CN116188752A - Cable joint temperature anomaly detection device, method and equipment based on image recognition - Google Patents
Cable joint temperature anomaly detection device, method and equipment based on image recognition Download PDFInfo
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Abstract
The application discloses a cable joint temperature anomaly detection device, method and equipment based on image recognition, and belongs to the technical field of Internet of things. The device comprises: the visible light camera and the infrared camera acquire a visible light image and an infrared image at the cable joint; the identification module is used for identifying the serial number information and the temperature information of the cable connector in the visible light image and the infrared image; the fitting module is used for fitting the visible light image and the infrared image to obtain a fitting image of the cable joint, and adding the number information and the temperature information; the temperature anomaly identification module is used for inputting the fitting image into a pre-trained anomaly cause analysis model and determining at least one cause of anomaly when the temperature information is higher than a set temperature threshold value; and the alarm module is used for carrying out association display on the fitting image and the reason causing the abnormality. According to the technical scheme, the temperature of the cable connector can be accurately obtained in real time, meanwhile, the abnormal reasons can be efficiently judged, the occurrence of false alarm conditions can be reduced, and the working efficiency of maintenance personnel is improved.
Description
Technical Field
The application belongs to the technical field of power equipment, and particularly relates to a cable joint temperature anomaly detection device, method and equipment based on image recognition.
Background
Along with the smooth and rapid increase of the economy in China, the demands of wires and cables also show vigorous situations. The electric wires and cables have a considerable weight in national economy, and are indispensable in all economic activities and social lives. The electric wires and cables are used for connection in the process of generating, transmitting and applying electricity, wherein the temperature of the cable head is a key index when the cable is in operation, because the cable head always generates heat before the cable head fails in actual operation, insulation breakdown occurs if the cable head is not processed in time, short circuit, tripping and other power supply faults are caused, and fire disasters also occur when the cable head is serious. Therefore, the temperature of the cable head must be monitored and regulated in time to ensure the normal operation of the cable.
The current mode of measuring the temperature of the cable head is to arrange a wireless temperature sensor in a monitoring node to collect the temperature value at the cable joint, transmit the temperature value to an upper computer for analysis and processing through a wireless communication technology, and if the temperature value is higher than a preset threshold value, the upper computer of the system sends an instruction to alarm.
However, the current wireless temperature sensor is powered by a battery, so that the wireless temperature sensor needs to be replaced regularly, and the later maintenance workload of staff is increased. In addition, the temperature sensor generally adopts an externally hung installation mode, has low fitting degree with the cable and low measurement precision, so that the problem that false alarm or abnormal high temperature is not identified and the service life of the cable is further reduced is possibly caused. Therefore, how to accurately measure the temperature of the cable head in real time and discover abnormality in time, reduce the occurrence of false alarm, further ensure the normal operation of the cable, and prolong the service life of the cable is a problem to be solved in the field.
Disclosure of Invention
The embodiment of the application provides a device, a method and equipment for detecting abnormal temperature of a cable joint based on image recognition, and aims to solve the problems that in the prior art, the measurement accuracy of the temperature of the cable joint is low, so that false alarm possibly exists or abnormal high temperature is not recognized, and the service life of a cable is further shortened. Through the cable joint temperature anomaly detection device based on image recognition, the temperature information of the cable joint can be accurately obtained in real time, whether anomalies and anomaly reasons occur can be judged in real time according to the temperature information, and accordingly workers can timely process the anomalies. The occurrence of false alarm is reduced to a certain extent, and the service life of the cable can be prolonged.
In a first aspect, an embodiment of the present application provides a cable joint temperature anomaly detection device based on image recognition, where the device includes:
the visible light camera is used for acquiring a visible light image at the cable joint;
the infrared camera is used for acquiring an infrared image at the cable joint;
the identification module is used for identifying the serial number information of the cable connector included in the visible light image; acquiring temperature information at the cable joint according to the infrared image;
the fitting module is used for fitting the visible light image and the infrared image to obtain a fitting image of the cable joint, and attaching the number information and the temperature information to the fitting image;
a temperature anomaly identification module for inputting the fitted image to a pre-trained anomaly cause analysis model to determine at least one cause of anomaly by the anomaly cause analysis model if the temperature information is above a set temperature threshold;
and the alarm module is used for carrying out association display on the fitting image and the reason causing the abnormality.
Further, the temperature anomaly identification module is specifically configured to:
under the condition that the temperature information is higher than a set temperature threshold value, dividing the fitted image into blocks according to a preset area;
Identifying the highest temperature and average temperature of each divided block, and assigning values to the fitting image;
the fitted image with the block temperature assignments is input to a pre-trained abnormality cause analysis model to determine at least one cause of the abnormality from the abnormality cause analysis model.
Further, the reasons for the abnormality include: abnormal material quality, loose contact, increased wiring resistance, electrochemical reaction of wiring and loose wrapping;
the abnormality cause analysis model is obtained by collecting and training a preset number of samples based on the temperature information reflected under the conditions of each cause causing the abnormality.
