CN115430814A - Method for judging and early warning of continuous casting machine state - Google Patents
Method for judging and early warning of continuous casting machine state Download PDFInfo
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- CN115430814A CN115430814A CN202211179068.1A CN202211179068A CN115430814A CN 115430814 A CN115430814 A CN 115430814A CN 202211179068 A CN202211179068 A CN 202211179068A CN 115430814 A CN115430814 A CN 115430814A
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- 238000009749 continuous casting Methods 0.000 title claims abstract description 105
- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000004458 analytical method Methods 0.000 claims abstract description 7
- 238000007781 pre-processing Methods 0.000 claims abstract description 4
- 238000012706 support-vector machine Methods 0.000 claims description 18
- 238000010183 spectrum analysis Methods 0.000 claims description 9
- 238000012549 training Methods 0.000 claims description 9
- 238000001914 filtration Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 5
- 238000002372 labelling Methods 0.000 claims description 2
- 238000002360 preparation method Methods 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 abstract description 5
- 238000005259 measurement Methods 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- CWYNVVGOOAEACU-UHFFFAOYSA-N Fe2+ Chemical compound [Fe+2] CWYNVVGOOAEACU-UHFFFAOYSA-N 0.000 description 1
- 229910000831 Steel Inorganic materials 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005266 casting Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000009851 ferrous metallurgy Methods 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 238000009628 steelmaking Methods 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22D—CASTING OF METALS; CASTING OF OTHER SUBSTANCES BY THE SAME PROCESSES OR DEVICES
- B22D11/00—Continuous casting of metals, i.e. casting in indefinite lengths
- B22D11/16—Controlling or regulating processes or operations
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Abstract
The invention discloses a method for judging and early warning the state of a continuous casting machine, which comprises the steps of collecting the state information of the continuous casting machine, wherein the state information comprises electric power data of the continuous casting machine, working video data of the continuous casting machine and the like, preprocessing the collected working video data of the continuous casting machine, and acquiring a vibration signal of the continuous casting machine; and constructing a continuous casting machine state judgment and early warning model, inputting continuous casting machine state information into the continuous casting machine state judgment and early warning model, outputting an analysis structure by using the continuous casting machine state judgment and early warning model, and giving early warning according to an output result. The method can judge the state of the continuous casting machine according to two factors of electric power and vibration of the continuous casting machine, analyze various factors comprehensively, improve the accuracy of an analysis result, and avoid misjudgment and influence on production efficiency.
Description
Technical Field
The invention relates to the technical field of continuous casting based on image processing, in particular to a method and a device for judging the state of a continuous casting machine.
Background
Continuous casting, a widely used steelmaking technique, represents a great advance in increasing efficiency, reducing cost, etc. The continuous casting machine is one of key equipment in the ferrous metallurgy industry, and an important production link for casting high-temperature liquid molten steel into a solid slab is essential in the ferrous industry. Monitoring of the operating conditions of continuous casting machines is also of critical importance, based on the importance of the continuous casting machine in the overall continuous casting production.
The traditional detection method of the continuous casting machine depends on manual measurement, maintenance work is carried out by manually measuring and calculating data, the method is low in measurement speed, consumes a large amount of manpower, influences the production of the continuous casting machine, and is very low in efficiency. For example, in a workshop, a worker is required to detect a continuous casting machine by adopting a handheld measuring instrument, and a plurality of indexes are required to be measured, so that on one hand, the measurement precision is influenced by human factors, and on the other hand, the measurement efficiency is low, and real-time detection and real-time early warning cannot be realized.
Disclosure of Invention
In order to solve the defects in the prior art, the method for judging and early warning the state of the continuous casting machine is provided, the state information of the detected continuous casting machine can be acquired in real time based on data acquisition, the state of the continuous casting machine is monitored based on the state information, and early warning can be given according to the state.
The technical scheme adopted by the invention is as follows:
a method for judging and early warning the state of a continuous casting machine comprises the following steps:
s1, acquiring continuous casting machine state information, wherein the state information comprises electric power data of a continuous casting machine and working video data of the continuous casting machine;
s2, preprocessing the collected work video data of the continuous casting machine to obtain a vibration signal of the continuous casting machine;
and S3, constructing a continuous casting machine state judging and early warning model, inputting the continuous casting machine state information preprocessed in the step S2 into the continuous casting machine state judging and early warning model, outputting an analysis structure by using the continuous casting machine state judging and early warning model, and giving early warning according to an output result.
