CN112668516A - Automatic point-aligning acceptance check method for alarm window of power dispatching system - Google Patents
Automatic point-aligning acceptance check method for alarm window of power dispatching system Download PDFInfo
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Abstract
The invention discloses an automatic point-to-point acceptance method for an alarm window of a power dispatching system, which comprises the following steps: screenshot is carried out on a real-time alarm window of the power dispatching system; preprocessing the screenshot of the alarm window to obtain a window image of the next half of the point signal; identifying the window image of the lower half of the alarm window to identify the text information of each line of the alarm window; and judging whether the lower half column image character recognition result of the alarm window has the same or different information with the signal to be point-aligned, if so, the point alignment of the signal is correct, otherwise, the point alignment of the signal is failed. The automatic counter-point checking and accepting method of the alarm window can reduce the burden of workers, improve the working efficiency of counter-point checking and accepting and improve the correctness of counter-point and picture association.
Description
Technical Field
The invention belongs to the technical field of electric power dispatching system point-to-point acceptance, and particularly relates to an automatic point-to-acceptance method for an alarm window of an electric power dispatching system.
Background
With the continuous popularization of unattended substations, whether each stage of scheduling center can accurately monitor the governed substation in real time is a precondition for safe and stable operation of a power grid, and remote transmission area point table information of a scheduling master station and a plant station end needs to be checked to verify the instantaneity of signals and the consistency of data, so that the scheduling center can be ensured to correctly monitor the substation.
And the signal point alignment and acceptance of the main station side of the power dispatching system basically adopts an artificial verification mode. In the method, a dispatching master station worker contacts a substation end through a telephone and simultaneously manually corrects signal information in a real-time alarm window of a dispatching master station system. The method brings great workload to dispatching workers, is low in efficiency, is easy to generate careless omission, and brings hidden danger to the safety of a power grid.
Therefore, a more intelligent, more efficient and safer master station side alarm window point-to-point acceptance method needs to be researched, the burden of workers is reduced, the working efficiency of the alarm window point-to-point acceptance is improved, and the accuracy of point-to-point and picture association is improved.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method for automatically checking and accepting the alarm window of the power dispatching system is provided, and the problems in the prior art are solved.
The technical scheme adopted by the invention is as follows: an automatic point-aligning acceptance method for an alarm window of a power dispatching system comprises the following steps:
step 1, screenshot is carried out on a real-time alarm window of a power dispatching system;
step 2, preprocessing the screenshot of the alarm window, cutting and extracting a window image of the next half of a window of a point-to-point signal refreshed in real time in the screenshot of the alarm window;
The point-to-point signals are sequentially sent out at a fixed period by the plant station end according to the point table to be tested, and the automatic point-to-point checking and accepting method of the alarm window sequentially performs point-to-point checking and accepting according to the point table to be checked.
The screenshot of the alarm window in the step 1 is realized by simulating a keyboard and mouse, the screenshot of the alarm window is realized by automatically controlling the keyboard and mouse to operate, and the screenshot is stored in a regular name (a point number, action description and screenshot time) so as to be convenient for later calling and checking.
The alarm information checked by the alarm window for checking and accepting is the transformer station name, the signal action description and the signal character color of the signal, the transformer station name and the signal name of the alarm window signal are obtained from the known transformer station list information of the scheduling system, and the action description and the character color of the alarm window signal are obtained from the alarm window configuration description file WCD in the XML format.
The method comprises the steps of combing action Description and character color characteristics of an alarm window of a dispatching master station system to form an alarm window Configuration Description file (alarm window Configuration Description file) WCD (alarm window Configuration Description) adopting an XML format, wherein action Description of alarm window signals is divided into remote signaling value 0 Description and remote signaling value 1 Description, remote signaling value 0 Description in the alarm window Configuration Description file WCD file is set to be 'brake-off' and 'reset', remote signaling value 1 Description is set to be 'brake-on' and 'action', signal alarm levels are divided into accidents, abnormities, notices, overlimit and deflection and are related to colors of the signal characters in the alarm window, and RGB color parameters are set in the alarm window Configuration Description file WCD file to represent different signal alarm levels.
