CN109459925B - Method for hand-drawing identification and parameter setting of PID control data - Google Patents
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Abstract
The invention discloses a method for hand-drawing identification and parameter setting of PID control data, which consists of three parts, namely PID curve drawing, PID curve datamation and PID parameter setting; the PID curve drawing part establishes a set of picture drawing method suitable for the subsequent identification process; the PID curve datamation part adopts methods of machine vision, coordinate transformation and the like to realize the conversion from pixel points to data values; the PID parameter setting part uses the data obtained by the data part to be put into a PID setting system to carry out PID parameter setting. According to the method, a user can carry out digitization on the PID curve obtained by observing the DCS and complete the PID parameter setting process to obtain the set PID parameter. The method can realize the PID setting work without a data interface, and has the core meaning of realizing physical isolation of the DCS and the PID parameter setting system, so that no physical transmission on data exists between the DCS and the PID parameter setting system, and the safety of the data between the systems and the safety of the system per se are ensured.
Description
Technical Field
The invention belongs to the technical field of curve identification and parameter setting, and particularly relates to a method for hand-drawing identification and parameter setting of PID control data.
Background
PID control is one of the core contents in the control subject, and the current closed-loop automatic system technology is based on a feedback link to reduce uncertainty. Three components in the feedback theory are: measuring, comparing and executing. The most critical in the measurement section is to compare the actual value of the controlled variable with the desired value, and to use this deviation to correct the response of the system and to perform the regulation control. The regulator control law which is most widely applied in the actual engineering is proportional, integral and differential control, PID control for short, and PID regulation.
The development of the PID controller has been a history for decades, and it has become one of the main technologies of industrial control due to its simple structure, good stability, reliable operation and convenient adjustment. When the structural parameters of the controlled object cannot be completely mastered or an accurate mathematical model is not obtained, the structure and the parameters of the system controller must be determined by depending on experience and field data measurement and debugging. The PID control technique is most convenient to apply. The PID control is controlled by calculating a control amount by proportional, integral, and differential according to the error of the system.
The important problem in the PID control is the parameter setting problem of the controller, that is, the setting of three parameters (proportional coefficient, integral time and differential time), and the quality of the setting affects not only the control quality but also the robustness of the controller. There are many methods for setting parameters of a PID controller, and there are two broad categories in summary: one is theoretical calculation and determination. The method is mainly used for determining the parameters of the controller through theoretical calculation according to a mathematical model of a system. The calculation data obtained by this method may not be used directly, but must be adjusted and modified by engineering practice. And the second is an engineering setting method which mainly depends on engineering experience and is directly carried out in the test of the control system, and the method is simple and easy to master and is widely adopted in engineering practice. The PID controller parameter setting method mainly comprises a critical proportion method, a reaction curve method and an attenuation method.
PID tuning requires specific parameters of the PID curve, which is problematic today in many companies and laboratories: the derivation of PID curve parameters is often inefficient and time consuming due to the need for level-to-level auditing of various problems. At the moment, only PID curves in the DCS system exist, and data of the curves do not exist, so that great obstruction and trouble are caused to PID setting.
However, there are few solutions to this problem on the market. Although there is some software related to curve recognition, it was a long-standing software. The adopted methods are a traditional coordinate transformation method, a mouse click curve position determination method and the like, so that the efficiency is low, the data do not reach the standard, the quality of PID parameter setting is seriously influenced, and the overall robustness of the system is also influenced.
Therefore, it is desirable to obtain data before PID adjustment by digitizing a picture of a freehand-drawn PID curve and further perform PID parameter adjustment by a PID parameter adjustment system.
Disclosure of Invention
The invention aims to provide a method for hand-drawing identification and parameter setting of PID control data aiming at the defects of the prior art, wherein a PID curve observed in a DCS screen of industrial production and the like is drawn and processed according to the method of the invention, so that PID curve data of the PID curve in a measurement time period can be obtained, and a PID parameter with good setting effect can be obtained through the parameter setting method. The implementation of the method consists of three parts of PID curve drawing, PID curve datamation and PID parameter setting.