Further, the device further comprises:
the connector position determining module is used for reading the serial number information of the cable connector and determining the installation position of the cable connector based on a comparison table of the pre-stored serial number information and the installation position.
Further, the joint position determining module is further configured to:
acquiring the equipment ID of the visible light camera and/or the infrared camera under the condition that the serial number information of the cable connector cannot be determined or the serial number information does not exist in the comparison table;
And determining the installation position of the cable joint according to the equipment ID.
In a second aspect, an embodiment of the present application provides a method for detecting a temperature anomaly of a cable joint based on image recognition, where the method includes:
obtaining a visible light image at the cable joint through a visible light camera;
acquiring an infrared image at the cable joint through an infrared camera;
identifying the serial number information of the cable joint included in the visible light image through an identification module; acquiring temperature information at the cable joint according to the infrared image;
fitting the visible light image and the infrared image through a fitting module to obtain a fitting image of a cable joint, and adding the number information and the temperature information into the fitting image;
inputting the fitted image into a pre-trained abnormality cause analysis model by a temperature abnormality recognition module under the condition that the temperature information is higher than a set temperature threshold value, so as to determine at least one cause of abnormality by the abnormality cause analysis model;
and carrying out association display on the fitting image and the reason causing the abnormality through an alarm module.
Further, in the case that the temperature information is higher than a set temperature threshold, inputting the fitted image to an abnormality cause analysis model trained in advance to determine at least one cause of abnormality by the abnormality cause analysis model, including:
Under the condition that the temperature information is higher than a set temperature threshold value, dividing the fitted image into blocks according to a preset area;
identifying the highest temperature and average temperature of each divided block, and assigning values to the fitting image;
the fitted image with the block temperature assignments is input to a pre-trained abnormality cause analysis model to determine at least one cause of the abnormality from the abnormality cause analysis model.
Further, the reasons for the abnormality include: abnormal material quality, loose contact, increased wiring resistance, electrochemical reaction of wiring and loose wrapping;
the abnormality cause analysis model is obtained by collecting and training a preset number of samples based on the temperature information reflected under the conditions of each cause causing the abnormality.
Further, after performing the association display on the fitting image and the reason for causing the abnormality, the method further includes:
and reading the serial number information of the cable connector through a connector position determining module, and determining the installation position of the cable connector based on a comparison table of the pre-stored serial number information and the installation position.
In a third aspect, embodiments of the present application provide an electronic device comprising a processor, a memory and a program or instruction stored on the memory and executable on the processor, the program or instruction implementing the steps of the method according to the first aspect when executed by the processor.
In a fourth aspect, embodiments of the present application provide a readable storage medium having stored thereon a program or instructions which when executed by a processor implement the steps of the method according to the first aspect.
In a fifth aspect, embodiments of the present application provide a chip, where the chip includes a processor and a communication interface, where the communication interface is coupled to the processor, and where the processor is configured to execute a program or instructions to implement a method according to the first aspect.
In the embodiment of the application, the visible light camera is used for acquiring a visible light image at the cable joint; the infrared camera is used for acquiring an infrared image at the cable joint; the identification module is used for identifying the serial number information of the cable connector included in the visible light image; acquiring temperature information at the cable joint according to the infrared image; the fitting module is used for fitting the visible light image and the infrared image to obtain a fitting image of the cable joint, and attaching the number information and the temperature information to the fitting image; a temperature anomaly identification module for inputting the fitted image to a pre-trained anomaly cause analysis model to determine at least one cause of anomaly by the anomaly cause analysis model if the temperature information is above a set temperature threshold; and the alarm module is used for carrying out association display on the fitting image and the reason causing the abnormality. Through the cable joint temperature anomaly detection device based on image recognition, the temperature information of the cable joint can be accurately obtained in real time, whether anomalies and reasons of the anomalies occur can be judged in real time according to the temperature information, and therefore workers can timely process the anomalies. The occurrence of false alarm is reduced to a certain extent, and the service life of the cable can be prolonged.
Drawings
Fig. 1 is a schematic structural diagram of a cable joint temperature anomaly detection device based on image recognition according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a cable joint temperature anomaly detection device based on image recognition according to a second embodiment of the present application;
fig. 3 is a schematic flow chart of a cable connector temperature anomaly detection method based on image recognition according to a third embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the following detailed description of specific embodiments thereof is given with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the matters related to the present application are shown in the accompanying drawings. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart depicts operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently, or at the same time. Furthermore, the order of the operations may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figures. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Technical solutions in the embodiments of the present application will be clearly described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application are within the scope of the protection of the present application.
The terms first, second and the like in the description and in the claims, 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, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type and not limited to the number of objects, e.g., the first object may be one or more. Furthermore, in the description and claims, "and/or" means at least one of the connected objects, and the character "/", generally means that the associated object is an "or" relationship.
The device, the method and the equipment for detecting the temperature abnormality of the cable joint based on the image recognition provided by the embodiment of the application are described in detail below by means of specific embodiments and application scenes thereof with reference to the accompanying drawings.