The method for identifying the signal characters and the colors thereof in the alarm window comprises the following steps:
step 1), reading a desktop screenshot file applied by a power dispatching system, calling a cvtColor function in OpenCV to convert a picture into a gray-scale image, setting a binarization threshold value to be 250, calling a threshold function of OpenCV to convert the gray-scale image into a binary image, setting a pixel value of a pixel gray value of more than 250 pixels in the image to be 1, and setting a pixel value of less than 250 in the image to be 0, thereby obtaining a binarization image; in the step, the interference area in the image is filtered through binarization, so that the contrast between the characters and the background is enhanced, and the character area is more obvious;
step 2), setting the size of an erosion kernel to be 2 x 2, calling an error function of OpenCV to perform erosion operation on the binaryzation processed picture, wherein the erosion operation can eliminate object boundary points, enable boundaries to shrink inwards, remove elements smaller than the size of the erosion kernel in the picture and eliminate small interference areas in the picture, thereby reducing the interference on profile search in the following steps and improving the speed of processing and searching the picture profile;
step 3), carrying out contour searching operation on the picture generated after the corrosion operation in the step 2), reserving two contours with the largest area and the second largest area, calculating the smallest external rectangle of the two contours by using a bounding rectangle function of OpenCV, and obtaining the top left corner vertex (x, y) and the length and width of the two rectangles;
step 4), corresponding the position of the minimum external rectangle to the picture in the step 3), taking the picture in the range of the two rectangles as two upper and lower regions to be identified, taking the vertex y with a small value at the upper left corner as an upper partial region, and taking the rectangle with a large value y as a lower partial region; the character area is obtained through contour detection and area filtering, so that the following steps of accurate character longitudinal projection and segmentation are possible;
step 5), respectively carrying out black pixel longitudinal projection on the determined binary images of the upper partial area and the lower partial area to obtain the number of black pixels in each row and form a longitudinal projection pixel number curve;
step 6), because the line pixels of the non-character part of the image are all white, the numerical value of the non-character part line after longitudinal projection is 0, a wave trough of a longitudinal projection pixel quantity curve is formed, and the wave trough position of the longitudinal projection pixel quantity curve graph is used as a character segmentation position; the segmentation position of the line character is obtained by projecting the trough position, and the segmentation accuracy of the line character is improved;
step 7), performing character segmentation on the upper and lower areas according to the character segmentation positions;
step 8), calculating the position of a central line of the segmented character picture, setting a threshold range of white color, and taking the color on the central line which is not in the range of the white threshold as the color of the character of the line; due to the screenshot characteristic of the scheduling master station system, the colors of the characters in each row are consistent, so that color taking is carried out at the position of the central line of the segmented character images in the rows, the white background color and the character colors mainly exist in the segmented character images in the rows, the threshold range of the white color is set, and the color on the central line which is not in the white threshold range is taken as the color of the character in the row; the method comprises the following steps of accurately obtaining the color of each line of characters through color filtering and reading;
and 9), calling an identification interface of tesseract to identify the regional characters.
The invention has the beneficial effects that: compared with the prior art, the invention has the following effects:
1) the invention adopts the character recognition technology to recognize the point-to-point signal information in the alarm window picture, thereby saving the manpower consumption of manpower for people, greatly improving the working efficiency, reducing the cost and avoiding the problem that the manual point-to-point mode is easy to make mistakes;
2) the invention adopts a key mouse simulation technology, can automatically control the key mouse to screen the alarm window picture, and saves the operation of manual screen-capturing;
3) the method self-defines the alarm window configuration description file WCD, has universality, and can deal with the point-to-point work of alarm window signals of scheduling systems of different manufacturers;
4) the point-to-point acceptance method program can be operated on a workstation computer of any scheduling system, does not have interface interaction such as communication and the like with the scheduling system, and does not have hidden dangers such as network safety and the like.
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FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a screenshot of a point table file xls to be measured;
FIG. 3 is a screenshot of the setup of an alarm window configuration description file WCD in the method;
FIG. 4 is an alert window screenshot.
Detailed Description
The invention is further described below with reference to specific figures and embodiments.
