CN117804337A

CN117804337A - Transformer coil size determining method, device, equipment and storage medium

Info

Publication number: CN117804337A
Application number: CN202311845423.9A
Authority: CN
Inventors: 孙蔡霞; 何铭仪; 许江华; 卢天华; 倪军
Original assignee: Hangzhou AIMS Intelligent Technology Co Ltd
Current assignee: Hangzhou AIMS Intelligent Technology Co Ltd
Priority date: 2023-12-28
Filing date: 2023-12-28
Publication date: 2024-04-02

Abstract

The invention discloses a method, a device, equipment and a storage medium for determining the size of a transformer coil. Comprising the following steps: determining acquisition parameters of a line laser camera, and detecting a transformer coil based on the acquisition parameters to acquire point cloud data; preprocessing the point cloud data to generate standard data; size information of the transformer coil is determined from the standard data. Through confirming line laser camera's collection parameter, including target frequency and collection scope, detect the coil outer lane boundary surface based on collection parameter, can acquire the point cloud data, then carry out preliminary treatment to the point cloud data, with the point cloud data conversion ellipse-like body form, and then generate standard data, at last, substituting standard data into appointed algorithm, combine the deviation parameter simultaneously, can confirm the size of transformer coil, improved whole measurement accuracy when having avoided the deviation influence, and the mounted position of camera can not exert an influence to production process, reduced manual work load, improved measurement efficiency.

Description

Transformer coil size determining method, device, equipment and storage medium

Technical Field

The present invention relates to the field of vision measurement technologies, and in particular, to a method, an apparatus, a device, and a storage medium for determining a size of a transformer coil.

Background

In the development of intelligent industry, more and more products are developing from manual detection to automatic detection, and vision-based measurement schemes are mature in the detection industry at present. For the detection of non-planar objects, three-dimensional imaging techniques such as time of flight (TOF), stereo vision, structured light and digital fringe projection techniques are commonly employed.

In the prior art, the dimension measurement of the coil in the coil winding process is mainly performed manually by adopting a flexible rule. Because in the production process, the mode efficiency of manually measuring by adopting the flexible rule is low and difficult, and meanwhile, the whole three-dimensional imaging of the coil cannot be directly measured and analyzed by directly using the structured light camera.

Disclosure of Invention

The invention provides a method, a device, equipment and a storage medium for determining the size of a transformer coil, which take measurement deviation into consideration, improve the overall measurement accuracy and ensure the measurement efficiency.

According to an aspect of the present invention, there is provided a transformer coil size determining method including:

determining acquisition parameters of a line laser camera, and detecting a transformer coil based on the acquisition parameters to acquire point cloud data, wherein the acquisition parameters comprise target frequency and an acquisition range;

preprocessing the point cloud data to generate standard data;

size information of the transformer coil is determined from the standard data.

Optionally, determining the acquisition parameters of the line laser camera includes: acquiring a target rotation speed of a central shaft of a transformer coil; acquiring a preset acquisition frequency list, wherein the acquisition frequency list comprises the corresponding relation between each rotation speed and frequency; matching the target rotation speed through the acquisition frequency list to acquire a target frequency corresponding to the target rotation speed; and acquiring camera calibration parameters, determining a measurement effective area of the line laser camera according to the camera calibration parameters, and taking the measurement effective area as an acquisition range.

Optionally, preprocessing the point cloud data to generate standard data includes: inputting the point cloud data into a preset software algorithm; the point cloud data is converted into an ellipsoid-like morphology based on a software algorithm to generate standard data.

Optionally, determining the size information of the transformer coil according to the standard data includes: obtaining a calibration distance, and determining an adjacent wave peak value and an adjacent wave trough value from standard data, wherein the calibration distance is the distance from a line laser camera to a central axis of a transformer coil; substituting the calibrated distance and the adjacent peak value into a first appointed algorithm to determine a short-axis pixel value; substituting the calibrated distance and the adjacent trough value into a second designated algorithm to determine a long-axis pixel value; and determining the size information of the transformer coil according to the short-axis pixel value and the long-axis pixel value.