The PID curve drawing mainly establishes a set of standardized picture drawing method, and mainly comprises calibration of the position of a curve area and a curve drawing method. The calibration of the position of the curve area adopts a method of circular marking, and the positions of small circular replacing points are drawn at four corner positions of the rectangular area where the curve is located; the method for drawing the curves is to draw three PID curves with different colors in a rectangular area. The core of the PID curve datamation lies in converting the pixel points of the representative curve in the picture into actual curve data, and mainly comprises the extraction of effective pixel points and the coordinate space conversion. The extraction of the effective pixel points is to extract the effective area where the curve is positioned and extract the corresponding curves by utilizing the marked characteristics in the curve drawing process; acquiring marks of coordinate axes in the hand-drawn picture by using an optical character recognition method; and after the pixel points are obtained, the pixel points are corresponding to the actual data points by using a coordinate transformation method. The main content of PID parameter setting is to use the result obtained by the above-mentioned digitization and to use the PID parameter setting system to carry out parameter setting. The specific implementation scheme of the method is as follows:
(1) the PID curves observed in the DCS screen are hand-drawn: drawing the boundary of a rectangular area where the PID curve is located; drawing the positions of round replacing points at four corner positions of the rectangular area by adopting a round marking method; the rectangular area is divided into three parts from top to bottom through dividing lines, and three PID curves with different colors are respectively drawn: SV (set value) curve, MV (controller output) curve, PV (process variable) curve; marking the numerical value of the coordinate axis near the outer side of the rectangular area, and respectively marking the three parts;
(2) PID curve datamation: shooting a hand-drawn PID curve, and extracting a rectangular effective area where the curve is located and corresponding curves in the hand-drawn picture by using the characteristics marked in the curve drawing process in the step (1); acquiring marks of coordinate axes in the hand-drawn picture by using an optical character recognition method to obtain the range of the time length and the value of each corresponding curve; performing position statistics according to columns on all the pixel points; converting the coordinate space according to the value range and the pixel point statistical result, and converting the original pixel space into an actual curve space, thereby obtaining data point information;
(3) PID parameter setting: and (3) performing parameter setting on the result digitalized in the step (2) by utilizing a PID parameter setting system.
Further, in the step (1), the overall curve is drawn on the white-based a4 paper, the rectangular area boundary adopts a black line, the three part dividing lines adopt black lines, and the three PID curves are drawn in red, green and blue colors respectively.
Further, in the step (2), the extracting of the rectangular effective region where the curve is located specifically includes: converting the hand-drawn picture from a color space to a gray scale space; circle detection is carried out through Hough circle transformation, the circle centers of four boundary area circles are obtained, and therefore the boundary position of the effective area is obtained; cutting the effective area by using the four boundary points to obtain the effective areas of the positions of the curves in the color space and the gray scale space; and correcting the distortion brought by the photographing process, and properly amplifying or reducing each line of the pixel points by using the image scaling principle to obtain a rectangular effective area.
Further, in the step (2), the curve extraction specifically includes: carrying out Hough line detection on a gray level picture in a rectangular effective area, obtaining the position of a segmentation line through line detection, thereby segmenting the image, respectively obtaining effective picture parts at the positions of three curves, carrying out filtering processing on the picture of the part to remove noise points, carrying out histogram statistics of gray levels on the filtered picture, and carrying out gray level binarization processing by taking the gray level of a representative curve as a threshold value; after the operation is carried out on the part of the picture where each curve is located, only curve data and part of noise points exist in the visual field of the picture, and therefore curve primary extraction is completed.
Further, in the step (2), denoising is performed again after curve preliminary extraction, specifically: processing by using points in a range of 3 multiplied by 3 around each pixel point, if more than half of the points around are all 1, judging the points to be points on a curve, otherwise, judging the points to be noise points; after the three curves are all finished, only curve data and a little noise exist in the view field of the picture.
Further, in the step (2), in the process of performing the column-wise position statistics on all the pixel points, since the curve has a certain width, all the positions where a plurality of points appear are counted and the average value is taken as the final result.
Further, in the step (2), the data points obtained after the coordinate space transformation are subjected to segmented outlier detection: dividing the data points into intervals according to the length, wherein the abnormal value is a point with a large difference between the data point and the mean value of the data points in the interval and the difference exceeds 0.5 time of the mean value; for continuity of the data points, the data of the removed points is complemented by a linear interpolation fitting method, so that all the data points in the gray level image are obtained.
