CN113034431B - Equipment use state online monitoring method, system, storage medium and terminal - Google Patents
Equipment use state online monitoring method, system, storage medium and terminal Download PDFInfo
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Abstract
The invention discloses an on-line monitoring method, a system, a storage medium and a terminal for the use state of equipment, belonging to the technical field of monitoring of instrument and meter equipment, wherein the method comprises the steps of acquiring a detection signal of detection equipment according to a certain time interval and time sequence; converting the detection signal into an image; judging the similarity between the images; and judging the use state of the monitored equipment according to the similarity between the images. The system comprises a detection signal acquisition unit, an image acquisition unit, a similarity judgment unit and a monitored equipment use state judgment unit. The terminal includes a memory and a processor. The invention can realize the on-line monitoring of the use state of the monitored equipment and has the characteristics of rapidness and automation.
Description
Technical Field
The invention relates to the technical field of instrument and meter equipment monitoring, in particular to an instrument and meter equipment use state online monitoring method, a system, a storage medium and a terminal based on an image similarity change identification technology.
Background
In the field of test measurement technology, it is generally necessary to detect the use status of instrumentation, here exemplified by (but not limited to) an oscilloscope. When the oscilloscope is used for measuring the monitored equipment, whether the monitored equipment works or not can be observed through waveform change. If the waveform is not changed, the equipment is in a state for a long time; if the waveform changes obviously, the use state of the equipment changes.
At present, the conventional methods for judging the use state of equipment through waveforms mainly include the following methods:
judging whether the use state of the equipment changes or not by manually observing the waveform change of the oscilloscope; the method comprises the steps of calculating mathematical indexes such as polar finger, maximum value, mean value, variance and the like of each measured data by collecting original data of waveform measured by an oscilloscope, and comparing the mathematical indexes to judge whether the working state of the equipment changes; the widely used method is to judge the using state of the device by calculating the original data of the waveform, and the method has the following disadvantages in practical application:
(1) many mathematical indexes such as extreme values, the most values, the mean values, the variances and the like need to be calculated, and the application is not simple and convenient enough;
(2) the change of the use state of the equipment needs to be judged by comparing the changes of different mathematical indexes, and different indexes and different combined indexes need to be compared for different equipment, so that the operation is very complicated;
disclosure of Invention
The invention aims to overcome the defects of the prior art and provides an equipment use state online monitoring method, an equipment use state online monitoring system, a storage medium and a terminal.
The purpose of the invention is realized by the following technical scheme: the device use state online monitoring method comprises the following steps: acquiring a detection signal of the detection equipment according to a certain time interval and a time sequence; converting the detection signal into an image; judging the similarity between the images; and judging the use state of the monitored equipment according to the similarity between the images.
Specifically, the detection signal of the detection device is a state signal generated in the working process of the monitored device, which is acquired by the detection device.
Specifically, converting the detection signal into an image is to convert a state waveform generated during the operation of the monitored device detected by the detection device into an image.
Specifically, the determination of the similarity between the images includes the sub-steps of:
carrying out gray level processing on the acquired image to obtain a new image; counting all pixel points of each new image in gray scale, and calculating the average color value of each image; calculating a fingerprint sequence of the images according to the average color value of each image; and calculating the Hamming distance between the two images through the fingerprint sequences of the two images, and obtaining the similarity of the two images through the Hamming distance.
Specifically, the judgment of the use state of the monitored equipment according to the similarity between the images comprises the following sub-steps:
storing the image similarity into a sequence, and then carrying out differential operation to obtain the change rate of the image similarity; and judging whether the use state of the monitored equipment is changed or not according to the change rate of the image similarity and outputting and displaying the change state.
As an option, the method also comprises the following steps between the step of carrying out gray processing on the collected image and the step of counting all pixel points of each image with gray levels: and scaling the size of the image subjected to the gray processing.
Specifically, the gray scale conversion can reduce the original data amount of the image and reduce the calculation amount when the image is subsequently processed, and the formula of the gray scale conversion is as follows:
wherein R, G, B are the red, green and blue pixel values of the pixel, respectively, and Gray represents the Gray level value of the image.