Example 1: as shown in fig. 1 to 4, an automatic point-to-point acceptance method for an alarm window of a power dispatching system includes the following steps:
step 1, screenshot is carried out on a real-time alarm window of a power dispatching system;
step 2, preprocessing the screenshot of the alarm window, cutting and extracting a window image of the next half of a bar of the point-to-point signal in the screenshot of the alarm window in real time, only cutting the screenshot, removing contents which do not need to be identified, conveniently identifying the signal, having less identification contents and high identification speed;
When the method is used, firstly, the table file xls of the point to be measured is imported, and as shown in FIG. 2, the name of the transformer station, the name of the signal and the sequence of the point table of the point to be measured are obtained. And then configuring an alarm window configuration description file WCD, as shown in FIG. 3, wherein the action description of the alarm window signal is divided into a remote signaling value 0 description and a remote signaling value 1 description, the remote signaling value 0 description in the WCD file is set as 'brake-off' and 'reset', and the remote signaling value 1 description is set as 'brake-on' and 'action'. The signal alarm grades are divided into accidents, abnormity, notification, out-of-limit and deflection, and are related to the color of signal characters in the alarm window. The WCD file may have RGB color parameters set to indicate different signal alarm levels. Through the alarm window configuration description file, the WCD can obtain the action description and the character color of the alarm window signal. The invention refers to the existing manual demand for point, extracts the information to be checked in the point process, expounds and standardizes the information of which measuring points need to be checked in the alarm window; the method does not check the point signals in the alarm window, self-defines the alarm window configuration description file WCD, has universality, and can deal with the point-to-point work of the alarm window signals of different factory dispatching systems;
when the point checking and accepting test is carried out, point signals are sequentially sent out at fixed periods by a plant station end according to a table to be tested, compared with the method for sending the point signals by the plant station end, the automatic point checking and accepting method for the alarm window has 2-second delay, and the delay is used for ensuring that the actual telecontrol signal data sent by the transformer station end is correctly sent to the dispatching master station system. The fixed time interval of checking the primary measuring point by the automatic point-checking acceptance method of the alarm window is 5s, and is the same as the sending interval of the terminal-to-point signals of the plant station. The order of the point list checked by the automatic point checking and accepting method of the alarm window is the same as the order of the point list sent by the factory station. The prior art means adopts a point-to-point tester device to test the point-to-point of a telecontrol device and a protection measurement and control device at the side of a transformer substation, and has the problems that: only the point-to-point signals of the substation side are checked, the point-to-point signals in the master station side scheduling system are not checked, and the point-to-point communication link is not complete. The method adopts identification of point-to-point signals in an alarm window, is carried out in a scheduling master station, firstly sends out the point-to-point signals in sequence on a transformer substation side, then sequentially checks the point-to-point signals in the alarm window in a scheduling system on the master station side, and the sent-out signals and the check signals are not related with each other but are synchronous in progress. The method has the advantages that point signals are sequentially sent out at a fixed period by a station end according to a point table to be measured, and the automatic point checking and accepting method of the alarm window sequentially carries out the setting of the point checking and accepting of the signals in the alarm window at the side of a dispatching main station according to the point table to be checked: and checking the integrity of a link of the point-to-point signal, wherein the link comprises a plant station side telecontrol device and a master station side scheduling system.
The screenshot of the alarm window in the step 1 is realized by simulating a keyboard and mouse, the screenshot of the alarm window is realized by automatically controlling the keyboard and mouse to operate, and the screenshot is stored in a regular name (point number, action description and screenshot time) so as to be convenient for later calling and checking, as shown in FIG. 4; and then preprocessing the screenshot of the alarm window, and clipping and extracting the window image of the next half of the window of the alarm window, which refreshes the point-to-point signal in real time. And then, recognizing the image of the lower half column of the alarm window by adopting text recognition of tesseract, and recognizing text information of each line (each signal) of the alarm window, wherein the text information comprises signal confirmation state, signal generation time, transformer station name, signal action description and signal text color (alarm level). The existing method does not check the point signals in the alarm window, and refers to a manual check mode. The screenshot is named regularly, so that the image file is called in a regular format when the image is identified conveniently, and when the point is wrong, the current screenshot file of the alarm window can be quickly searched according to the point number.