Example 1
Fig. 1 is a schematic structural diagram of a cable joint temperature anomaly detection device based on image recognition according to an embodiment of the present application. As shown in fig. 1, the method specifically includes the following steps:
a visible light camera 101 for acquiring a visible light image at a cable joint;
an infrared camera 102 for acquiring an infrared image at the cable joint;
an identification module 103, configured to identify serial number information of a cable joint included in the visible light image; acquiring temperature information at the cable joint according to the infrared image;
the fitting module 104 is configured to fit the visible light image and the infrared image to obtain a fitted image of the cable joint, and attach the number information and the temperature information to the fitted image;
a temperature anomaly identification module 105 for inputting the fitted image to a pre-trained anomaly cause analysis model to determine at least one cause of anomaly by the anomaly cause analysis model if the temperature information is above a set temperature threshold;
and the alarm module 106 is used for carrying out association display on the fitting image and the reason causing the abnormality.
Firstly, the use scene of the scheme can be a scene in which the temperature of the cable head is measured, and after the abnormal temperature is measured, the abnormal reason is analyzed and displayed. Specifically, the temperature of the cable head can be measured by the temperature measuring equipment, and the reasons of the abnormal temperature of the cable head are analyzed and displayed by the control terminal. The temperature measurement device can comprise a visible light camera and an infrared camera, the control terminal can be intelligent terminal equipment, such as a notebook computer, a desktop computer, a tablet personal computer and the like, and also can be an internet of things platform.
Based on the above usage scenario, it can be understood that the execution body of the application may be a terminal device integrated with measuring the cable head temperature and analyzing and displaying the cause of the cable head abnormal temperature, which is not limited in any way.
The visible light camera may be a color camera, i.e. a camera used when taking color pictures. In the scheme, the color camera is used for shooting a color image of the cable connector so that the intelligent terminal equipment or the internet of things platform can recognize the serial number information of the cable connector according to the color image and measure the temperature of the cable connector on the basis.
The cable may be an electrical energy or signal transmission device, typically consisting of several wires or groups of wires, including power cables, control cables, compensation cables, shielding cables, high temperature cables, computer cables, signal cables, coaxial cables, fire resistant cables, marine cables, mining cables, and aluminum alloy cables. The cable joint is also called a cable head. After the cable is laid, the sections must be connected as a unit in order to form a continuous line, and these points of connection are called cable joints. The cable joints in the middle of the cable line are called intermediate joints, while the cable joints at both ends of the line are called terminal heads. The cable connector is used for locking and fixing the incoming and outgoing lines, and plays a role in preventing water, dust and vibration.
The visible light image may be a color image of the cable tie taken by a color camera. Further, capturing a color image of the cable joint with a color camera may be a process of acquiring a visible light image of the cable joint.
The infrared camera can be an infrared temperature measuring camera, is a camera for imaging by utilizing infrared rays, and can form pictures according to the heat of the infrared rays besides common light rays. In this scheme, infrared camera is used for shooing the image that contains cable joint and cable joint temperature to supply intelligent terminal equipment or thing networking platform to accomplish cable joint temperature detection on the basis of the visible light image of this image and cable joint department that visible light camera shot afterwards.
The infrared image may be an image taken by an infrared camera containing the cable splice and the temperature of the cable splice. Further, capturing an image containing the cable splice and the temperature of the cable splice with an infrared camera may be a process of acquiring an infrared image at the cable splice.
The numbering information may be a unique number in the cable connector, and in order to distinguish between different cable connectors, different numbers may be provided for each cable connector so that the position of the cable connector may be located according to the number of the cable connector when the temperature of the cable connector is abnormal. Specifically, the number may include a number, a letter, and a text, and in this embodiment, the number may be numbered from one end to the other end along the cable laying direction. For example, a first splice number 1001 along the cabling direction, a second splice number 1002, and so on may result in a subsequent splice number.
The temperature information may be a temperature of the cable joint, and since the infrared image may reflect a temperature value of each pixel in the image, a highest temperature at the cable joint in the image may be taken as the temperature information, so that whether the temperature of the cable joint is an abnormal temperature or not may be determined based on the temperature information afterwards.
After the visible light camera acquires the visible light image at the cable joint, the visible light image can be transmitted to the intelligent terminal equipment or the internet of things platform through a wireless communication technology, wherein wireless communication refers to long-distance transmission communication between a plurality of nodes without transmission through conductors or cables, and wireless communication can be performed by using a radio, a radio and the like. And after the intelligent terminal equipment or the internet of things platform receives the visible light image, identifying the number information in the visible light image based on the template library. For example, when a number is used as the serial number information of the cable connector, since the serial number information is a simple character, the data set can be downloaded in advance on the internet, and then the intelligent terminal or the internet of things platform reads the visible light image acquired by the visible light camera and performs graying and binarization on the image (since the image itself is stored in a number, the binarized image has only two values of 0 and 255). After binarizing the image, the characters in the image are divided left and right and up and down to obtain an image with single numbers, the size of the image is adjusted to be the same as that of a template (the maximum size in the template is generally adopted), then the images to be matched are subtracted from the other 10 templates (the templates with the numbers of 0-10) (the values of the corresponding coordinate pixels of the two images are subtracted), and the absolute values of all differences are summed. And finally, the absolute value sum is minimum when the template is matched with the image, so that the image is matched with the template most, and the character is identified. And after all the characters are recognized, combining the characters to obtain the serial number information of the cable connector. The above is the whole process of identifying the number information of the cable joint included in the visible light image.