Further, in the step (3), the PID parameter tuning system needs to be able to complete the PID parameter tuning process of multiple types of DCS systems.
Further, in the step (3), according to the requirement of the PID parameter tuning system for the sampling time, the data obtained in the step (2) is resampled and interpolated.
Further, in the step (3), data is imported into the parameter setting system, and by using the DCS type and the PID type of the data source, sampling time is selected according to the interval of the data points to perform PID parameter setting, so as to finally obtain a set PID parameter.
The invention has the beneficial effects that: the implementation of the method consists of three parts of PID curve drawing, PID curve datamation and PID parameter setting; the PID curve drawing part establishes a set of picture drawing method suitable for the subsequent identification process, and provides service for the subsequent datamation process; the PID curve datamation part adopts methods of machine vision, coordinate transformation and the like to realize the conversion from pixel points to data values; the PID parameter setting part uses the data obtained by the data part to be put into a PID setting system to carry out PID parameter setting. According to the method, a user can carry out digitization on the PID curve obtained by observing the DCS and complete the PID parameter setting process to obtain the set PID parameter. The method can realize the PID setting work without a data interface, and has the core meaning of realizing physical isolation of the DCS and the PID parameter setting system, so that no physical transmission on data exists between the DCS and the PID parameter setting system, and the safety of the data between the systems and the safety of the system per se are ensured.
Drawings
FIG. 1 is an overall flow diagram of the process of the present invention;
FIG. 2 is a flow chart of PID curve datamation;
FIG. 3 is a schematic diagram of a PID curve of the DCS system;
FIG. 4 is a schematic hand-drawn PID curve;
FIG. 5 is a schematic diagram of a PID parameter tuning system;
fig. 6 is a schematic diagram of a parameter setting result.
Detailed Description
The following further description of specific embodiments of the invention is provided to facilitate understanding by those skilled in the art.
As shown in FIG. 1, the specific implementation of the present invention can be divided into three steps of PID curve drawing, PID curve datamation and PID parameter tuning.
The first step is PID curve drawing, i.e. drawing the PID curve (as shown in FIG. 3) observed in the DCS system screen of industrial production and the like by hand. The method mainly comprises calibration of the position of a curve area and a curve drawing method. The calibration of the position of the curve area adopts a method of circular marking, and the positions of small circular replacing points are drawn at four corner positions of the rectangular area where the curve is located; the method for drawing the curves is to draw three PID curves with different colors in a rectangular area.
The whole curve is drawn on A4 paper with white as the ground color, a rectangular area is used as a coordinate axis, the position of four corner positions where the rectangular area is located is marked by replacing points with circles, the color can be selected to be black with high contrast with the ground color, and meanwhile, the whole rectangular area boundary drawing is also completed by using black. Thereby completing the drawing of the effective area where the PID curve is located.
The PID curves are divided into three, which are SV (set value) curve, MV (controller output) curve and PV (process variable) curve. The drawing area is divided into three parts in the vertical direction by using a black line, the three parts are divided into three rectangular areas, three curves are respectively drawn, and the adopted colors are red, green and blue.
In the overall rendering process, the numerical values of the coordinate axes are marked near the outer side of the rectangular region, and are marked separately.
The hand-drawn PID curve is shown in fig. 4.
The second step is PID curve datamation, and the implementation flow is shown in FIG. 2.
Since it is troublesome to process an image in an original color space, a gray scale is first converted into a gray scale space by the following formula. Thereby obtaining PID curve pictures in two spaces.
Gray＝R×0.299+G×0.587+B×0.114
In the first step, the effective area where the curve is located is calibrated, so that circle detection is performed by Hough circle transformation in the step, and circle centers of four boundary area circles can be obtained through the circle detection in the step, so that the boundary position of the effective area is obtained. And the effective area is cut by four boundary points, so that the effective area of the position of the curve under two spaces (color space and gray scale space) is obtained.
After the effective area is obtained, it can be obviously found that the effective area may not be a complete rectangle, and the image distortion is easily caused to be a trapezoid in the case of normal photographing, so that what is needed in this step is image correction, and each line where the pixel points are located is appropriately enlarged or reduced to fit the actual rectangle by using the principle of image scaling.