Optionally, determining the size information of the transformer coil according to the short-axis pixel value and the long-axis pixel value includes: acquiring the coil core size of a transformer coil; substituting the coil core size, the short axis pixel value and the long axis pixel value into a third specified algorithm to determine pixel equivalent; determining a deviation parameter, wherein the deviation parameter comprises a deviation angle and a mutation deviation value; and determining the size information according to the pixel equivalent, the deviation parameter, the calibration distance, the adjacent wave peak value and the adjacent wave trough value.

Optionally, determining the deviation parameter includes: acquiring rotation center data through a shooting device at a designated position; when the difference value of two adjacent rotation center data is larger than a preset threshold value, taking the rotation center data as abrupt change data; determining mutation deviation values corresponding to the mutation data; determining an actual central axis corresponding to the ellipse-like body shape, and acquiring the shooting direction of the line laser camera; the angle between the shooting direction and the actual central axis is taken as the deviation angle.

Optionally, determining the size information according to the pixel equivalent, the deviation parameter, the calibration distance, the adjacent peak value and the adjacent trough value includes: substituting the pixel equivalent, the deviation parameter, the calibration distance and the adjacent peak value into a fourth specified algorithm to determine a short-axis actual value; substituting the pixel equivalent, the deviation parameter, the calibration distance and the adjacent trough value into a fifth specifying algorithm to determine a major axis actual value; the short axis actual value and the long axis actual value are taken as size information.

According to another aspect of the present invention, there is provided a transformer coil sizing device, the device comprising:

the system comprises a point cloud data acquisition module, a power transformer coil acquisition module and a power transformer coil acquisition module, wherein the point cloud data acquisition module is used for determining acquisition parameters of a line laser camera and detecting the power transformer coil based on the acquisition parameters to acquire point cloud data, and the acquisition parameters comprise target frequency and an acquisition range;

the point cloud data preprocessing module is used for preprocessing the point cloud data to generate standard data;

and the coil size information determining module is used for determining the size information of the transformer coil according to the standard data.

According to another aspect of the present invention, there is provided an electronic apparatus including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform a method of determining a size of a transformer coil according to any one of the embodiments of the present invention.

According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement a method for determining a size of a transformer coil according to any one of the embodiments of the present invention when executed.

According to the technical scheme, the acquisition parameters of the line laser camera, including the target frequency and the acquisition range, are determined, the outermost boundary surface of the coil is detected based on the acquisition parameters, point cloud data can be obtained, then the point cloud data are preprocessed to be converted into an ellipsoid-like shape, standard data are generated, the standard data are substituted into a specified algorithm, and meanwhile, the deviation parameters are combined, so that the size of the transformer coil can be determined, the influence of the deviation is avoided, the overall measurement precision is improved, the installation position of the camera does not influence the production process, the manual workload is reduced, and the measurement efficiency is improved.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flowchart of a method for determining a size of a coil of a transformer according to a first embodiment of the present invention;

fig. 2 is a flowchart of another method for determining the size of a coil of a power transformer according to a first embodiment of the invention;

fig. 3 is a flowchart of another method for determining the coil size of a power transformer according to the second embodiment of the present invention;

fig. 4 is a schematic structural view of a transformer coil size determining device according to a third embodiment of the present invention;

fig. 5 is a schematic structural diagram of an electronic device implementing a method for determining a size of a transformer coil according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

Fig. 1 is a flowchart of a method for determining a size of a transformer coil according to an embodiment of the present invention, where the method may be performed by a transformer coil size determining device, which may be implemented in hardware and/or software, and the transformer coil size determining device may be configured in a computer controller. As shown in fig. 1, the method includes:

s110, determining acquisition parameters of the line laser camera, and detecting a transformer coil based on the acquisition parameters to acquire point cloud data, wherein the acquisition parameters comprise target frequency and an acquisition range.

In the process of detecting the transformer coil, a line laser camera is a common detection device. The line laser camera acquires three-dimensional information of an object by emitting a laser beam and receiving reflected light. In the detection of transformer coils using line laser cameras, acquisition parameters, including target frequency and acquisition range, need to be determined. The target frequency refers to the frequency of the laser beam emitted by the line laser camera, and the acquisition range refers to the field of view of the line laser camera.

