ranging sensor 5 installed above the amplitude vibration sensor 4 and used for monitoring the up-down displacement of the amplitude vibration sensor 4, controlling the receiving time point of vibration signals, wherein the amplitude vibration sensor 4 and the ultrasonic ranging sensor 5 are directly connected with an industrial personal computer 8 through an RS485 communication interface, realizing the real-time communication of the sensors and the upper computer, processing the acquired signals through the industrial personal computer 8 and displaying the quality of the flexible packaging on a display 6 in real time.
As shown in fig. 1, 3 and 4, there is provided a method for detecting sealability of a flexible package seal, comprising:
s1, controlling a vibration sensor to receive signals according to the condition that an ultrasonic ranging sensor monitors the up-down displacement of a rolling cylinder, and determining a threshold value for starting and receiving the vibration sensor according to the installation position of the ultrasonic sensor; when the current value of the ultrasonic ranging sensor is smaller than the threshold value, the vibration sensor starts to receive the vibration signal of the roller; when the vibration sensor receives signals and the current value of the ultrasonic ranging sensor is larger than or equal to a threshold value, the vibration sensor stops receiving signals, and vibration signal acquisition is completed;
s2, extracting initial ten groups of vibration signal data, and storing the data in a matrix format of 10xN (N is the data length); after the maximum value and the minimum value of each column of data are removed from the sample array, sequentially carrying out average value processing on each column of data to obtain a standard sample template X;
s3, carrying out smoothing treatment on the standard signal sample and the signal to be detected so as to remove abnormal points in the standard signal sample and the signal to be detected; carrying out wavelet denoising treatment on the standard signal sample and the signal to be detected after the smoothing treatment to remove noise points and interference points in the standard signal sample and the signal to be detected, carrying out normalization treatment on the standard signal sample and the signal to be detected after the wavelet denoising treatment to eliminate the adverse effect of the singular sample and optimize parameters at the same time, and reducing the calculated amount;
s4, calculating a nonlinear similarity value and a spatial distance value of the preprocessed standard signal sample and the signal to be detected;
s5, judging that the tightness of the soft package seal is qualified when the nonlinear similarity value is more than or equal to 0.84 and the space distance value is less than or equal to 0.90; otherwise, the test result is disqualified.
In the embodiment, the tightness of the flexible package is converted into the vibration signal in a digital form by utilizing the vibration sensor signal acquisition technology, the sealing state of the flexible package is intuitively displayed by using waveforms, the use of the templates is well simplified by improving the implementation mode of the traditional algorithm and combining the waveform sample templates, the calculated amount of the algorithm is reduced, meanwhile, the interference signals caused by external factors such as machine vibration and the like are solved, the whole flow is simpler and more convenient, the adaptability is strong, the efficiency is high, and the aim of carrying out high-precision and high-efficiency real-time quality monitoring on the flexible package product is fulfilled.
In an embodiment, the expression of the element contained in the vector X is:
in->
The kth value representing the ith column of the sample matrix,/->
Representing the sample matrix column i data.
The length of the standard signal sample and the signal to be detected is N, the smoothing method is five-point three-time smoothing method, and the input sequence
Outputting the sequence +.>
Wherein->
The expression of (2) is:
in the middle of
Is the sequence->
The calculation formula is y (i) when i is between (2, N-1) and the ith data point included in the data.