Specifically, the average color value calculation formula is:
summing all the gray values of the pixel points and dividing the sum by the total number of the pixel points; wherein average in the formula represents the average color value of the image, pixels represent the pixel value of the image, i represents the initial pixel point, and n represents the total number of the pixel points in the image.
Specifically, the method for acquiring the fingerprint sequence comprises the following steps:
Fingers[i]＝pixels[i]＞average1:0
if the pixel value of a certain point is larger than the average value, the pixel value is 1, otherwise, the pixel value is 0; wherein, Fingers [ i ] in the formula represents the ith point of the image fingerprint sequence, and pixels [ i ] represents the color value of a certain pixel point of the image.
Specifically, the calculation formula of the hamming distance is:
wherein, f in the formula1And f2Respectively representing sequences of fingerprints of two different images,
D(f1，f2) Representing the Hamming distance of two image fingerprint sequences;
representing a modulo-2 addition operation.
Specifically, the similarity calculation formula is:
wherein sim (f) in the formula1，f2) The similarity of the fingerprint sequences of two different images is shown, and n represents the length of the fingerprint sequence.
Specifically, the calculation formula of the difference operation is as follows:
in the formula, | Δ f (x)) | represents that the difference operation is performed on the similarity sequence of two images, f (x) represents the previous similarity, wherein h is 1, so f (x + h) represents the next similarity, and specifically, the similarity calculation result is obtained by substituting the difference operation formula | Δ f (x)) | into:
|Δsim|＝|sim(f3,f2)-sim(f2,f1)|
where | Δ sim | represents the rate of change of the similarity.
Specifically, the method for determining the use state of the monitored equipment comprises the following steps: setting a threshold value for the change rate of the similarity, and if the change rate of the similarity is greater than the set threshold value, determining that the use state of the monitored equipment changes; and if the similarity change rate is less than or equal to the set threshold value, judging that the use state of the monitored equipment is not changed.
Further, the system for monitoring the use state of the instrument and equipment on line based on image recognition comprises a detection signal acquisition unit, a detection signal acquisition unit and a monitoring unit, wherein the detection signal acquisition unit is used for acquiring detection signals of the detection equipment according to a certain time interval and a time sequence;
the image acquisition unit comprises an image acquisition module used for converting the detection signal into an image;
the similarity judging unit comprises a gray level conversion module, a pixel counting module, an image fingerprint module and an image similarity module and is used for judging the similarity between the images;
the monitored equipment use state judging unit comprises a judging module and an output module and is used for judging the use state of the monitored equipment according to the similarity of the images.
Specifically, the image acquisition module acquires a waveform image output by the oscilloscope in the working process of the monitored equipment and uploads the waveform image to the gray scale conversion module, the gray scale conversion module performs gray scale processing on the image, the pixel statistics module counts the average value of pixel points of the image, the image fingerprint module calculates an image fingerprint sequence, the image similarity module compares the similarity of two images, the judgment module judges the use state of the equipment according to the change rate of the similarity of the images and transmits the use state to the output module, and the output module displays the judgment result;
specifically, the detection device comprises an oscilloscope and a frequency spectrograph, and is used for representing the working state of the monitored device in a waveform change mode; the monitored equipment comprises instruments, instruments and experimental equipment; the detection equipment is connected with the output end of the monitored equipment.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention can realize the on-line monitoring of the use state of the instrument and equipment without referring to excessive parameters, and has the characteristics of rapidness and automation.
(2) According to the invention, the collected image is subjected to gray processing, so that the effects of reducing the original data volume of the image and lightening the calculation amount in the subsequent image processing can be achieved.
(3) According to the invention, the image is zoomed, so that the effects of removing the details of the image, only retaining the structure and brightness information and abandoning the image difference caused by different sizes and proportions can be achieved.