Through the two steps, a complete rectangular effective area can be obtained, and then curve extraction and datamation can be carried out on the obtained area. The following is a process of converting data into data.
The method comprises the steps of firstly carrying out Hough line detection on a gray picture in the region, obtaining the position of a segmentation line through line detection, segmenting the image by utilizing the detected linear position, thus obtaining effective picture parts of the positions of three curves respectively, carrying out proper filtering processing on the picture of the part to remove noise points, recommending that median filtering is adopted, carrying out histogram statistics on the gray level of the filtered picture, and carrying out gray level binarization processing on the gray level representing the curve as a threshold value through a statistical result because the gray level of the picture part where each curve is located can be obviously divided into two types, wherein one type is the gray level mainly comprising the curve, and the other type is the gray level mainly comprising the boundary.
After the above operations are performed on the picture of the portion where each curve is located, only curve data and a portion of noise are present in the view field of the picture.
At this time, the denoising operation is performed again. The denoising method is to process by utilizing points in a 3 x 3 range around each pixel point, if more than half of the points around are all 1, the point can be judged to be a point on a curve, and if not, the point is a noise point. The main basis of the denoising is the continuity of the curve, and the curve has a certain width, so if the curve is an isolated noise point, the noise can be necessarily filtered by the method. The method can directly use the following template to carry out operation, and carry out binarization processing by taking 4 or 5 as a threshold value:
after all three curves have completed the above operation, then a picture of only the curves is obtained at this point, and a few possible noise remains.
At this time, all the pixel points are subjected to position statistics by columns, and since the curve has a certain width, positions where a plurality of points appear need to be subjected to total statistics and an average value is taken as a final result. Therefore, statistics of all pixel points is completed.
And (3) carrying out coordinate axis scale identification in the residual picture cut from the first effective area by using an optical character identification method, wherein the range of the time length and the value of each corresponding curve can be obtained by using the method.
And transforming the coordinate space by using the value range and the statistical result of the pixel points, and converting the original pixel space into an actual curve space, thereby obtaining basic data point information.
At this time, the problem of the data points still lies in the situation that there may be some noise influence, at this time, the abnormal value detection of the segments can be performed, the obtained data points are divided into intervals according to the length, and the threshold value for dividing the interval number needs to be controlled according to the number of the actual data points. The abnormal value is considered as the point which is greatly different from the mean value of the data points in the interval and is more than 0.5 time of the mean value. Outliers are determined using the method described above, and the data from which points are removed is completed using the following linear interpolation fitting method for continuity of the data points.
All data points in the grayscale image are thus obtained.
The verification can be performed by using a color picture, and all points are drawn on the color picture to perform the verification of observing the coincidence degree as the identification accuracy.
The third step is PID parameter setting, which mainly uses a PID parameter setting system to carry out parameter setting.
The PID parameter setting system needs to be capable of completing the PID parameter setting process of various DCS systems, and the interface of a certain PID parameter setting system is shown in FIG. 5. After the data is obtained, operations such as resampling, interpolation and the like need to be carried out according to the requirement of a PID parameter setting system on sampling time, and the sampling time is recommended to be as small as possible so as to improve the accuracy of setting.
After the above operations are completed, the data are imported into a parameter setting system, and by using the DCS type and the PID type of the data source, sampling time is selected according to the interval of the data points to perform PID parameter setting, so as to finally obtain a set PID parameter, as shown in fig. 6.
One skilled in the art can, using the teachings of the present invention, readily make various changes and modifications to the invention without departing from the spirit and scope of the invention as defined by the appended claims. Any modifications and equivalent variations of the above-described embodiments, which are made in accordance with the technical spirit and substance of the present invention, fall within the scope of protection of the present invention as defined in the claims.
