CN113657363A - Intelligent substation anti-misoperation method and system - Google Patents
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Abstract
The invention discloses an intelligent substation anti-misoperation method and system, wherein the method comprises the following steps: step 1: retrieving a corresponding operation ticket from a database of the background server, and waiting for a returned real-time signboard image according to an operation sequence in the operation ticket; step 2: before an operator operates, acquiring a signboard image at the current position, and sending the acquired signboard image to a background server; and step 3: the background server receives and carries out image processing on the signboard image so as to identify the signboard image information, determines the working position of the current operator, and compares the position information with the position information required by the operation sequence; and 4, step 4: if the two position information are consistent, the background server sends an unlocking command to the access control equipment, and an operator can execute subsequent operation; and 5: and after the operation is finished, the operator sends a finishing instruction to the background server, and then the steps 2 to 4 are repeated until all the operation instructions in the operation ticket are finished.
Description
Technical Field
The invention belongs to the technical field of power systems, and particularly relates to an intelligent substation anti-misoperation method and system.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The transformer substation is an important component of an electric power system and is responsible for important tasks such as voltage class conversion, load input/load removal and the like. Because the devices such as circuit breakers, isolating switches, grounding isolating switches and the like in the transformer substation are numerous, if the devices are not operated properly, misoperation accidents are likely to occur, large-area power failure, device damage and even casualties are caused, and therefore the reduction or elimination of misoperation of the transformer substation is of great significance.
The five-prevention system is generally adopted at present to prevent misoperation accidents of the transformer substation, the key principle of the system is to carry out computerized management on all lockset keys of the transformer substation, and although the five-prevention system of the transformer substation can reduce errors of operators, misoperation accidents of the transformer substation are still happened. Analysis shows that most of the accidents occur because the operators enter wrong intervals of the substation operation cabinets to operate when the operators receive the operation tickets to operate the intelligent substations, thereby causing misoperation. Therefore, how to solve the potential safety hazard caused by the fact that an operator enters a wrong transformer substation operation cabinet interval to perform an operation task is a problem to be solved urgently at present.
Disclosure of Invention
In order to solve the problems, the invention provides an intelligent substation misoperation prevention method and system, which are characterized in that an image of a signboard at the current position of an operator is acquired, the acquired image is processed and analyzed to determine whether the current position of the operator is consistent with the correct position of an operation sequence in an operation ticket, if the current position of the operator is consistent with the correct position of the operation sequence in the operation ticket, the operator is allowed to perform operation work, and if the current position of the operator is inconsistent with the correct position of the operation sequence in the operation ticket, the operator is reminded that the operator cannot perform the next operation work, so that the operator is ensured to perform operation work at the correct substation operation cabinet interval.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides an intelligent substation anti-misoperation method, which adopts the following technical scheme:
step 1: retrieving a corresponding operation ticket from a database of the background server, and waiting for a returned real-time signboard image according to an operation sequence in the operation ticket;
step 2: before an operator operates, firstly, acquiring a signboard image at the current position, and sending the acquired signboard image to a background server;
and step 3: the background server receives and carries out image processing on the signboard image so as to identify the signboard image information, determines the working position of the current operator, and compares the position information with the position information required by the operation sequence;
and 4, step 4: if the two position information are consistent, the background server sends an unlocking command to the access control equipment, and an operator can execute subsequent operation;
and 5: and after the operation is finished, the operator sends a finishing instruction to the background server, and then the steps 2 to 4 are repeated until all the operation instructions in the operation ticket are finished.
One or more embodiments provide an intelligent substation anti-misoperation system, including:
the image acquisition unit is used for acquiring the signboard image before the operation task of an operator and sending the signboard image to the image processing unit;
the image processing unit is used for carrying out image frame positioning, image up-down segmentation and character segmentation on the acquired signboard image;
and the position information identification unit is used for carrying out character judgment on the signboard characters through a neural network so as to determine whether the acquired signboard information is consistent with the target image information, if so, an unlocking command is sent, and if not, the locking state is kept.
An electronic device comprising a memory and a processor and computer instructions stored on the memory and executed on the processor, the computer instructions, when executed by the processor, performing the steps of the above method.
A computer readable storage medium storing computer instructions which, when executed by a processor, perform the steps of the above method.