Drawings
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
FIG. 1 is a flowchart of a method of example 1 of the present invention;
fig. 2 is a waveform diagram of an apparatus operating state acquired in embodiment 1 of the present invention;
FIG. 3 is a waveform diagram showing the operating state of the apparatus after the gradation processing in embodiment 1 of the present invention;
FIG. 4 is a sequence chart of image similarity in embodiment 1 of the present invention;
FIG. 5 is a sequence chart of similarity difference in embodiment 1 of the present invention;
FIG. 6 is a diagram showing the result of monitoring the usage status of the device in embodiment 1 of the present invention;
fig. 7 is a waveform diagram after size scaling in embodiment 1 of the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, and it should be understood that the embodiments described herein are only for illustrating and explaining the present invention and are not used to limit the present invention.
Example 1
The embodiment relates to an on-line monitoring method for the use state of equipment, which is applied to the on-line monitoring of instruments and equipment, realizes the real-time on-line monitoring of the use state of the monitored equipment and has the characteristics of quickness and automation.
As shown in fig. 1, a method for online monitoring of a device usage status includes: acquiring a detection signal of the detection equipment according to a certain time interval and a time sequence; converting the detection signal into an image; judging the similarity between the images; and judging the use state of the monitored equipment according to the similarity of the images.
More specifically, the detection signal of the detection device is a state signal generated in the working process of the monitored device, which is acquired by the detection device.
More specifically, converting the detection signal into an image is to convert a state waveform generated during the operation of the monitored device detected by the detection device into an image. Fig. 2 shows 9 detection signals of the detection device acquired at a certain time interval and time sequence, where the abscissa in the figure represents time and the ordinate represents amplitude, and it can be clearly seen that fig. 1_ b.png is different from other 8 images (1.png to 8.png), that is, the usage state of the monitored device changes.
More specifically, the judging of the similarity between the images includes the substeps of:
s01: carrying out gray level processing on the acquired image to obtain a new image; the calculation formula for carrying out gray scale processing is as follows:
r, G, B are the red, green and blue pixel values of the pixel, respectively, and the Gray scale value ranges from 0 to 255. The conversion of the color image into the gray image can reduce the original data amount of the image, reduce the calculation amount in the subsequent image processing, and perform gray processing on the acquired waveform image to obtain the graph shown in fig. 3, wherein the abscissa in the graph represents time, and the ordinate represents amplitude, and the image in fig. 3 only has a change in color value relative to the corresponding image in fig. 2, and the remaining parameters remain unchanged.
S02: counting all pixel points of a new image after gray processing, and calculating the average color value of each image; in this embodiment, the statistics of the gray value arrays of all the pixel points of the 1.png image in the gray level map 3 is as follows:
[-1907998,-855310,-1250068,-1052689,-1052689,-65794,-1,-1,-1,-1,-1,-1,pixels＝……
-1,-1,-1250068,-1315861,-1315861]
the average color calculation is performed for the gray values of all pixels, and the formula is as follows:
the average in the formula represents the average color value of the image, pixels represent the pixel value of the image, i represents the initial pixel point, and n represents the total number of the pixel points in the image, namely, the gray values of all the pixel points are summed and then divided by the total number of the pixel points.
S03: calculating a fingerprint sequence of the images according to the average color value of each image; the calculation method of the fingerprint sequence comprises the following steps:
Fingers[i]＝pixels[i]＞average1:0
wherein, finger [ i ] in the formula represents the image fingerprint sequence, and pixel [ i ] represents the color value of a certain pixel point of the image, that is, if the gray value of a certain pixel point is greater than the average color value, the pixel point value is 1, otherwise, the pixel point value is zero, and a specific fingerprint sequence can be obtained.