After the infrared camera acquires the infrared image of the cable connector, the infrared image can be transmitted to the intelligent terminal equipment or the internet of things platform through a wireless communication technology, and the intelligent terminal equipment or the internet of things platform can read the highest temperature value at the cable connector as temperature information after receiving the infrared image because the infrared image contains the temperature value of each pixel point. The above is a process of acquiring temperature information at a cable joint in an infrared image.
The fitting image can be a combined image of a visible light image and an infrared image, and the visible light image can clearly display the outline and the number of the cable joint, and the infrared image can display the temperature information of the cable joint, so that the visible light image and the infrared image can be combined to obtain an image containing the outline, the number and the temperature information of the cable joint.
After receiving the visible light image and the infrared image, the intelligent terminal equipment or the internet of things platform can put the visible light image and the infrared image into image processing software. Since the three primary colors (red, green and blue) of the color light are used when shooting the color image, the three primary colors are expressed in the form of channels in the image processing software, namely, expressed as three channels of Red Green Blue (RGB), wherein the red channel is responsible for displaying the information of red contained in the photo; a green channel is responsible for displaying the information of green contained in the photo; the blue channel is responsible for displaying the information in the photograph that contains blue. Thus, the color image is represented as an RGB 3-channel image in the image processing software. Further, the infrared single channel of the infrared image can be directly expanded into a 3-channel RGB image, and the RGB value of each pixel is identical, namely a gray image, but has 3 channels. Then, the image is fused with the color image in a semitransparent manner to obtain a fitting image. The above is a process of obtaining a fitted image of a cable joint.
After the fitted image is obtained, photo cap (digital camera batch tool) may be used to add Exif (Exchangeable image file format exchangeable image file format) information to the fitted image. Specifically, after the fitted image is imported in the editing area of the photoscap in the standard mode, the serial number information and the temperature information of the cable connector are input in the "Exif object attribute setting" dialog box, so that the purpose of adding the serial number information and the temperature information to the fitted image can be achieved. The Exif format is specifically set for digital camera photos. This format may record digital photograph attribute information. PhotoCap has powerful batch processing functions for date, text, borders, exif data, change file names, etc. commonly used by digital camera users.
The set temperature threshold may be a temperature at which an abnormality occurs in the cable joint. For example, when the temperature at the cable joint is higher than 60 ℃, the cable is abnormal, the set temperature threshold may be set to 60 ℃, and when the temperature information exceeds the set temperature threshold, the next operation of inputting the fitting image into the pre-trained abnormality cause analysis model is performed.
The abnormality cause analysis model may be an abnormality attribution model, which may be a big data model that analyzes the cause of occurrence of an abnormality from information. In the scheme, the abnormality attribution model can be trained in advance, namely, abnormality indexes are input into a data modeling tool, and the abnormality attribution model is set through methods of funnel attribution, internal attribution, external attribution and the like, so that the purpose of training the abnormality cause analysis model is achieved. Funnel attribution is the reason for finding out the lower level of personnel matters from the occurrence of abnormality; internal attribution is to find the reason directly from the personnel matters with abnormality; the remainder are all externally attributed categories. The number of anomaly indices can be determined using a ten-fold rule, which is the amount of data that the model typically requires to exceed its degree of freedom by a factor of ten. The degrees of freedom here may be parameters affecting the model output, being one attribute of the data points, i.e. the columns in the dataset. The objective of the ten-fold rule is to counteract the changes brought by these combination parameters to the model input, so that we can estimate the number of data sets quickly, and ensure that the project remains running. For example, if parameters in the model are number information, temperature information, fitting image and abnormality cause, the number of abnormality indexes is at least forty.
The reasons for the abnormality may be the reasons for the abnormality of the temperature of the cable joint, and may include problems of manufacturing process, mechanical damage, and installation density.
After the intelligent terminal equipment or the internet of things platform obtains the fitting image, the abnormal cause analysis model is called after the temperature information is identified to be higher than the set threshold value, and the fitting image is input into the model. The abnormality cause analysis model identifies the cause of abnormality after comprehensive judgment by identifying the fitted image, temperature information, number information, and the like.
After the reasons for the abnormality are obtained, the analysis model for the reasons for the abnormality can correlate and display the fitting image and the reasons for the abnormality through the client, so that a worker can repair the cable connector according to the information in time. Specifically, the form of association presentation may be: fitting the image-the cause of the anomaly.
On the basis of the above technical solution, optionally, the apparatus further includes:
the connector position determining module is used for reading the serial number information of the cable connector and determining the installation position of the cable connector based on a comparison table of the pre-stored serial number information and the installation position.