Specifically, the transformer coil is detected based on the acquisition parameters, so that point cloud data can be acquired. The point cloud data is a three-dimensional data set composed of a large number of points, each of which contains coordinate information and reflection intensity information of the point. By analyzing these points, the size information of the transformer coil can be obtained.

S120, preprocessing the point cloud data to generate standard data.

By preprocessing the point cloud data, standard data, namely processed point cloud data, can be generated, and the data can be used for subsequent analysis and processing.

Specifically, three-dimensional modeling software or a computer vision algorithm can be used for processing the point cloud data to remove noise and abnormal values in the point cloud data, and meanwhile, smoothing and filtering processing can be performed on the data to improve the quality and the accuracy of the data. In addition, in converting the point cloud data into an ellipsoid-like morphology, it can be implemented using mathematical models and geometric transformation algorithms. For example, the shape and size of an ellipsoid can be described by using an elliptic equation, and then converted into an ellipsoid-like morphology by performing coordinate transformation and interpolation processing on point cloud data. By converting the point cloud data into an ellipsoid-like morphology, subsequent analysis and processing may be facilitated.

It should be noted that there are many methods for preprocessing the point cloud data, and the specific method to be selected depends on the characteristics and application scenario of the point cloud data. In practical applications, a suitable pretreatment method may need to be selected according to specific situations so as to obtain better treatment effects and precision.

S130, determining the size information of the transformer coil according to the standard data.

Wherein the size information of the transformer coil is determined from the standard data. By analyzing the standard data, the major axis actual value and the minor axis actual value of the transformer coil can be obtained. Such dimensional information may be used in the design, manufacture, and maintenance of transformers.

Fig. 2 is a flowchart of a method for determining a coil size of a transformer according to an embodiment of the invention, and step S130 mainly includes steps S131 to S137 as follows:

s131, obtaining a calibration distance, and determining an adjacent wave peak value and an adjacent wave trough value from standard data, wherein the calibration distance is the distance from the line laser camera to the central axis of the transformer coil.

Specifically, first, a calibration distance from the line laser camera to the central axis of the transformer coil needs to be determined. For example, a parallel line passing through the center point of the camera can be used as the central axis of the coil, and the calibration distance is the distance from the base line of the line laser camera to the central axis of the transformer coil. Further, from the standard data, adjacent peak values and adjacent valley values may be determined, which values represent the contour characteristics of the transformer coil.

S132, substituting the calibration distance and the adjacent peak value into a first specified algorithm to determine a short-axis pixel value.

Specifically, the first specified algorithm is a mathematical formula or algorithm for calculating the short axis pixel value, expressed by the following formula (1):

H _{short shaft} ＝2×Hr-H3-H4 (1)

Wherein H is _{Short shaft} And (3) representing a short-axis pixel value, wherein Hr represents a calibration distance, H3 and H4 represent adjacent wave peak values, and substituting the calibration distance and the adjacent wave peak values into a first specified algorithm to determine the short-axis pixel value.

S133, substituting the calibrated distance and the adjacent trough value into a second designated algorithm to determine the long-axis pixel value.

Specifically, the second specified algorithm is a mathematical formula or algorithm for calculating the long axis pixel value, expressed by the following formula (2):

H _{long axis} ＝2×Hr-H1-H2 (2)

Wherein H is _{Long axis} And (3) representing a long-axis pixel value, wherein Hr represents a calibration distance, H1 and H2 represent adjacent trough values, and substituting the calibration distance and the adjacent trough values into a second specification algorithm to determine the long-axis pixel value.

S134, obtaining the coil core size of the transformer coil.

Specifically, the coil core size of the transformer coil needs to be obtained first, which can be accomplished by directly measuring or referring to the related design drawing.

S135, substituting the coil core size, the short-axis pixel value, and the long-axis pixel value into a third specified algorithm to determine the pixel equivalent.

Specifically, the pixel equivalent indicates the actual size represented by each pixel. The third specified algorithm is a mathematical formula or algorithm for converting pixel values to actual sizes, expressed by the following formula (3):

α＝(L _{long axis} -L _{Short shaft} )/(H _{Long axis} -H _{Short shaft} ) (3)

Wherein α represents pixel equivalent, L _{Long axis} Represents the actual value of the long axis of the coil core, L _{Short shaft} Represents the actual value of the short axis of the coil core, H _{Long axis} Representing the long-axis pixel value, H _{Short shaft} Representing the short axis pixel values.