The wavelet denoising comprises three steps of wavelet decomposition, threshold processing and wavelet inverse transformation; the wavelet decomposition adopts a Malet algorithm, and input data is a smooth processed sequence
The orthogonal wavelet transform decomposition expression is: />
In (1) the->
，/>
For the scale factor>
Is a wavelet coefficient; h. g is a pair of quadrature mirror filter banks (QMF); j is the number of decomposition layers, wherein the number of decomposition layers is 5; n is the number of sampling points;
the wavelet coefficient obtained by decomposition is subjected to threshold processing to remove irrelevant parameters such as noise points, and the threshold processing method adopts a hard threshold method, and the expression is as follows:
wherein, the threshold t is generally 2.5;
performing wavelet inverse transformation on the wavelet coefficient subjected to the threshold processing, wherein the expression of the reconstruction process is as follows:
in (1) the->
For the scale factor>
Is a wavelet coefficient; j is the number of decomposition layers, wherein the number of decomposition layers is 5; h. g is a pair of quadrature mirror filter banks (QMF);
the de-noised vibration signal is obtained after wavelet reconstruction;
carrying out normalization processing on the denoised standard signal sample and the signal to be detected, wherein the normalization adopts a Z-score normalization method, and the expression is as follows:
wherein mu is the average value of all vibration signal sample data, and sigma is the standard deviation of all vibration signal sample data; x is a selected vibration signal sample data point;
after normalization treatment, a standard signal sample and a signal to be detected after pretreatment are obtained;
normalizing the denoised standard signal sample and the signal to be detected to eliminate the adverse effect of the singular sample, optimize parameters, reduce calculation amount, and normalize by adopting a Z-score normalization method, wherein the expression of the Z-score normalization method is thatThe formula is:
wherein mu is the average value of all vibration signal sample data, and sigma is the standard deviation of all vibration signal sample data; x is a selected vibration signal sample data point;
and after normalization treatment, obtaining a standard signal sample and a signal to be detected after pretreatment.
The step S4 of calculating the nonlinear similarity value between the preprocessed standard signal sample and the signal to be detected comprises the following steps:
s401, setting a pre-processed standard signal sample as X, setting a pre-processed signal to be detected as Y, and calculating a cross-correlation coefficient of the pre-processed standard signal sample and the pre-processed signal to be detected as Y, wherein the formula is as follows:
in (1) the->
Is the covariance between X and Y, +.>
Variance of X>
Variance of Y; the cross-correlation coefficient has a value range of [ -1,1]Between, if->
Then the two sets of vibration signals are positively correlated, if +.>
The two sets of vibration signals are uncorrelated, if +.>
The two sets of vibration signals are inversely related; uncorrelated here means that there is no linear relationship between the two sets of signals, other relationships cannot be excluded;
s402, calculating a mutual information coefficient according to a standard signal sample X and a signal to be detected Y, wherein the formula is as follows:
in (1) the->
For joint probability density function, +.>
And->
As a marginal probability density function; the mutual information coefficient ranges from +.>
The larger the value of the mutual information coefficient is, the higher the correlation degree of the two groups of data is represented;
s403, carrying out normalization processing on the calculated mutual information coefficient, and further quantifying a correlation index, wherein the formula is as follows:
in (1) the->
Is the normalization result of mutual information, and the value range is from +.>
Normalized to
Unifying measurement indexes and->
Meanwhile, the linear relation and the nonlinear relation between the two groups of vibration signals are included, and compared with the cross correlation coefficient, the mutual information measurement index is wider;
s404, calculating the nonlinear correlation degree of the standard signal sample X and the signal to be detected Y according to the cross-correlation coefficient and the normalized mutual information coefficient, wherein the formula is as follows
In (1) the->
Normalized results for mutual information, ++>
；/>
The direct nonlinear relation of the vibration signals is characterized, and the method can be used for indicating whether nonlinear relation or nonlinear correlation degree exists between variables, wherein the larger the value is, the higher the nonlinear correlation degree is represented;
s405, according to the method for calculating the nonlinear correlation, the nonlinear correlation among the initial ten groups of sample data is obtained, the lowest correlation minus the error value is taken as a detection threshold of the nonlinear correlation, and the error value is taken as 0.02;
s406, adopting a Marshall distance as a calculation method of a space distance value, judging the similarity of two groups of vibration signals from a vector space angle, and enabling quality detection to be more accurate through multi-index judgment, wherein the expression is as follows:
wherein x and y are vectors of dimensions of the standard signal sample and the signal to be detected respectively,
a covariance matrix of x and y;
s407, according to the method for calculating the space distance, the space distance between the first ten groups of sample data is obtained, the lowest Markov distance is taken to be used as a detection threshold value of the space distance value after subtracting the error value, and the error value is taken to be 0.04.