The installation location may be the geographical coordinates of the installation of the cable connector and may be expressed as (latitude, longitude). For example, the geographical coordinates of the cable connector installation are (30 ° N120 ° E), indicating that the cable connector installation location is 30 degrees north latitude and 120 degrees east longitude.
After the cable joint is installed, a database table 1 for storing the serial number information, the installation position and the fitting image of the cable joint can be established in the intelligent terminal or the internet of things platform, wherein the database table 1 is a comparison table of the pre-stored serial number information and the installation position.
When it is determined that an abnormality has occurred in the cable joint, the position of the cable joint is located so that a serviceman can go to the position for maintenance. The intelligent terminal or the internet of things platform can use the Exif information viewer to view the Exif information of the fitting image of the abnormal cable joint and read the serial number information of the cable joint. After the cable connector serial number information is read, the intelligent terminal or the internet of things platform invokes a comparison table of the pre-stored serial number information and the installation position, and the corresponding installation position can be determined by inquiring the comparison table according to the serial number information.
In this scheme, through storing numbering information and mounted position in the comparison table in advance, can confirm corresponding mounted position fast when reading cable joint numbering information to the staff can maintain according to this position fast, has improved maintenance personnel work efficiency to a certain extent.
On the basis of the above technical solution, optionally, the joint position determining module is further configured to:
acquiring the equipment ID of the visible light camera and/or the infrared camera under the condition that the serial number information of the cable connector cannot be determined or the serial number information does not exist in the comparison table;
and determining the installation position of the cable joint according to the equipment ID.
In this scheme, because there are corresponding visible light camera and infrared camera in every cable junction department, visible light camera and infrared camera all have corresponding equipment number, namely equipment ID. Specifically, the device ID may be in the form of a combination of letters and numbers, for example, the visible light camera device ID may be a001, the infrared camera device ID may be b001, and corresponding cable joint number information may be 1001. After the cable connector is installed, a database table 2 can be pre-established in the intelligent terminal or the internet of things platform, and the visible light camera equipment ID, the infrared camera equipment ID, the fitting image and the installation position are stored.
Under the condition that the serial number information of the cable connector cannot be determined or the serial number information does not exist in the comparison table, the intelligent terminal or the Internet of things platform transmits a 'reading equipment ID command' to the visible light camera and the infrared camera which shoot the cable connector image through a wireless communication technology, the visible light camera and the infrared camera read the equipment ID of the internal storage unit after receiving the command, and the equipment ID is transmitted to the intelligent terminal or the Internet of things platform through the wireless communication technology, so that the purpose of acquiring the equipment IDs of the visible light camera and the infrared camera can be achieved.
After receiving the device IDs of the visible light cameras and the infrared cameras, the intelligent terminal or the Internet of things platform automatically calls the database table 2, and the installation position of the corresponding cable connector can be determined according to the ID inquiry.
In this scheme, through setting up the mode of confirming the mounted position of cable connector according to the visible light camera of shooting cable connector visible light image and infrared image and the equipment ID of infrared camera, also can obtain the mounted position of cable connector when night or cable connector serial number information are fuzzy can't be discerned to the staff carries out corresponding maintenance according to the mounted position. The method is equivalent to setting a standby scheme, improves the efficiency of determining the installation position of the cable connector to a certain extent, and can efficiently treat the abnormal condition of the cable connector by maintenance personnel.
The technical scheme provided by the embodiment is that the visible light camera is used for acquiring a visible light image at a cable joint; the infrared camera is used for acquiring an infrared image at the cable joint; the identification module is used for identifying the serial number information of the cable connector included in the visible light image; acquiring temperature information at the cable joint according to the infrared image; the fitting module is used for fitting the visible light image and the infrared image to obtain a fitting image of the cable joint, and attaching the number information and the temperature information to the fitting image; a temperature anomaly identification module for inputting the fitted image to a pre-trained anomaly cause analysis model to determine at least one cause of anomaly by the anomaly cause analysis model if the temperature information is above a set temperature threshold; and the alarm module is used for carrying out association display on the fitting image and the reason causing the abnormality. Through the cable joint temperature anomaly detection device based on image recognition, the temperature information of the cable joint can be accurately obtained in real time, whether anomalies and reasons of the anomalies occur can be judged in real time according to the temperature information, and therefore workers can timely process the anomalies. The occurrence of false alarm is reduced to a certain extent, and the service life of the cable can be prolonged.
The device for detecting the abnormal temperature of the cable joint based on the image recognition in the embodiment of the application can be a device, and can also be a component, an integrated circuit or a chip in a terminal. The device may be a mobile electronic device or a non-mobile electronic device. By way of example, the mobile electronic device may be a cell phone, tablet computer, notebook computer, palm computer, vehicle-mounted electronic device, wearable device, ultra-mobile personal computer (ultra-mobile personal computer, UMPC), netbook or personal digital assistant (personal digital assistant, PDA), etc., and the non-mobile electronic device may be a server, network attached storage (Network Attached Storage, NAS), personal computer (personal computer, PC), television (TV), teller machine or self-service machine, etc., and the embodiments of the present application are not limited in particular.