S04: calculating the distance between two images by means of fingerprint sequences of the two imagesAnd obtaining the similarity of the two images through the hamming distance. Wherein Hamming distance is the basic concept in information theory and is used for describing two n long byte codes
And
the distance between the two sequences is judged whether the two sequences are similar, namely whether the two sequences have different digits, and the calculation formula of the Hamming distance is as follows:
wherein, f in the formula1And f2Respectively representing sequences of fingerprints of two different images,
D(f1，f2) Representing the Hamming distance of two image fingerprint sequences;
the modulo-2 addition operation is represented, the modulo-2 addition operation is that exclusive or operation is carried out on the two sequences, the number of the result is 1 is counted, if one bit of the two sequences is different, the Hamming distance is 1, if the two bits of the two sequences are different, the Hamming distance is 2, and the like. For a computer, the operation speed is extremely high, so that the method for monitoring the use state of the instrument and equipment based on the image similarity can quickly track the change of the working state of the equipment to be detected.
After the Hamming distance is obtained, further calculating the image similarity of adjacent time points, wherein the formula for calculating the similarity is as follows:
wherein sim (f) in the formula1，f2) The similarity of the fingerprint sequences of two different images is represented, n represents the length of the fingerprint sequence, the similarity sequence is actually obtained according to the algorithm, as shown in fig. 4, the abscissa in the figure represents the similarity sequence, and the ordinate represents the similarity value.
More specifically, the determination of the use state of the monitored device based on the similarity between the images includes the sub-steps of:
s05: storing the image similarity into a sequence, and then carrying out differential operation to obtain the change rate of the image similarity; the formula for carrying out differential operation on the similarity sequence is as follows:
in the formula, | Δ f (x) | represents that the difference operation is performed on the similarity sequence of two images, f (x) represents the previous similarity, wherein h is 1, so f (x + h) represents the next similarity, the actually obtained difference similarity sequence is shown in fig. 5, the abscissa in the figure represents the waveform image sequence of the monitored equipment sampled in time sequence, and the ordinate represents the similarity of the image sequences at adjacent time points.
Further, substituting the similarity calculation result into the difference operation equation | Δ f (x) | yields:
|Δsim|＝|sim(f3,f2)-sim(f2,f1)|
where | Δ sim | represents the rate of change of the similarity.
S06: and judging whether the use state of the monitored equipment is changed or not according to the change rate of the image similarity, and outputting and displaying the change. Wherein, the change of the use state of the monitored equipment during operation is displayed through the output module.
Further, the judging module judges whether the use state of the monitored equipment changes or not by setting a threshold value for the change rate of the similarity, and if the change rate of the similarity is greater than the set threshold value, the use state of the monitored equipment is judged to change, otherwise, the use state of the monitored equipment is not changed. As shown in fig. 6, the abscissa in the graph represents the similarity sequence, and the ordinate represents the similarity and the similarity change rate, and it is seen from the image similarity change data of the adjacent time points that there is a case where there is a sudden change in the image similarity change of the adjacent time points; if the set threshold value of the change rate of the similarity is 20%, 40.13 in the figure is greater than 20%, which indicates that the use state of the instrument and equipment is changed; otherwise, the change rate is less than 20%, which indicates that the usage state of the device is not changed. It is apparent that the ninth to tenth sampling points in fig. 6, i.e., the operating states of the monitored equipment have changed at the sampling time points S9 to S10, and likewise, the operating states of the monitored equipment have changed at the sampling time points S11 to S12. The on-line monitoring method for the equipment use state realizes automatic and rapid on-line monitoring of the working states of the monitored equipment and instruments.
As an option, the following steps are further included between step S01 and step S02:
step S01': and scaling the size of the image subjected to the gray processing. The size scaling module scales the acquired image to 32 multiplied by 32 pixels, removes the details of the image, only retains the structure and brightness information, and discards the image difference brought by different sizes and proportions. As shown in fig. 7, the left side is an image before reduction, and the right side is an image reduced to 32 × 32 pixels.
Example 2
The embodiment relates to an online monitoring system for the use state of equipment based on image recognition, which is further optimized on the basis of the embodiment 1, and comprises:
the detection signal acquisition unit is used for acquiring detection signals of the detection equipment according to a certain time interval and time sequence;
the image acquisition unit comprises an image acquisition module used for converting the detection signal into an image;
the similarity judging unit comprises a gray level conversion module, a pixel counting module, an image fingerprint module and an image similarity module and is used for judging the similarity between the images;
the monitored equipment use state judging unit comprises a judging module and an output module and is used for judging the use state of the monitored equipment according to the similarity of the images.