The following list is an optional implementation procedure in an application scenario:
firstly, the speeds of a roller and a conveyor belt are adjusted according to the width of a soft packaging bag, so that the time for the soft packaging bag to pass through the roller to be detected is ensured to be about one second, and meanwhile, the rotating speed of the roller is ensured to be the same as the speed of the conveyor belt;
when the flexible packaging bag passes through the roller to be detected, the roller moves upwards and instantly the ultrasonic ranging sensor monitors the displacement of the roller, the vibration sensor is controlled to automatically receive vibration signals, the acquired first ten groups of vibration signals are automatically stored, standard signal samples are manufactured, and the standard signal samples are stored as templates;
inputting the template into a processor, preprocessing the template serving as a matching sample with a vibration signal acquired next to realize algorithm matching, realizing soft package sealing quality detection, and finally giving out qualified and unqualified product quality information.
On the basis of the soft package tightness detection method, the embodiment provides a soft package tightness detection system, which comprises the following components:
the vibration signal acquisition module receives the displacement condition of the roller through the ultrasonic ranging sensor, receives the vibration signal of the roller through the vibration sensor, and determines a threshold value for starting the vibration sensor to receive according to the installation position of the ultrasonic sensor;
the vibration signal preprocessing module is used for extracting an initial plurality of groups of signals to manufacture standard signal samples of vibration signals, obtaining the standard signal samples and the signal samples to be detected of the vibration signals, and carrying out smoothing, denoising and normalization preprocessing on the two signal samples;
the soft package tightness judging module is used for calculating the nonlinear similarity and the spatial distance value of the preprocessed standard signal sample and the signal sample to be detected and judging whether the soft package tightness is qualified or not.
In summary, the method for detecting the sealing tightness of the flexible package converts the sealing tightness of the flexible package into a digital vibration signal by using a vibration sensor signal acquisition technology, intuitively displays the sealing state of the flexible package by using waveforms, well simplifies the use of templates by combining with waveform sample templates through improving the implementation mode of the traditional algorithm, reduces the calculated amount of the algorithm, simultaneously solves the interference signals caused by external factors such as machine vibration, and the like, has simpler and more convenient overall process, strong adaptability and high efficiency, and aims to realize high-precision and high-efficiency real-time quality monitoring of the flexible package product.
According to the method for detecting the tightness of the soft package seal, provided by the invention, the influence of uneven distribution of products in the soft package on the acquisition of vibration signals is considered, and the soft package is subjected to leveling operation by a preprocessing device before the vibration signals are acquired, so that the error is reduced; secondly, noise interferes with the vibration signal, smoothing, wavelet filtering and normalization processing are carried out on the vibration signal, so that the interference of external factors on the signal is eliminated as much as possible while the signal characteristics are guaranteed, and the accuracy of algorithm detection is improved; the designed processor can realize automatic detection of the tightness of the flexible package, and improves the detection efficiency.
In the several embodiments provided in the present application, it is obvious that the disclosed method, system and apparatus may be implemented in other ways, and are not limited to the apparatus described above. For example, some of the steps depicted in the flowcharts of the detection methods in the figures may be performed simultaneously, or the order of steps performed may be altered, as may be desired for different functional situations. Also, each block shown in the flowcharts may be implemented by a dedicated hardware system for performing the relevant functions or actions, or by a computer program collocated with hardware.
If implemented as a software functional module, and sold or used as a separate product, the system may be stored via a readable storage medium. In view of this, the technical solution of the present invention may be essentially or a part of the technical solution thereof as a software product, which includes several instructions to make a computer device (may be a personal computer, a server, or a network device) implement all or part of the methods described in the embodiments of the present invention, where the storage medium includes: a U-disk, a removable hard disk, a RAM, a ROM, an optical disk, or the like, which can store a program.
With the above-described preferred embodiments according to the present invention as an illustration, the above-described descriptions can be used by persons skilled in the relevant art to make various changes and modifications without departing from the scope of the technical idea of the present invention. The technical scope of the present invention is not limited to the description, but must be determined according to the scope of claims.