Further, the image acquisition device is used for acquiring the working video of the continuous casting machine.
Further, the method for acquiring the vibration signal of the continuous casting machine based on the working video of the continuous casting machine comprises the following steps:
decomposing the collected working video of the continuous casting machine into a single-frame image, and converting the single-frame image from a spatial domain into a frequency domain to obtain a frequency domain image;
performing spectral analysis on the frequency domain image to locate a preliminary vibration region; and performing power spectrum analysis on the frequency domain characteristic mean value in the grid of the frequency domain image to obtain a preliminary vibration region.
Performing multi-directional frequency filtering on time domain signals of the frequency domain images superposed in different frames, comparing the vibration intensity of the signals, and determining the vibration direction;
filtering the preliminary vibration region of the frequency domain image according to the vibration direction, and comparing the filtered frequency domain with the amplitude intensity in a spatial domain to obtain an accurate vibration region; and performing power spectrum analysis on the time domain through phase values of points in the precise vibration region on the frequency domain image in the precise vibration region to obtain a final vibration signal.
Further, fourier transform is adopted to convert the single-frame image from a spatial domain to a frequency domain.
Further, the method for training the continuous casting machine state judgment and early warning model comprises the following steps:
s3.1, preparing a data set:
processing the vibration data by adopting the S2 method to obtain vibration signals of the continuous casting machine, manually marking the vibration signals, endowing a label corresponding to each vibration signal, and forming a vibration signal data set of the continuous casting machine;
manually labeling the electric power data aiming at the electric power data, endowing a label corresponding to each electric power data, and forming an electric power data set;
s3.2, adopting a multi-classification support vector machine model for the continuous casting machine state judging and early warning model, and training the multi-classification support vector machine model by using the data set obtained in the step S3.1;
and S3.3, setting an early warning grade according to the classification result.
Further, constructing corresponding multi-classification support vector machine classifiers by using a vibration signal data set and an electric power data set of the continuous casting machine respectively; parameters of a multi-classification support vector machine classifier are obtained by training a multi-classification support vector machine model, the multi-classification support vector machine classifier is built, and then a continuous casting machine state judgment and early warning model is obtained.
Further, the early warning grade is divided according to the vibration degree of the continuous casting machine, and the higher the vibration degree is, the higher the early warning grade is.
Further, corresponding early warning levels are divided according to the size of the electric power data, the electric power in normal operation is used as a reference, the lowest threshold value and the highest threshold value of the electric power are respectively set, and the early warning levels are higher when the electric power is lower than or exceeds the reference electric power.
The invention has the beneficial effects that:
1. the non-contact object vibration frequency measurement method based on machine vision is limited by constraint conditions; the method is suitable for both offline video data and online video data; the method has the advantages of simple equipment, low cost, good adaptability and wide application range.
2. The method can judge the state of the continuous casting machine according to two factors of electric power and vibration of the continuous casting machine, analyze various factors comprehensively, improve the accuracy of an analysis result, and avoid misjudgment and influence on production efficiency.
3. According to the method, the early warning of the corresponding degree is carried out according to the state judgment result of the continuous casting machine; and corresponding early warning levels are set according to electric power and vibration respectively, and after the state of the continuous casting machine is obtained, early warning information can be accurately sent out, workers are prompted to check, the problems can be timely checked and solved by the workers, and risks are avoided.
Drawings
Fig. 1 is a flow chart of a method for judging and warning the state of a continuous casting machine according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, a method for judging and warning the status of a continuous casting machine includes the following steps:
s1, acquiring continuous casting machine state information, wherein the state information comprises electric power data of a continuous casting machine and working video data of the continuous casting machine. In the application, the image acquisition device is used for acquiring the working video of the continuous casting machine and subsequently acquiring the vibration data of the corresponding part on the continuous casting machine.