S136, determining a deviation parameter, wherein the deviation parameter comprises a deviation angle and a mutation deviation value.

Wherein the deviation parameter includes a deviation angle and a sudden change deviation value. The deviation angle refers to a deviation between the central axis of the coil and the photographing angle, and the abrupt deviation value refers to abrupt change or discontinuity that may occur in some positions of the coil. The abrupt deviation is generated by abrupt change of the movement center caused by a certain gap in the center of the shaft when the mold is empty and the center of gravity is changed when the product rotates.

Specifically, the rotation center data may be acquired using a photographing device. The camera may be a camera, laser scanner or other device capable of capturing the center of rotation of the object. By placing the photographing device at a designated position, an image or data of the object when it rotates can be captured, and rotation center data can be obtained. After the rotation center data is acquired, it is necessary to further check the difference between the adjacent two rotation center data. And if the difference value of the adjacent two rotation center data is larger than a preset threshold value, marking the rotation center data as abrupt change data. Abrupt change data indicates that the object has significantly changed or been discontinuous during rotation. The mutation deviation value may be calculated mathematically for the mutation data, such as least squares, average deviation, etc.

Further, after the mutation data are processed, the actual central axis corresponding to the ellipsoid-like morphology needs to be determined. The actual central axis refers to the actual axis of rotation of the transformer coil during rotation. And then determining an included angle between the shooting direction and the actual central axis by acquiring the shooting direction of the line laser camera, namely, a deviation angle.

And S137, determining size information according to the pixel equivalent, the deviation parameter, the calibration distance, the adjacent wave peak value and the adjacent wave trough value.

Specifically, the fourth specified algorithm is a mathematical formula or algorithm for converting the pixel value into the actual size, and is expressed by the following formula (4):

wherein H' _{Short shaft} The short-axis actual value is represented, hr represents the calibration distance, H3 and H4 represent the adjacent wave peak value, θ represents the deviation angle, β represents the abrupt deviation value, and by substituting the pixel equivalent, the deviation parameter, the calibration distance and the adjacent wave peak value into a fourth specified algorithm, we can obtain the short-axis actual value, that is, the length of the short axis in the actual space.

Specifically, the fifth specified algorithm is another mathematical formula or algorithm for converting the pixel value into the actual size, and is expressed by the following formula (5):

wherein H' _{Long axis} The long axis actual value is represented, hr represents the calibration distance, H1 and H2 represent the adjacent trough values, θ represents the deviation angle, β represents the abrupt deviation value, and by substituting the pixel equivalent, the deviation parameter, the calibration distance and the adjacent trough values into the fifth specification algorithm, we can obtain the long axis actual value, that is, the length of the long axis in the actual space.

Example two

Fig. 3 is a flowchart of a method for determining a coil size of a transformer according to a second embodiment of the present invention, where a specific process for determining an acquisition parameter of a line laser camera is added on the basis of the first embodiment. The specific contents of steps S260 to S270 are substantially the same as steps S120 to S130 in the first embodiment, and thus, the detailed description is omitted in this embodiment. As shown in fig. 3, the method includes:

s210, acquiring a target rotation speed of a central shaft of the transformer coil.

Specifically, since the coil speeds in operation are different, the encoder is connected to the coil in motion, and the target rotation speed of the center shaft can be obtained. An encoder is a device capable of converting mechanical motion into an electrical signal, and determining the motion state of an object by measuring a rotation angle or a linear displacement. The encoder is connected with the coil, so that the rotation speed of the coil can be monitored in real time, and the rotation speed is converted into an electric signal to be output, so that the target rotation speed of the central shaft of the coil is obtained.

S220, acquiring a preset acquisition frequency list, wherein the acquisition frequency list comprises the corresponding relation between each rotation speed and frequency.

The collection frequency list is a list containing the corresponding relation between each rotation speed and frequency. The acquisition frequency list is usually preset according to the characteristics and acquisition requirements of the line laser camera, and can be used for quickly determining the acquisition frequency matched with the target rotation speed according to the target rotation speed.

S230, matching the target rotation speed through the acquisition frequency list to acquire a target frequency corresponding to the target rotation speed.