Claims (8)
1. The method for detecting the tightness of the seal of the flexible package is characterized by comprising the following steps of:
s1, controlling a vibration sensor to receive signals according to the condition that an ultrasonic ranging sensor monitors the up-down displacement of a rolling cylinder, and determining a threshold value for starting and receiving the vibration sensor according to the installation position of the ultrasonic sensor; when the current value of the ultrasonic ranging sensor is smaller than the threshold value, the vibration sensor starts to receive the vibration signal of the roller; when the vibration sensor receives signals and the current value of the ultrasonic ranging sensor is larger than or equal to a threshold value, the vibration sensor stops receiving signals, and vibration signal acquisition is completed;
s2, extracting initial ten groups of vibration signal data, and storing the data in a matrix format of 10xN (N is the data length); after the maximum value and the minimum value of each column of data are removed from the sample array, sequentially carrying out average value processing on each column of data to obtain a standard sample template X;
s3, carrying out smoothing treatment on the standard signal sample and the signal to be detected so as to remove abnormal points in the standard signal sample and the signal to be detected; carrying out wavelet denoising treatment on the standard signal sample and the signal to be detected after the smoothing treatment to remove noise points and interference points in the standard signal sample and the signal to be detected, carrying out normalization treatment on the standard signal sample and the signal to be detected after the wavelet denoising treatment to eliminate the adverse effect of the singular sample and optimize parameters at the same time, and reducing the calculated amount;
s4, calculating a nonlinear similarity value and a spatial distance value of the preprocessed standard signal sample and the signal to be detected;
s5, judging that the tightness of the soft package seal is qualified when the nonlinear similarity value is more than or equal to 0.84 and the space distance value is less than or equal to 0.90; otherwise, the test result is disqualified.
2. The method for detecting sealability of a flexible package seal according to claim 1, wherein the expression of the element contained in the standard sample template X is:
the k-th value of the i-th column of the sample matrix is expressed in +.>
Representing the sample matrix column i data.
3. The method for detecting tightness of flexible package seal according to claim 2, wherein the length of the signal of the standard signal sample and the signal to be detected is N, the smoothing method used is five-point three-time smoothing method, and the sequence is input
Outputting the sequence +.>
Wherein->
The expression of (2) is:
in the middle of
Is the sequence->
The calculation formula is y (i) when i is between (2, N-1) and the ith data point included in the data.
4. The method for detecting tightness of a flexible package seal according to claim 3, wherein the wavelet denoising comprises three steps of wavelet decomposition, thresholding and wavelet inverse transformation; the wavelet decomposition adopts a Malet algorithm, and input data is a smooth processed sequence
The orthogonal wavelet transform decomposition expression is: />
In the method, in the process of the invention,
，/>
for the scale factor>
Is a wavelet coefficient; h. g is a pair of quadrature mirror filter banks (QMF); j is the number of decomposition layers, wherein the number of decomposition layers is 5; n is the number of sampling points;
the wavelet coefficient obtained by decomposition is subjected to threshold processing to remove irrelevant parameters such as noise points, and the threshold processing method adopts a hard threshold method, and the expression is as follows:
wherein, the threshold t is 2.5;
performing wavelet inverse transformation on the wavelet coefficient subjected to the threshold processing, wherein the expression of the reconstruction process is as follows:
in (1) the->
For the scale factor>
Is a wavelet coefficient; j is the number of decomposition layers, wherein the number of decomposition layers is 5; h. g is a pair of quadrature mirror filter banks (QMF);
the de-noised vibration signal is obtained after wavelet reconstruction;
carrying out normalization processing on the denoised standard signal sample and the signal to be detected, wherein the normalization adopts a Z-score normalization method, and the expression is as follows:
wherein mu is the average value of all vibration signal sample data, and sigma is the standard deviation of all vibration signal sample data; x is a selected vibration signal sample data point;
and after normalization treatment, obtaining a standard signal sample and a signal to be detected after pretreatment.