The cable joint temperature anomaly detection device based on image recognition in the embodiment of the application may be a device with an operating system. The operating system may be an Android operating system, an ios operating system, or other possible operating systems, which are not specifically limited in the embodiments of the present application.
Example two
Fig. 2 is a schematic structural diagram of a cable joint temperature anomaly detection device based on image recognition according to a second embodiment of the present application. As shown in fig. 2, the method specifically includes the following steps:
the temperature anomaly identification module 105 is specifically configured to:
under the condition that the temperature information is higher than a set temperature threshold value, dividing the fitted image into blocks according to a preset area;
identifying the highest temperature and average temperature of each divided block, and assigning values to the fitting image;
the fitted image with the block temperature assignments is input to a pre-trained abnormality cause analysis model to determine at least one cause of the abnormality from the abnormality cause analysis model.
In this solution, the preset area may be set according to a preset rule, for example, the preset area may be set according to three parts of the cable connector, i.e. the middle part and the end part, and the cable connector may be divided into three blocks according to the three preset areas. Finally, the cable joint can be divided into three blocks according to three parts of preset areas in the fitting image to finish block division of the fitting image according to the preset areas.
Because the fitting image is a combined image of the visible light image and the infrared image, the infrared image can reflect the temperature values corresponding to all pixels, and the highest temperature can be the highest temperature value in the temperature values corresponding to all pixels of the current block. The average temperature may be a ratio of a sum of temperature values corresponding to all pixels of the current block to the number of pixels, and the calculation formula may be:
average temperature= (pixel 1 temperature+pixel 2 temperature+.+ pixel n temperature)/(number of pixels)
When the intelligent terminal or the internet of things platform recognizes that the temperature information of the cable connector in the fitting image is higher than the set temperature threshold, the fitting image is automatically divided into blocks according to the preset area, then the highest temperature of each block is read, an average temperature calculation formula is called to calculate the average temperature of the current block, and the process of recognizing the highest temperature and the average temperature of each block after division can be completed.
After the highest temperature and the average temperature of each block are identified, the intelligent terminal or the internet of things platform can input the highest temperature and the average temperature of each block of the cable connector in an Exif object attribute setting dialog box after the fitting image is imported in a standard mode in an editing area of the PhotoCap, and the purpose of assigning the fitting image can be achieved.
After the maximum temperature and the average temperature of each block are identified, the fitting image with the number information and the assigned value of the temperature of each block can be input into a pre-trained abnormality cause analysis model, and at least one cause of abnormality is analyzed by using the model. In this case, since the parameter amounts change at this time, the data amount required for the abnormality cause analysis model during training will also change according to the ten-fold rule. For example, when the fitted image is divided into three modules, the parameter may be number information, block 1 temperature information, block 2 temperature information, block 3 temperature information, the fitted image, and the abnormality cause, and the amount of data required for the abnormality cause analysis model in training is sixty.
According to the technical scheme provided by the embodiment, the fitting image is divided into the blocks according to the preset area, the highest temperature and the average temperature of each block are measured respectively, and the accuracy of determining the abnormal reasons can be improved. Meanwhile, the specific position of the abnormal cable connector can be accurately positioned.
On the basis of the technical scheme, optionally, the reasons for causing the abnormality include: abnormal material quality, loose contact, increased wiring resistance, electrochemical reaction of wiring and loose wrapping;
The abnormality cause analysis model is obtained by collecting and training a preset number of samples based on the temperature information reflected under the conditions of each cause causing the abnormality.
The abnormal material quality can be caused by the problem of the quality of the cable joint material, so that the temperature of the cable joint is easy to be abnormal. For example, when the insulating material of the cable joint is polyvinyl chloride, there may be a problem that the cable is likely to run and heat generation is likely to occur due to the quality problems such as a large amount of impurities, unqualified thermal weight loss, air holes in the extrusion layer, and difficulty in plasticization, and further, the temperature of the cable joint is likely to be abnormal.
The infirm contact can be that the joint manufacturing technique is bad, and the crimping is inseparable, causes joint department contact resistance too big, also can cause the cable to produce the phenomenon of generating heat, and further, the cable joint temperature appears unusual easily.
When the wiring resistance increases and the voltage is unchanged, the current increases, and the heat generated when the current flows through the cable increases. Further, the cable generates heat during operation, so that the temperature of the cable joint is easy to be abnormal.
The electrochemical reaction may be a chemical reaction that falls within the electrochemical category. During electrochemical reaction, the electrode reaction of hydrogen evolution, oxygen evolution and chlorine evolution is carried out on the surface of the electrode, and the separated gases are adsorbed on the surface of the electrode in the form of bubbles, so that the active area of the electrode is reduced, the potential and current density of the electrode are unevenly distributed, and electrode polarization is generated. When a large number of bubbles are adsorbed on the surface of the electrode, a gas film is formed on the surface of the electrode, so that the electrode is passivated and deactivated. The gas deposited on the electrode surface is dispersed in the electrolyte in the form of bubbles, so that the electrolyte becomes a gas-liquid mixed system, and the actual conductivity is reduced. In order to ensure that the electric quantity delivered by the cable is unchanged, the voltage value needs to be increased, so that the energy consumption of the process is increased. Further, the cable generates heat during operation, so that the temperature of the cable joint is easy to be abnormal.