Specifically, the target rotational speed may be matched with the rotational speeds in the collection frequency list to determine a target frequency corresponding to the target rotational speed. The target frequency refers to the frequency that the line laser camera should use in the acquisition process, and is closely related to the target rotation speed.

S240, acquiring camera calibration parameters, determining a measurement effective area of the line laser camera according to the camera calibration parameters, and taking the measurement effective area as an acquisition range.

Specifically, using camera calibration parameters, we can determine the measurement effective area of a line laser camera. The measurement effective area refers to an area where the camera can accurately measure an object. The acquisition range refers to the area that the line laser camera should cover during acquisition, and it should include the area where the target rotation speed of the central axis of the transformer coil is located. The method is very important to the acquisition effect and accuracy of the line laser camera, and the line laser camera can be better utilized to measure and analyze the transformer coil by determining the acquisition parameters.

S250, detecting the transformer coil based on acquisition parameters to acquire point cloud data, wherein the acquisition parameters comprise target frequency and acquisition range.

S260, preprocessing the point cloud data to generate standard data.

And S270, determining the size information of the transformer coil according to the standard data.

Example III

Fig. 4 is a schematic structural diagram of a transformer coil size determining device according to a third embodiment of the present invention. As shown in fig. 4, the apparatus includes: the point cloud data acquisition module 310 is configured to determine acquisition parameters of the line laser camera, and detect the transformer coil based on the acquisition parameters to acquire point cloud data, where the acquisition parameters include a target frequency and an acquisition range;

a point cloud data preprocessing module 320, configured to preprocess the point cloud data to generate standard data;

the coil size information determining module 330 is configured to determine size information of the transformer coil according to the standard data.

Optionally, the point cloud data acquisition module 310 specifically includes: acquisition parameter acquisition unit for: acquiring a target rotation speed of a central shaft of a transformer coil; acquiring a preset acquisition frequency list, wherein the acquisition frequency list comprises the corresponding relation between each rotation speed and frequency; matching the target rotation speed through the acquisition frequency list to acquire a target frequency corresponding to the target rotation speed; and acquiring camera calibration parameters, determining a measurement effective area of the line laser camera according to the camera calibration parameters, and taking the measurement effective area as an acquisition range.

Optionally, the point cloud data preprocessing module 320 is specifically configured to: inputting the point cloud data into a preset software algorithm; the point cloud data is converted into an ellipsoid-like morphology based on a software algorithm to generate standard data.

Optionally, the coil size information determining module 330 specifically includes: a distance and peak-to-valley value determining unit for: obtaining a calibration distance, and determining an adjacent wave peak value and an adjacent wave trough value from standard data, wherein the calibration distance is the distance from a line laser camera to a central axis of a transformer coil; a short-axis pixel value determining unit for: substituting the calibrated distance and the adjacent peak value into a first appointed algorithm to determine a short-axis pixel value; a long axis pixel value determining unit for: substituting the calibrated distance and the adjacent trough value into a second designated algorithm to determine a long-axis pixel value; a size information determining unit for: and determining the size information of the transformer coil according to the short-axis pixel value and the long-axis pixel value.

Optionally, the size information determining unit specifically includes: a coil core size acquisition subunit configured to: acquiring the coil core size of a transformer coil; a pixel equivalent determining subunit for: substituting the coil core size, the short axis pixel value and the long axis pixel value into a third specified algorithm to determine pixel equivalent; a deviation parameter determination subunit configured to: determining a deviation parameter, wherein the deviation parameter comprises a deviation angle and a mutation deviation value; a size information determination subunit configured to: and determining the size information according to the pixel equivalent, the deviation parameter, the calibration distance, the adjacent wave peak value and the adjacent wave trough value.

Optionally, the deviation parameter determining subunit is specifically configured to: acquiring rotation center data through a shooting device at a designated position; when the difference value of two adjacent rotation center data is larger than a preset threshold value, taking the rotation center data as abrupt change data; determining mutation deviation values corresponding to the mutation data; determining an actual central axis corresponding to the ellipse-like body shape, and acquiring the shooting direction of the line laser camera; the angle between the shooting direction and the actual central axis is taken as the deviation angle.