The invention relates to an instrument and equipment use state online monitoring system based on image similarity.A signal waveform detected by detection equipment is acquired by an image acquisition module according to a certain time interval and time sequence and is converted into an image, then a gray level conversion module performs gray level processing on the acquired image, a pixel statistics module performs statistics on pixel points of the zoomed image and performs averaging processing, an image fingerprint module calculates an image fingerprint sequence according to an average pixel color value, and then an image similarity module compares the fingerprint sequences between two images to obtain a Hamming distance between the two images and calculate the similarity between the images. Continuing with this, the judging module obtains a similarity sequence, carries out difference operation to the similarity sequence, obtains the similarity rate of change, judges the change situation of equipment use state through the mode of setting for the threshold value, promptly: if the similarity change rate is larger than the set threshold value, judging that the use state of the equipment is changed; if the similarity change rate is less than or equal to the set threshold, it is determined that the apparatus use state has not changed.
As a preferred item, the similarity determination unit further includes a size scaling module, which is used to scale and change the image and abandon the image difference caused by different sizes and proportions.
Example 3
The embodiment relates to a terminal, which is further optimized on the basis of the embodiment 1, and the terminal comprises a memory and a processor, wherein the memory stores computer instructions capable of running on the processor; and when the processor runs the computer instructions, all the steps of the online monitoring method for the use state of the equipment in the embodiment 1 are executed.
The above detailed description is for the purpose of describing the invention in detail, and it should not be construed that the detailed description is limited to the description, and it should be understood that various simple deductions and substitutions can be made by those skilled in the art without departing from the spirit of the invention.
Claims (7)
1. An on-line monitoring method for the use state of equipment is characterized by comprising the following steps:
acquiring a detection signal of the detection equipment according to a certain time interval and a time sequence;
converting the detection signal into an image;
judging the similarity between the images;
judging the use state of the monitored equipment according to the similarity between the images;
the detection signal of the detection equipment is a state signal which is acquired by the detection equipment and generated in the working process of the monitored equipment; the step of converting the detection signal into the image is to convert a state waveform, which is detected by the detection equipment and generated in the working process of the monitored equipment, into the image;
the judging of the similarity between the images comprises the following substeps:
carrying out gray level processing on the acquired image to obtain a new image;
counting all pixel points of the new image after the gray processing, and calculating the average color value of each new image;
calculating a fingerprint sequence of the image according to the average color value of each new image;
calculating the Hamming distance between the two images through the fingerprint sequences of the two images, and obtaining the similarity of the two images through the Hamming distance;
the method for judging the use state of the monitored equipment according to the similarity between the images comprises the following substeps:
storing the image similarity into a sequence, and then carrying out differential operation to obtain the change rate of the image similarity;
judging whether the use state of the monitored equipment changes or not according to the change rate of the image similarity and outputting and displaying the change;
the calculation formula of the difference operation is as follows:
in the formula, | Δ f (x) | represents that the difference operation is carried out on the similarity sequence of the two images, and f (x) represents the previous similarity, wherein h is 1, so that f (x + h) represents the next similarity;
substituting the similarity calculation result into a difference operation formula | Δ f (x) | to obtain:
|Δsim|＝|sim(f3,f2)-sim(f2,f1)|
where | Δ sim | represents the rate of change of the similarity, sim (f)2，f1)|、sim(f3，f2) Both represent the similarity of two images adjacent in time sequence;
and judging whether the use state of the monitored equipment changes or not by setting a threshold value for the change rate of the similarity, if the change rate of the similarity is greater than the set threshold value, judging that the use state of the monitored equipment changes, otherwise, indicating that the use state of the monitored equipment does not change.
2. The on-line monitoring method for the use state of the equipment according to claim 1, wherein the steps between the step of performing gray processing on the acquired image and the step of counting all pixel points of a new image after the gray processing further comprise the following steps:
and scaling the size of the image subjected to the gray processing.