The method for identifying the signal characters and the colors thereof in the alarm window comprises the following steps:
step 1), reading a desktop screenshot file applied by a power dispatching system, calling a cvtColor function in OpenCV to convert the image into a gray-scale image, setting a binarization threshold value as 250, and calling a threshold function of the OpenCV to convert the gray-scale image into a binary image;
step 2), setting the size of a corrosion kernel to be 2 x 2, calling an error function of OpenCV to perform corrosion operation on the binaryzation processed picture, eliminating a small interference area in the picture, and improving the speed of contour searching and processing;
step 3), carrying out contour searching operation on the picture generated after the corrosion operation in the step 2), reserving two contours with the largest area and the second largest area, calculating the smallest external rectangle of the two contours by using a bounding rectangle function of OpenCV, and obtaining the top left corner vertex (x, y) and the length and width of the two rectangles;
step 4), corresponding the position of the minimum external rectangle to the picture in the step 3), taking the picture in the range of the two rectangles as two upper and lower regions to be identified, taking the vertex y with a small value at the upper left corner as an upper partial region, and taking the rectangle with a large value y as a lower partial region;
step 5), respectively carrying out black pixel longitudinal projection on the determined binary images of the upper partial area and the lower partial area to obtain the number of black pixels in each row and form a longitudinal projection pixel number curve;
step 6), taking the trough position of the longitudinal projection pixel number curve graph as a character segmentation position;
step 7), performing character segmentation on the upper and lower areas according to the character segmentation positions;
step 8), calculating the position of a central line of the segmented character picture, setting a threshold range of white color, and taking the color on the central line which is not in the range of the white threshold as the color of the character of the line;
and 9), calling an identification interface of tesseract to identify the regional characters.
Step 10), setting a character misrecognition adjustment list, wherein the adjustment list is stored in a text file, and the format of each line is as follows:
wrong phrase and correct phrase
Step 11), replacing the wrong phrase with the correct phrase according to the content of the adjustment list, and improving the accuracy rate of character recognition;
and 12), combining the characters and the colors identified in the steps 8) and 9) into a list to be output, and completing the segmentation and processing of the front picture.
The method solves the problem how to extract the attention area of the user on the front interface, and realizes the automatic segmentation adjustment of the area through an image preprocessing technology, a thresholding technology, a connected domain detection technology and a binarization image projection technology;
the invention solves the problems of the character line segmentation and color identification method after extracting the attention area, ensures the accuracy of the character line segmentation by the longitudinal projection segmentation technology of the binary character, and realizes the accuracy of the color identification by filtering and reading the color threshold of the segmentation area.
The invention realizes automatic screen capture of the alarm window picture and automatic identification and judgment of the signal characters in the alarm window picture by a keyboard and mouse simulation technology and a character identification technology, and improves the point-to-point acceptance check efficiency and the intelligent operation level of the alarm window at the master station end.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present invention, and therefore, the scope of the present invention should be determined by the scope of the claims.
Claims (6)
1. An automatic point-aligning acceptance method for an alarm window of a power dispatching system is characterized by comprising the following steps: the method comprises the following steps:
step 1, screenshot is carried out on a real-time alarm window of a power dispatching system;
step 2, preprocessing the screenshot of the alarm window, cutting and extracting a window image of the next half of a window of a point-to-point signal refreshed in real time in the screenshot of the alarm window;
step 3, recognizing the lower half-bar window image of the alarm window by adopting text recognition of tesseract, and recognizing text information of each line of the alarm window, wherein the text information comprises signal confirmation state, signal generation time, transformer station name, signal action description and signal text color;
step 4, inquiring whether the image character recognition result of the lower half column of the alarm window has the information which is the same as the point signal description to be aligned: if the identification result has the same information as the point signal to be aligned, the point is aligned correctly by the signal; if the identification result is not the same as the point aligning signal, the point aligning is failed by the signal.