When the parcel is not hard up, also can cause the junction contact resistance too big to cause the cable to produce the phenomenon of generating heat, further, the cable joint temperature appears unusual easily.
When the cause of abnormality is different, the temperature information of the abnormality of the cable joint may be different, for example, when the cause of abnormality is that the wiring resistance is increased, the abnormal temperature range of the cable joint may be 120 ℃ to 150 ℃, and the abnormal temperature information is one temperature value in this range; when the abnormality is a material abnormality, the abnormal temperature range of the cable joint may be 70-80 ℃, and the abnormal temperature information is a temperature value in the range. Therefore, when training the abnormality cause analysis model, the abnormality cause in the parameter may be refined to a specific cause, and after dividing the fitted image into three blocks, the refined parameter amounts may include the number information, the block 1 temperature information, the block 2 temperature information, the block 3 temperature information, the fitted image, the abnormality cause-material abnormality, the abnormality cause-contact insecurity, the abnormality cause-increase in wiring resistance, the abnormality cause-wiring electrochemical reaction, and the abnormality cause-package looseness. Correspondingly, the preset number of collected samples is set to be one hundred according to the ten-fold rule.
In the scheme, the reasons for abnormal temperature of the cable joint are thinned, so that the training preset quantity is enlarged when the abnormal reason analysis model is trained, the analysis result of the abnormal reason analysis model is more accurate, the corresponding solution can be judged according to the abnormal reason more quickly when the worker is maintained, and the maintenance efficiency of the worker is improved. Meanwhile, the cable connector faults can be removed more quickly, so that the normal operation time of the cable can be prolonged to a certain extent, and the service life of the cable can be prolonged.
Example III
Fig. 3 is a schematic flow chart of a cable connector temperature anomaly detection method based on image recognition according to a third embodiment of the present application. As shown in fig. 3, the method specifically comprises the following steps:
s301, obtaining a visible light image at a cable joint through a visible light camera;
s302, acquiring an infrared image at a cable joint through an infrared camera;
s303, identifying the serial number information of the cable connector included in the visible light image through an identification module; acquiring temperature information at the cable joint according to the infrared image;
s304, fitting the visible light image and the infrared image through a fitting module to obtain a fitting image of the cable connector, and adding the number information and the temperature information into the fitting image;
S305, inputting the fitting image into a pre-trained abnormality cause analysis model through a temperature abnormality recognition module under the condition that the temperature information is higher than a set temperature threshold value, so as to determine at least one cause of abnormality through the abnormality cause analysis model;
s306, carrying out association display on the fitting image and the reason causing the abnormality through an alarm module.
Further, in the case that the temperature information is higher than a set temperature threshold, inputting the fitted image to an abnormality cause analysis model trained in advance to determine at least one cause of abnormality by the abnormality cause analysis model, including:
under the condition that the temperature information is higher than a set temperature threshold value, dividing the fitted image into blocks according to a preset area;
identifying the highest temperature and average temperature of each divided block, and assigning values to the fitting image;
the fitted image with the block temperature assignments is input to a pre-trained abnormality cause analysis model to determine at least one cause of the abnormality from the abnormality cause analysis model.
Further, the reasons for the abnormality include: abnormal material quality, loose contact, increased wiring resistance, electrochemical reaction of wiring and loose wrapping;
The abnormality cause analysis model is obtained by collecting and training a preset number of samples based on the temperature information reflected under the conditions of each cause causing the abnormality.
Further, after performing the association display on the fitting image and the reason for causing the abnormality, the method further includes:
and reading the serial number information of the cable connector through a connector position determining module, and determining the installation position of the cable connector based on a comparison table of the pre-stored serial number information and the installation position.
In the embodiment of the application, a visible light image at a cable joint is obtained through a visible light camera; acquiring an infrared image at the cable joint through an infrared camera; identifying the serial number information of the cable joint included in the visible light image through an identification module; acquiring temperature information at the cable joint according to the infrared image; fitting the visible light image and the infrared image through a fitting module to obtain a fitting image of a cable joint, and adding the number information and the temperature information into the fitting image; inputting the fitted image into a pre-trained abnormality cause analysis model by a temperature abnormality recognition module under the condition that the temperature information is higher than a set temperature threshold value, so as to determine at least one cause of abnormality by the abnormality cause analysis model; and carrying out association display on the fitting image and the reason causing the abnormality through an alarm module. By the method for detecting the temperature abnormality of the cable joint based on image recognition, the temperature information of the cable joint can be accurately obtained in real time, whether the abnormality and the abnormality cause occur or not can be judged in real time according to the temperature information, and therefore staff can process the abnormality in time. The occurrence of false alarm is reduced to a certain extent, and the service life of the cable can be prolonged.