The invention has the beneficial effects that:
in the invention, an operator firstly carries out image acquisition on the signboard of the compartment to be operated, and determines the current position of the operator by comparing the image information acquired by the operator with the target image information of the operation sequence in the operation ticket, thereby avoiding the operator from entering the wrong transformer substation operation cabinet compartment for operation and further improving the safety of transformer substation operation.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a flow chart of the present invention;
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
Example one
As shown in fig. 1, the method for preventing misoperation of the intelligent substation of the invention comprises the following steps:
step 1: retrieving a corresponding operation ticket from a database of the background server, and waiting for a returned real-time signboard image according to an operation sequence in the operation ticket;
step 2: before an operator operates, firstly, acquiring a signboard image at the current position, and sending the acquired signboard image to a background server;
and step 3: the background server receives and carries out image processing on the signboard image so as to identify the signboard image information, determines the working position of the current operator, and compares the position information with the position information required by the operation sequence;
and 4, step 4: if the two position information are consistent, the background server sends an unlocking command to the access control equipment, and an operator can execute subsequent operation;
and 5: and after the operation is finished, the operator sends a finishing instruction to the background server, and then the steps 2 to 4 are repeated until all the operation instructions in the operation ticket are finished.
Further, the method also comprises the following steps: and if the position of the current operator is inconsistent with the position information required by the operation sequence in the operation ticket, the corresponding access control equipment is in a locked state, and the operator is prompted to suspend the current operation state.
In the step 2, the device for image acquisition by the operator communicates with the background server through a wireless network.
In the step 3, the background server performs image processing on the signboard image, including frame positioning, image up-and-down segmentation and character segmentation on the image;
the frame positioning of the signboard image comprises the positioning of the left and right boundaries and the positioning of the upper and lower boundaries of the image.
The specific steps of positioning the left and right boundaries of the signboard include:
1) and (4) carrying out edge detection on the signboard image, and obtaining an edge binarization image by adopting an improved canny edge algorithm.
2) And (5) performing left and right straight line processing on the edge binary image by hough transformation to detect left and right straight lines meeting requirements.
Among them, detecting right and left straight lines meeting the requirements may be: and the straight line with the length larger than the height 1/2 of the edge binary image, the angle of the left half part of the edge binary image is between 40 and 90 degrees, and the angle of the right half part of the edge binary image is between 80 and 130 degrees.
3) Dividing the detected left and right straight lines into a left part and a right part, finding out the longest straight line in the left half part, setting the width position corresponding to the longest straight line in the left half part as the left boundary of the signboard image, finding out the longest straight line in the right half part, setting the width position corresponding to the longest straight line as the right boundary of the signboard image, and outputting the signboard image with the left and right boundaries repositioned.
The specific steps of positioning the upper and lower boundaries of the signboard include:
1) horizontally projecting the image of the signboard to obtain the gray sum of each line and obtain a curve;
2) then, carrying out first-order derivation on the gray sum of each line to obtain a curve related to a first-order derivative;
3) further, carrying out second-order derivation on the gray sum to obtain a curve related to a second-order derivative;
4) obtaining the upper boundary of the signboard image according to the obtained characteristics of the gray scale and the curve and the gray scale and the first derivative curve;
5) and obtaining the lower boundary of the signboard image according to the characteristics in the gray scale and the first derivative curve as well as the gray scale and the second derivative curve.
The frame of the signboard is determined by positioning the left and right boundaries and the upper and lower boundaries of the signboard image.
The method for vertically dividing the signboard image comprises the following specific steps:
1) and carrying out binarization processing on the signboard image with the determined frame.
2) An array a is created, the length of which depends on the values of the pixels in the signboard row.
3) And scanning the signboard, and storing the number of black pixel points in the ith row in the array element ai.
4) And finding element jumping points in the array a [ i ], and finding the row information of the upper part character and the lower part character in the image according to the information.
5) And obtaining the central position of the blank area between the upper character and the lower character.
The step of character segmenting the image comprises:
1) the arrays a, b, and c are established. The length of the array a is the image width after the positioning of the signboard frame, and the lengths of the arrays b and c are the maximum number of partial characters on the signboard in the image library. The image library is the images of all the statistical signboards, and the maximum number of the partial characters on the signboards can be obtained by counting the images of all the signboards.
2) And vertically projecting the upper part of the signboard to obtain a projection drawing, and storing the number of black pixel points in the ith row into an array element ai.
3) And finding the jumping points of the elements in the array a [ ], sequentially storing the coordinates from the blank area to the character area into an array b [ ], and storing the coordinates from the character area to the blank area into an array c [ ], wherein b [ i ] and c [ i ] are left and right boundaries of line coordinates of the ith character in the image.