And acquiring electric power data of each continuous casting machine through an electric power acquisition instrument.
S2, preprocessing the collected work video data of the continuous casting machine to obtain a vibration signal of the continuous casting machine.
Aiming at the collected working video of the continuous casting machine, a video image is decomposed into a single-frame image according to frames, but the single-frame image is represented as pixel points on a spatial domain, and the pixel points correspond to discrete two-dimensional signals, so that the single-frame image needs to be converted into a frequency domain from a spatial domain. In the application, fourier transform is adopted for a single-frame image, and the conversion from a space domain to a frequency domain is realized to obtain a frequency domain image.
Performing spectral analysis on the frequency domain image to locate a preliminary vibration region; and performing power spectrum analysis on the frequency domain characteristic mean value in the grid of the frequency domain image to obtain a preliminary vibration region.
Performing multi-directional frequency filtering on time domain signals of the frequency domain images superposed in different frames, comparing the vibration intensity of the signals, and determining the vibration direction;
filtering the preliminary vibration region of the frequency domain image according to the vibration direction, and comparing the filtered frequency domain with the amplitude intensity in a spatial domain to obtain an accurate vibration region; and performing power spectrum analysis on the time domain by using the phase value of the point in the accurate vibration region on the frequency domain image in the accurate vibration region to obtain a final vibration signal.
And S3, constructing a continuous casting machine state judging and early warning model, inputting the continuous casting machine state information preprocessed in the S2 into the continuous casting machine state judging and early warning model, outputting an analysis structure by using the continuous casting machine state judging and early warning model, and giving early warning according to an output result.
The method for training the continuous casting machine state judgment and early warning model comprises the following steps:
s3.1, data set preparation
Aiming at vibration data, firstly collecting historical vibration data of a certain magnitude, wherein the historical vibration data comprises data of a normal working state and data of an abnormal working state; and processing by adopting the method disclosed by S2 to obtain vibration signals of the continuous casting machine, manually marking the vibration signals, endowing a label corresponding to each vibration signal, and forming a vibration signal data set of the continuous casting machine.
Collecting a certain magnitude of historical electric power data aiming at the electric power data, wherein the historical electric power data comprises data of a normal working state and data of an abnormal working state; and marking the electric power data manually, and endowing each electric power data with a corresponding label to form an electric power data set.
And S3.2, adopting a multi-classification support vector machine model by the continuous casting machine state judging and early warning model, and training the multi-classification support vector machine model by using the data set obtained in the step S3.1. Specifically, a vibration signal data set and an electric power data set of the continuous casting machine are used for respectively constructing corresponding multi-classification support vector machine classifiers.
Parameters of a multi-classification support vector machine classifier are obtained by training a multi-classification support vector machine model, the multi-classification support vector machine classifier is built, and then a continuous casting machine state judgment and early warning model is obtained.
And S3.3, setting an early warning grade according to the classification result.
And dividing the early warning level according to the vibration degree of the continuous casting machine, wherein the higher the vibration degree is, the higher the early warning level is. For example, the early warning level is divided into low, medium and high, if the early warning level is low, only the vibration degree is sent to the mobile end of a worker, and the worker is reminded to pay attention to the real-time state of the continuous casting machine; if the early warning level is middle, the light reminding is started while the vibration degree is sent to the mobile end of the worker; if the early warning level is high, the vibration degree is sent to the moving end of the worker, and meanwhile, light reminding and sound reminding are started.
Dividing corresponding early warning levels according to the size of the electric power data, and respectively setting a lowest threshold value and a highest threshold value of the electric power by taking the electric power in normal operation as a reference, namely when the electric power is lower than or exceeds the reference electric power, determining that the working state of the continuous casting machine needs to be emphasized by workers, so that the early warning level is higher when the electric power is lower than or exceeds the reference electric power. Particularly, the electric power value can be divided by referring to the early warning mode of the vibration degree to obtain low, medium and high grades; and outputting different reminders according to different grades.