3. The on-line monitoring method for the usage status of equipment according to claim 1, wherein the average color value calculation formula is:
wherein average in the formula represents the average color value of the image, pixels represent the pixel value of the image, i represents the initial pixel point, and n represents the total number of the pixel points in the image;
the fingerprint sequence is obtained by the following method:
Fingers[i]＝pixels[i]＞average1:0
wherein, finger [ i ] in the formula represents the ith point of the image fingerprint sequence, and pixel [ i ] represents the color value of a certain pixel point of the image.
4. The on-line monitoring method for the usage status of equipment according to claim 3, wherein the calculation formula of the Hamming distance is:
wherein, f in the formula1And f2Fingerprint sequences respectively representing two successive images, f1 i∈{0,1},f2 i∈{0,1}；D(f1,f2) Representing the Hamming distance of two continuous image fingerprint sequences;
represents a modulo-2 addition operation;
the similarity calculation formula is as follows:
wherein sim (f) in the formula1，f2) The similarity of the fingerprint sequences of the two images is shown, and n represents the length of the fingerprint sequence.
5. An online monitoring system for the usage status of equipment, the system comprising:
the detection signal acquisition unit is used for acquiring detection signals of the detection equipment according to a certain time interval and time sequence; the detection signal of the detection equipment is a state signal which is acquired by the detection equipment and generated in the working process of the monitored equipment;
the image acquisition unit comprises an image acquisition module used for converting the detection signal into an image; the step of converting the detection signal into the image is to convert a state waveform, which is detected by the detection equipment and generated in the working process of the monitored equipment, into the image;
the similarity judging unit comprises a gray level conversion module, a pixel counting module, an image fingerprint module and an image similarity module and is used for judging the similarity between the images; judging the similarity between the images comprises carrying out gray processing on the collected images to obtain new images; counting all pixel points of the new image after the gray processing, and calculating the average color value of each new image; calculating a fingerprint sequence of the image according to the average color value of each new image; calculating the Hamming distance between the two images through the fingerprint sequences of the two images, and obtaining the similarity of the two images through the Hamming distance;
the monitored equipment use state judging unit comprises a judging module and an output module and is used for judging the use state of the monitored equipment according to the similarity of the images; the method for judging the use state of the monitored equipment according to the similarity between the images comprises the following substeps:
storing the image similarity into a sequence, and then carrying out differential operation to obtain the change rate of the image similarity;
judging whether the use state of the monitored equipment changes or not according to the change rate of the image similarity and outputting and displaying the change;
the calculation formula of the difference operation is as follows:
in the formula, | Δ f (x) | represents that the difference operation is carried out on the similarity sequence of the two images, and f (x) represents the previous similarity, wherein h is 1, so that f (x + h) represents the next similarity;
substituting the similarity calculation result into a difference operation formula | Δ f (x) | to obtain:
|Δsim|＝|sim(f3,f2)-sim(f2,f1)|
where | Δ sim | represents the rate of change of the similarity;
the judgment module judges whether the use state of the monitored equipment changes or not by setting a threshold value for the change rate of the similarity, if the change rate of the similarity is larger than the set threshold value, the use state of the monitored equipment is judged to change, otherwise, the use state of the monitored equipment is not changed.
6. A storage medium having computer instructions stored thereon, characterized in that: the computer instructions when executed perform the steps of the method for on-line monitoring of usage status of a device according to any one of claims 1 to 4.
7. A terminal comprising a memory and a processor, the memory having stored thereon computer instructions executable on the processor, wherein the processor executes the computer instructions to perform the steps of the method for on-line monitoring of device usage status according to any one of claims 1 to 4.
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Denomination of invention: A method, system, storage medium, and terminal for online monitoring of device usage status Effective date of registration: 20230619 Granted publication date: 20220617 Pledgee: Chengdu Rural Commercial Bank Co.,Ltd. Dayuan Sub branch Pledgor: CHENGDU TIANHENG ZHIZAO TECHNOLOGY Co.,Ltd. Registration number: Y2023510000154 |