4) And (3) scanning the upper part of the signboard by taking the c [ i ] and the b [ i ] as the upper and lower boundaries, and finding the upper and lower boundaries of the column coordinates of the ith character of the upper part in the picture.
5) And similarly, the lower part of the signboard is subjected to character segmentation.
In the step 3, the characters obtained after the image processing is carried out on the signboard images collected in the step 3 are sequentially connected, and the image matching is carried out through an artificial neural network, wherein a BP neural network can be adopted, and the BP neural network method is an artificial neural network method which adopts a reverse error propagation algorithm to convert the pattern recognition problem into a nonlinear optimization problem. The method can thus achieve a continuous non-linear mapping between its input and output variables.
In the embodiment, a 3-layer BP neural network including an input layer, an output layer and a hidden layer is designed, a character image is normalized into 32 × 32 pixels, and an array with the length of 1024 formed by the pixels is used as input. And (3) giving a 7-bit binary code to each character as output, and extracting character image information of all the signboards as samples to train the neural network.
The character image obtained after the character segmentation is normalized into 32 multiplied by 32 pixels and input to a trained neural network, the output value is the binary code of the character, so that the character is recognized, after all the characters are recognized, the character information in the original image can be obtained, and then the character information is compared with the target image to determine whether the current position sent by an operator is consistent with the position information of the operation sequence in the operation order.
In the step 4, if the current position information of the operator is consistent with the position information of the sequential operation in the operation ticket, the background server sends the unlocking instruction to the access control device, and the operator can perform subsequent operation.
Example two
This embodiment provides an intelligent substation prevents mistake operating system, and it includes:
the image acquisition unit is used for acquiring the signboard image before the operation task of an operator and sending the signboard image to the image processing unit;
the image processing unit is used for carrying out image edge detection, image up-down segmentation and character segmentation on the acquired signboard image;
and the position information identification unit is used for carrying out character judgment on the signboard characters through a neural network so as to determine whether the acquired signboard information is consistent with the target image information, if so, an unlocking command is sent, and if not, the locking state is kept.
EXAMPLE III
The embodiment provides a computer-readable storage medium, on which a computer program is stored, and the program, when executed by a processor, implements the steps in the method for preventing misoperation of an intelligent substation according to the first embodiment.
Example four
The embodiment provides a computer device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to implement the steps in the intelligent substation misoperation prevention method according to the first embodiment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An anti-misoperation method of an intelligent substation is characterized by comprising the following steps:
step 1: retrieving a corresponding operation ticket from a database of the background server, and waiting for a returned real-time signboard image according to an operation sequence in the operation ticket;
step 2: before an operator operates, firstly, acquiring a signboard image at the current position, and sending the acquired signboard image to a background server;
and step 3: the background server receives and carries out image processing on the signboard image so as to identify the signboard image information, determines the working position of the current operator, and compares the position information with the position information required by the operation sequence;
and 4, step 4: if the two position information are consistent, the background server sends an unlocking command to the access control equipment, and an operator can execute subsequent operation;
and 5: and after the operation is finished, the operator sends a finishing instruction to the background server, and then the steps 2 to 4 are repeated until all the operation instructions in the operation ticket are finished.
2. The intelligent substation anti-misoperation method according to claim 1, further comprising the steps of:
and if the position of the current operator is inconsistent with the position information required by the operation sequence, the corresponding access control equipment is in a locking state, and meanwhile, the operator is reminded to suspend the current operation state.
3. The intelligent substation anti-misoperation method according to claim 1, wherein the background server performs image processing on the signboard image, and the image processing comprises image frame positioning, image up-down segmentation and character segmentation.
4. The intelligent substation anti-misoperation method according to claim 1, wherein the positioning of the image frame comprises positioning of left and right boundaries of the image and positioning of upper and lower boundaries of the image.
5. The intelligent substation anti-misoperation method according to claim 4, wherein the specific step of positioning the left and right boundaries of the image comprises:
carrying out edge detection on the signboard image, and obtaining an edge binarization image by adopting a canny edge algorithm;
carrying out left and right straight line processing on the edge binary image by hough transformation, and detecting left and right straight lines meeting requirements;
the detected left and right straight lines are divided into left and right parts, the longest straight line in the left and right parts is found out, the corresponding width position is set as the left and right boundaries of the signboard image, and the outputted left and right boundaries are repositioned to the signboard image.