Optionally, the size information determining subunit is specifically configured to: substituting the pixel equivalent, the deviation parameter, the calibration distance and the adjacent peak value into a fourth specified algorithm to determine a short-axis actual value; substituting the pixel equivalent, the deviation parameter, the calibration distance and the adjacent trough value into a fifth specifying algorithm to determine a major axis actual value; the short axis actual value and the long axis actual value are taken as size information.

The transformer coil size determining device provided by the embodiment of the invention can execute the transformer coil size determining method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the executing method.

Example IV

Fig. 5 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

As shown in fig. 5, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as a transformer coil sizing method. Namely: determining acquisition parameters of a line laser camera, and detecting a transformer coil based on the acquisition parameters to acquire point cloud data, wherein the acquisition parameters comprise target frequency and an acquisition range; preprocessing the point cloud data to generate standard data; size information of the transformer coil is determined from the standard data.

In some embodiments, a transformer coil sizing method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of one of the above-described transformer coil sizing methods may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform a transformer coil sizing method by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.

The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims

1. A method for sizing a coil of a power transformer, comprising:

preprocessing the point cloud data to generate standard data;

and determining the size information of the transformer coil according to the standard data.

2. The method of claim 1, wherein determining acquisition parameters of a line laser camera comprises:

acquiring a target rotation speed of a central shaft of a transformer coil;

acquiring a preset acquisition frequency list, wherein the acquisition frequency list comprises the corresponding relation between each rotation speed and frequency;

matching the target rotation speed through the acquisition frequency list to acquire a target frequency corresponding to the target rotation speed;

and acquiring camera calibration parameters, determining a measurement effective area of the line laser camera according to the camera calibration parameters, and taking the measurement effective area as the acquisition range.

3. The method of claim 1, wherein the preprocessing the point cloud data to generate standard data comprises:

inputting the point cloud data into a preset software algorithm;

the point cloud data is converted into an ellipsoid-like morphology based on the software algorithm to generate the standard data.

4. A method according to claim 3, wherein said determining size information of the transformer coil from the standard data comprises:

obtaining a calibration distance, and determining adjacent wave peak values and adjacent wave trough values from the standard data, wherein the calibration distance is the distance from a line laser camera to a central axis of a transformer coil;

substituting the calibrated distance and the adjacent peak value into a first specified algorithm to determine a short-axis pixel value;

substituting the calibrated distance and the adjacent trough value into a second designating algorithm to determine a long-axis pixel value;

and determining the size information of the transformer coil according to the short-axis pixel value and the long-axis pixel value.

5. The method of claim 4, wherein said determining size information of the transformer coil from the short axis pixel values and the long axis pixel values comprises:

acquiring the coil core size of the transformer coil;

substituting the coil core size, the short axis pixel value, and the long axis pixel value into a third specified algorithm to determine a pixel equivalent;

determining a deviation parameter, wherein the deviation parameter comprises a deviation angle and a mutation deviation value;

and determining the size information according to the pixel equivalent, the deviation parameter, the calibration distance, the adjacent wave peak value and the adjacent wave trough value.

6. The method of claim 5, wherein determining the deviation parameter comprises:

acquiring rotation center data through a shooting device at a designated position;

when the difference value of two adjacent rotation center data is larger than a preset threshold value, taking the rotation center data as abrupt change data;

determining mutation deviation values corresponding to the mutation data;

determining an actual central axis corresponding to the ellipsoid-like shape, and acquiring the shooting direction of a line laser camera;

and taking the included angle between the shooting direction and the actual central axis as the deviation angle.

7. The method of claim 5, wherein said determining said size information based on said pixel equivalent, said deviation parameter, said calibrated distance, said adjacent peak value, and said adjacent valley value comprises:

substituting the pixel equivalent, the deviation parameter, the calibration distance and the adjacent peak value into a fourth specified algorithm to determine the short-axis actual value;

substituting the pixel equivalent, the deviation parameter, the calibration distance, and the adjacent trough value into a fifth specified algorithm to determine the long axis actual value;

and taking the short axis actual value and the long axis actual value as the size information.

8. A transformer coil sizing device, comprising:

9. An electronic device, the electronic device comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.

10. A computer storage medium storing computer instructions for causing a processor to perform the method of any one of claims 1-7 when executed.