2. The automatic point-to-point acceptance method for the alarm window of the power dispatching system according to claim 1, characterized in that: the point-to-point signals are sequentially sent out at a fixed period by the station side according to the point table to be measured, and the automatic point-to-point checking and accepting method of the alarm window sequentially performs point-to-point checking and accepting of the signals in the alarm window on the scheduling main station side according to the point table to be checked.
3. The automatic point-to-point acceptance method for the alarm window of the power dispatching system according to claim 1, characterized in that: and (3) the screenshot of the alarm window in the step 1 is realized by simulating a keyboard and a mouse, the screenshot of the alarm window is realized by automatically controlling the keyboard and the mouse to operate, and the screenshot is stored in a regular name.
4. The automatic point-to-point acceptance method for the alarm window of the power dispatching system according to claim 1, characterized in that: the alarm information checked by the alarm window for checking and accepting is the transformer station name, the signal action description and the signal character color of the signal, the transformer station name and the signal name of the alarm window signal are obtained from the known transformer station list information of the scheduling system, and the action description and the character color of the alarm window signal are obtained from the alarm window configuration description file WCD in the XML format.
5. The automatic point-to-point acceptance method for the alarm window of the power dispatching system according to claim 1, characterized in that: the method comprises the steps of combing action description and character color characteristics of an alarm window of a scheduling master station system to form an alarm window configuration description file WCD adopting an XML format, wherein the action description of alarm window signals is divided into remote signaling value 0 description and remote signaling value 1 description, the remote signaling value 0 description in the alarm window configuration description file WCD file is set to be 'brake-off' and 'reset', the remote signaling value 1 description is set to be 'brake-on' and 'motion', the signal alarm grades are divided into accidents, abnormity, notification, threshold crossing and deflection and are related to the colors of the signal characters in the alarm window, and RGB color parameters are set in the alarm window configuration description file WCD file to represent different signal alarm grades.
6. The automatic point-to-point acceptance method for the alarm window of the power dispatching system according to claim 1, characterized in that: the method for identifying the signal characters and the colors thereof in the alarm window comprises the following steps:
step 1), reading a desktop screenshot file applied by a power dispatching system, calling a cvtColor function in OpenCV to convert the image into a gray-scale image, setting a binarization threshold value as 250, and calling a threshold function of the OpenCV to convert the gray-scale image into a binary image;
step 2), setting the size of an etching kernel to be 2 x 2, and calling an error function of OpenCV to perform etching operation on the binaryzation processed picture;
step 3), carrying out contour searching operation on the picture generated after the corrosion operation in the step 2), reserving two contours with the largest area and the second largest area, calculating the smallest external rectangle of the two contours by using a bounding rectangle function of OpenCV, and obtaining the top left corner vertex (x, y) and the length and width of the two rectangles;
step 4), corresponding the position of the minimum external rectangle to the picture in the step 3), taking the picture in the range of the two rectangles as two upper and lower regions to be identified, taking the vertex y with a small value at the upper left corner as an upper partial region, and taking the rectangle with a large value y as a lower partial region;
step 5), respectively carrying out black pixel longitudinal projection on the determined binary images of the upper partial area and the lower partial area to obtain the number of black pixels in each row and form a longitudinal projection pixel number curve;
step 6), taking the trough position of the longitudinal projection pixel number curve graph as a character segmentation position;
step 7), performing character segmentation on the upper and lower areas according to the character segmentation positions;
step 8), calculating the position of a central line of the segmented character picture, setting a threshold range of white color, and taking the color on the central line which is not in the range of the white threshold as the color of the character of the line;
and 9), calling an identification interface of tesseract to identify the regional characters.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113256766A (en) * | 2021-07-13 | 2021-08-13 | 国网浙江省电力有限公司宁波供电公司 | Method and device for acquiring power graphic picture, storage medium and electronic equipment |
| CN113256766B (en) * | 2021-07-13 | 2021-11-16 | 国网浙江省电力有限公司宁波供电公司 | Method and device for acquiring power graphic picture, storage medium and electronic equipment |
| CN114371654A (en) * | 2021-12-10 | 2022-04-19 | 中国民用航空华东地区空中交通管理局 | Artificial intelligence simulation monitoring system |
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