Or
The specific steps of positioning the upper and lower boundaries of the image include:
horizontally projecting the image of the signboard to obtain the gray sum of each line and obtain a curve;
then, carrying out first-order derivation on the gray sum of each line to obtain a curve related to a first-order derivative;
carrying out second-order derivation on the gray sums to obtain a curve related to a second-order derivative;
obtaining the upper boundary of the signboard image according to the obtained characteristics of the gray scale and the curve and the gray scale and the first derivative curve;
and obtaining the lower boundary of the signboard image according to the characteristics in the gray scale and the first derivative curve as well as the gray scale and the second derivative curve.
6. The intelligent substation anti-misoperation method according to claim 3, wherein the image is subjected to character segmentation by a projection method.
7. The intelligent substation anti-misoperation method according to claim 1, wherein the consistency of the two position information is determined by identifying the sign characters by adopting a neural network.
8. An intelligent substation anti-misoperation system applied to the intelligent substation anti-misoperation method according to any one of claims 1-7, is characterized by comprising the following steps:
the image acquisition unit is used for acquiring the signboard image before the operation task of an operator and sending the signboard image to the image processing unit;
the image processing unit is used for carrying out image frame positioning, image up-down segmentation and character segmentation on the acquired signboard image;
and the position information identification unit is used for carrying out character judgment on the signboard characters through a neural network so as to determine whether the acquired signboard information is consistent with the target image information, if so, an unlocking command is sent, and if not, the locking state is kept.
9. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the steps of the method for preventing misoperation of an intelligent substation according to any one of claims 1 to 7.
10. A processing apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps in the smart substation anti-misoperation according to any one of claims 1-7.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202004896U (en) * | 2010-12-07 | 2011-10-05 | 河南省电力公司焦作供电公司 | Anti-misoperation intelligent visual recognition system |
| CN102547215A (en) * | 2010-12-07 | 2012-07-04 | 河南省电力公司焦作供电公司 | Intelligent visual identification system capable of preventing wrong operation |
| CN106355175A (en) * | 2016-10-13 | 2017-01-25 | 国网江苏省电力公司检修分公司 | Transformer substation incorrect operation prevention method based on image recognition technology |
| CN109300125A (en) * | 2018-09-21 | 2019-02-01 | 苏州塞弗瑞智能装备有限公司 | Municipal rail train pantograph pan image zooming-out algorithm under a kind of complex environment |
| CN109687581A (en) * | 2018-12-20 | 2019-04-26 | 国网北京市电力公司 | Method, apparatus, storage medium and the processor of Anti-maloperation for Substation |
| CN112508022A (en) * | 2020-09-23 | 2021-03-16 | 国网浙江省电力有限公司绍兴供电公司 | Transformer substation anti-misoperation system and method based on operation and inspection operation full process |
-
2021
- 2021-07-29 CN CN202110865044.0A patent/CN113657363A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202004896U (en) * | 2010-12-07 | 2011-10-05 | 河南省电力公司焦作供电公司 | Anti-misoperation intelligent visual recognition system |
| CN102547215A (en) * | 2010-12-07 | 2012-07-04 | 河南省电力公司焦作供电公司 | Intelligent visual identification system capable of preventing wrong operation |
| CN106355175A (en) * | 2016-10-13 | 2017-01-25 | 国网江苏省电力公司检修分公司 | Transformer substation incorrect operation prevention method based on image recognition technology |
| CN109300125A (en) * | 2018-09-21 | 2019-02-01 | 苏州塞弗瑞智能装备有限公司 | Municipal rail train pantograph pan image zooming-out algorithm under a kind of complex environment |
| CN109687581A (en) * | 2018-12-20 | 2019-04-26 | 国网北京市电力公司 | Method, apparatus, storage medium and the processor of Anti-maloperation for Substation |
| CN112508022A (en) * | 2020-09-23 | 2021-03-16 | 国网浙江省电力有限公司绍兴供电公司 | Transformer substation anti-misoperation system and method based on operation and inspection operation full process |
Non-Patent Citations (2)
| Title |
|---|
| 乐健: "基于图像识别技术的变电站防误操作***的研制", 电力自动化设备, vol. 31, no. 7, pages 131 - 135 * |
| 魏伟明等: "一种基于图像文字识别的变电站防误操作***", 浙江电力, vol. 40, no. 1, pages 18 - 22 * |
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