Claims (9)
1. A method for hand-drawing identification and parameter setting of PID control data is characterized by comprising the following steps:
(1) the PID curves observed in the DCS screen are hand-drawn: drawing the boundary of a rectangular area where the PID curve is located; drawing the positions of round replacing points at four corner positions of the rectangular area by adopting a round marking method; the rectangular area is divided into three parts from top to bottom through dividing lines, and three PID curves with different colors are respectively drawn: SV curve, MV curve, PV curve; marking the numerical value of the coordinate axis near the outer side of the rectangular area, and respectively marking the three parts;
(2) PID curve datamation: shooting a hand-drawn PID curve, and extracting a rectangular effective area where the curve is located and corresponding curves in the hand-drawn picture by using the characteristics marked in the curve drawing process in the step (1); the extraction of the rectangular effective area where the curve is located is specifically as follows: converting the hand-drawn picture from a color space to a gray scale space; circle detection is carried out through Hough circle transformation, the circle centers of four boundary area circles are obtained, and therefore the boundary position of the effective area is obtained; cutting the effective area by using the four boundary points to obtain the effective areas of the positions of the curves in the color space and the gray scale space; correcting the distortion brought by the photographing process, and properly amplifying or reducing each line of the pixel points by using the image scaling principle to obtain a rectangular effective area; acquiring marks of coordinate axes in the hand-drawn picture by using an optical character recognition method to obtain the range of the time length and the value of each corresponding curve; performing position statistics according to columns on all the pixel points; converting the coordinate space according to the value range and the pixel point statistical result, and converting the original pixel space into an actual curve space, thereby obtaining data point information;
(3) PID parameter setting: and (3) performing parameter setting on the result digitalized in the step (2) by utilizing a PID parameter setting system.
2. The method for PID control data hand-drawn identification and parameter tuning as claimed in claim 1, wherein in step (1), the whole curve is drawn on a paper a4 with white as the background color, the rectangular area boundary is black line, the three part dividing lines are black line, and the three PID curves are drawn in red, green and blue colors respectively.
3. The method for PID control data freehand drawing identification and parameter tuning according to claim 1, wherein in the step (2), the curve extraction specifically comprises: carrying out Hough line detection on a gray level picture in a rectangular effective area, obtaining the position of a segmentation line through line detection, thereby segmenting the image, respectively obtaining effective picture parts at the positions of three curves, carrying out filtering processing on the picture of the part to remove noise points, carrying out histogram statistics of gray levels on the filtered picture, and carrying out gray level binarization processing by taking the gray level of a representative curve as a threshold value; after the operation is carried out on the part of the picture where each curve is located, only curve data and part of noise points exist in the visual field of the picture, and therefore curve primary extraction is completed.
4. The method for PID control data freehand drawing identification and parameter tuning as claimed in claim 3, wherein in the step (2), denoising is performed again after curve preliminary extraction, specifically: processing by using points in a range of 3 multiplied by 3 around each pixel point, if more than half of the points around are all 1, judging the points to be points on a curve, otherwise, judging the points to be noise points; after the three curves are all finished, only curve data and a little noise exist in the view field of the picture.
5. The method for PID control data freehand drawing identification and parameter tuning according to claim 1, wherein in the step (2), in the process of performing position statistics for all pixel points by column, since the curve has a certain width, the positions where a plurality of points appear are totally counted and averaged to be the final result.
6. The method for PID control data freehand drawing identification and parameter tuning according to claim 1, wherein in the step (2), segmented outlier detection is performed on the data points obtained after coordinate space transformation: dividing the data points into intervals according to the length, wherein the abnormal value is a point with a large difference between the data point and the mean value of the data points in the interval and the difference exceeds 0.5 time of the mean value; for continuity of the data points, the data of the removed points is complemented by a linear interpolation fitting method, so that all the data points in the gray level image are obtained.
7. The method for the hand-drawn identification and parameter setting of the PID control data according to claim 1, wherein in the step (3), the PID parameter setting system needs to be able to complete the PID parameter setting process of multiple types of DCS systems.
8. The method for PID control data freehand drawing identification and parameter setting according to claim 1, wherein in the step (3), the data obtained in the step (2) is resampled and interpolated according to the requirement of a PID parameter setting system for sampling time.
9. The method for PID control data freehand drawing identification and parameter setting according to claim 1, wherein in the step (3), the data is imported into a parameter setting system, and the PID parameter setting is performed by using DCS type and PID type of data source and selecting sampling time according to the interval of data points, and finally the set PID parameter is obtained.
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