5. The method for detecting tightness of a flexible package seal according to claim 1 or 4, wherein the calculating a nonlinear similarity value between the preprocessed standard signal sample and the signal to be detected in S4 includes:
s401, setting a pre-processed standard signal sample as X, setting a pre-processed signal to be detected as Y, and calculating a cross-correlation coefficient of the pre-processed standard signal sample and the pre-processed signal to be detected as Y, wherein the formula is as follows:
in (1) the->
Is the covariance between X and Y, +.>
Variance of X>
Variance of Y; the cross-correlation coefficient has a value range of [ -1,1]Between, if->
Then the two sets of vibration signals are positively correlated, if +.>
The two sets of vibration signals are uncorrelated, if +.>
The two sets of vibration signals are inversely related; uncorrelated here means that there is no linear relationship between the two sets of signals, other relationships cannot be excludedTying;
s402, calculating a mutual information coefficient according to a standard signal sample X and a signal to be detected Y, wherein the formula is as follows:
in (1) the->
For joint probability density function, +.>
And->
As a marginal probability density function; the mutual information coefficient ranges from +.>
The larger the value of the mutual information coefficient is, the higher the correlation degree of the two groups of data is represented;
s403, carrying out normalization processing on the calculated mutual information coefficient, and further quantifying a correlation index, wherein the formula is as follows:
in (1) the->
Is the normalization result of mutual information, and the value range is from +.>
Normalized to->
Unifying measurement indexes and->
Meanwhile, the linear relation and the nonlinear relation between the two groups of vibration signals are included, and compared with the cross correlation coefficient, the mutual information measurement index is wider;
s404, calculating the nonlinear correlation degree of the standard signal sample X and the signal to be detected Y according to the cross-correlation coefficient and the normalized mutual information coefficient, wherein the formula is as follows
In (1) the->
Normalized results for mutual information, ++>
；/>
The direct nonlinear relation of the vibration signals is characterized, and the method can be used for indicating whether nonlinear relation or nonlinear correlation degree exists between variables, wherein the larger the value is, the higher the nonlinear correlation degree is represented;
s405, according to the method for calculating the nonlinear correlation, the nonlinear correlation among the initial ten groups of sample data is obtained, the lowest correlation minus the error value is taken as a detection threshold of the nonlinear correlation, and the error value is taken as 0.02;
s406, adopting a Marshall distance as a calculation method of a space distance value, judging the similarity of two groups of vibration signals from a vector space angle, and enabling quality detection to be more accurate through multi-index judgment, wherein the expression is as follows:
wherein x and y are vectors of dimensions of the standard signal sample and the signal to be detected, respectively, < >>
A covariance matrix of x and y;
s407, according to the method for calculating the space distance, the space distance between the first ten groups of sample data is obtained, the lowest Markov distance is taken to be used as a detection threshold value of the space distance value after subtracting the error value, and the error value is taken to be 0.04.
6. A flexible package closure sealability test system employing the test method of any one of claims 1-5, comprising:
the vibration signal acquisition module receives the displacement condition of the roller through the ultrasonic ranging sensor, receives the vibration signal of the roller through the vibration sensor, and determines a threshold value for starting the vibration sensor to receive according to the installation position of the ultrasonic sensor;
the vibration signal preprocessing module is used for extracting an initial plurality of groups of signals to manufacture standard signal samples of vibration signals, obtaining the standard signal samples and the signal samples to be detected of the vibration signals, and carrying out smoothing, denoising and normalization preprocessing on the two signal samples;
the soft package tightness judging module is used for calculating the nonlinear similarity and the spatial distance value of the preprocessed standard signal sample and the signal sample to be detected and judging whether the soft package tightness is qualified or not.
7. A flexible package closure sealability detection apparatus employing the detection system of claim 6, comprising: the device comprises a conveyor belt (3) for transporting flexible packaging bags (9), at least 3 groups of rollers (1) which are equidistantly arranged are arranged at the inlet of the conveyor belt (3), brackets (10) are arranged at two sides of the middle section of the conveyor belt (3), test rollers are arranged on the brackets (10), vibration amplitude vibration sensors (4) are arranged at two shaft ends of the test rollers and are connected and fixed by an ultrasonic reflection plane (7), vibration data are collected, an ultrasonic ranging sensor (5) is connected above the vibration amplitude vibration sensors (4) and is used for monitoring the up-down displacement of the vibration amplitude vibration sensors (4) and controlling the receiving time point of vibration signals; the amplitude vibration sensor (4) and the ultrasonic ranging sensor (5) are electrically connected with the industrial personal computer (8), so that real-time communication between the sensor and the upper computer is realized, and meanwhile, the collected signals are processed through the industrial personal computer (8) and the real-time display of the quality of the flexible package is performed on the display (6).
8. The flexible package seal tightness detection device according to claim 7, wherein springs (2) are provided at both ends of the drum (1), and the drum (1) is supported to move up and down by the springs (2).
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