The method for judging and early warning the state of the continuous casting machine can be specifically arranged in a controller, is realized through means such as software programming, and can specifically acquire the state information of the continuous casting machine through a data acquisition device such as a camera and an electric power measurer. And inputting the continuous casting machine state information acquired by the data acquisition device into a computer or a controller for processing and analysis, and outputting a state judgment result. Meanwhile, an early warning unit such as a light alarm, a sound alarm and a display can be arranged or a wireless terminal of a worker can be wirelessly sent to push an early warning result in real time.
The above embodiments are only used for illustrating the design idea and features of the present invention, and the purpose of the present invention is to enable those skilled in the art to understand the content of the present invention and implement the present invention accordingly, and the protection scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes or modifications based on the principles and design concepts disclosed herein are intended to be included within the scope of the present invention.
Claims (8)
1. A method for judging and early warning the state of a continuous casting machine is characterized by comprising the following steps:
s1, acquiring continuous casting machine state information, wherein the state information comprises electric power data of a continuous casting machine and working video data of the continuous casting machine;
s2, preprocessing the collected work video data of the continuous casting machine to obtain a vibration signal of the continuous casting machine;
and S3, constructing a continuous casting machine state judging and early warning model, inputting the continuous casting machine state information preprocessed in the step S2 into the continuous casting machine state judging and early warning model, outputting an analysis structure by using the continuous casting machine state judging and early warning model, and giving early warning according to an output result.
2. The method for judging and warning the state of the continuous casting machine according to claim 1, characterized in that an image acquisition device is used for acquiring a working video of the continuous casting machine.
3. The method for judging and warning the state of the continuous casting machine according to claim 1, wherein the method for acquiring the vibration signal of the continuous casting machine based on the work video of the continuous casting machine comprises the following steps:
decomposing the collected working video of the continuous casting machine into a single-frame image, and converting the single-frame image from a spatial domain into a frequency domain to obtain a frequency domain image;
performing spectral analysis on the frequency domain image to locate a preliminary vibration region; performing power spectrum analysis on the frequency domain characteristic mean value in the grid of the frequency domain image to obtain a preliminary vibration region;
performing multi-directional frequency filtering on time domain signals of the frequency domain images superposed in different frames, comparing the vibration intensity of the signals, and determining the vibration direction;
filtering the preliminary vibration region of the frequency domain image according to the vibration direction, and comparing the filtered frequency domain with the amplitude intensity in a spatial domain to obtain an accurate vibration region; and performing power spectrum analysis on the time domain by using the phase value of the point in the accurate vibration region on the frequency domain image in the accurate vibration region to obtain a final vibration signal.
4. The method of claim 3, wherein the single frame image is transformed from spatial domain to frequency domain by Fourier transform.
5. The method for judging and warning the state of the continuous casting machine according to claim 1, wherein the method for training the continuous casting machine state judging and warning model comprises the following steps of:
s3.1, data set preparation:
processing the vibration data by adopting the S2 method to obtain vibration signals of the continuous casting machine, manually marking the vibration signals, endowing a label corresponding to each vibration signal, and forming a vibration signal data set of the continuous casting machine;
manually labeling the electric power data aiming at the electric power data, endowing a label corresponding to each electric power data, and forming an electric power data set;
s3.2, adopting a multi-classification support vector machine model for the continuous casting machine state judging and early warning model, and training the multi-classification support vector machine model by using the data set obtained in the step S3.1;
and S3.3, setting an early warning grade according to the classification result.
6. The method for judging and early warning the state of the continuous casting machine according to claim 5, wherein corresponding multi-classification support vector machine classifiers are respectively constructed by utilizing a vibration signal data set and an electric power data set of the continuous casting machine; parameters of a multi-classification support vector machine classifier are obtained by training a multi-classification support vector machine model, the multi-classification support vector machine classifier is built, and then a continuous casting machine state judgment and early warning model is obtained.
7. The method for judging and warning the state of the continuous casting machine according to claim 5, wherein the warning level is divided according to the vibration degree of the continuous casting machine, and the warning level is higher when the vibration degree is higher.
8. The method as claimed in claim 5, wherein the pre-warning level is divided according to the magnitude of the electric power data, and the lowest threshold and the highest threshold of the electric power are set respectively based on the electric power during normal operation, and the pre-warning level is higher when the electric power is lower than or exceeds the reference electric power.
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