The method for detecting the abnormal temperature of the cable joint based on the image recognition provided by the embodiment corresponds to the device provided by the above embodiments and has the corresponding execution process and beneficial effects, and is not repeated here.
Example IV
As shown in fig. 4, the embodiment of the present application further provides an electronic device 400, including a processor 401, a memory 402, and a program or an instruction stored in the memory 402 and capable of running on the processor 401, where the program or the instruction implements each process of the cable joint temperature anomaly detection device embodiment based on image recognition when executed by the processor 401, and the process can achieve the same technical effect, so that repetition is avoided, and no redundant description is provided herein.
The electronic device in the embodiment of the application includes the mobile electronic device and the non-mobile electronic device described above.
Example five
The embodiment of the application further provides a readable storage medium, on which a program or an instruction is stored, where the program or the instruction realizes each process of the embodiment of the cable joint temperature anomaly detection device based on image recognition when being executed by a processor, and the same technical effects can be achieved, so that repetition is avoided, and no redundant description is provided here.
Wherein the processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium such as a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and the like.
Example six
The embodiment of the application further provides a chip, the chip includes a processor and a communication interface, the communication interface is coupled with the processor, the processor is used for running a program or an instruction, implementing each process of the cable joint temperature anomaly detection device embodiment based on image recognition, and achieving the same technical effect, so as to avoid repetition, and no redundant description is provided here.
It should be understood that the chips referred to in the embodiments of the present application may also be referred to as system-on-chip chips, chip systems, or system-on-chip chips, etc.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solutions of the present application may be embodied essentially or in a part contributing to the prior art in the form of a computer software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the methods described in the embodiments of the present application.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those of ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are also within the protection of the present application.
The foregoing description is only of the preferred embodiments of the present application and the technical principles employed. The present application is not limited to the specific embodiments described herein, but is capable of numerous obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the present application. Therefore, while the present application has been described in connection with the above embodiments, the present application is not limited to the above embodiments, but may include many other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the claims.
Claims (10)
1. An apparatus for detecting temperature anomalies of a cable joint based on image recognition, characterized in that it comprises:
the visible light camera is used for acquiring a visible light image at the cable joint;
the infrared camera is used for acquiring an infrared image at the cable joint;
the identification module is used for identifying the serial number information of the cable connector included in the visible light image; acquiring temperature information at the cable joint according to the infrared image;
the fitting module is used for fitting the visible light image and the infrared image to obtain a fitting image of the cable joint, and attaching the number information and the temperature information to the fitting image;
A temperature anomaly identification module for inputting the fitted image to a pre-trained anomaly cause analysis model to determine at least one cause of anomaly by the anomaly cause analysis model if the temperature information is above a set temperature threshold;
and the alarm module is used for carrying out association display on the fitting image and the reason causing the abnormality.
2. The device for detecting abnormal temperature of a cable joint based on image recognition according to claim 1, wherein the temperature abnormality recognition module is specifically configured to:
under the condition that the temperature information is higher than a set temperature threshold value, dividing the fitted image into blocks according to a preset area;
identifying the highest temperature and average temperature of each divided block, and assigning values to the fitting image;
the fitted image with the block temperature assignments is input to a pre-trained abnormality cause analysis model to determine at least one cause of the abnormality from the abnormality cause analysis model.
3. The apparatus for detecting abnormal temperature of a cable joint based on image recognition according to claim 2, wherein the causes of the abnormality include: abnormal material quality, loose contact, increased wiring resistance, electrochemical reaction of wiring and loose wrapping;
The abnormality cause analysis model is obtained by collecting and training a preset number of samples based on the temperature information reflected under the conditions of each cause causing the abnormality.
4. The apparatus for detecting temperature anomaly of a cable joint based on image recognition according to claim 1, further comprising:
the connector position determining module is used for reading the serial number information of the cable connector and determining the installation position of the cable connector based on a comparison table of the pre-stored serial number information and the installation position.
5. The apparatus for detecting a temperature anomaly of a cable joint based on image recognition of claim 4, wherein the joint position determining module is further configured to:
acquiring the equipment ID of the visible light camera and/or the infrared camera under the condition that the serial number information of the cable connector cannot be determined or the serial number information does not exist in the comparison table;
and determining the installation position of the cable joint according to the equipment ID.
6. The cable joint temperature anomaly detection method based on image recognition is characterized by comprising the following steps of:
obtaining a visible light image at the cable joint through a visible light camera;
Acquiring an infrared image at the cable joint through an infrared camera;
identifying the serial number information of the cable joint included in the visible light image through an identification module; acquiring temperature information at the cable joint according to the infrared image;
fitting the visible light image and the infrared image through a fitting module to obtain a fitting image of a cable joint, and adding the number information and the temperature information into the fitting image;
inputting the fitted image into a pre-trained abnormality cause analysis model by a temperature abnormality recognition module under the condition that the temperature information is higher than a set temperature threshold value, so as to determine at least one cause of abnormality by the abnormality cause analysis model;
and carrying out association display on the fitting image and the reason causing the abnormality through an alarm module.
7. The method for detecting a temperature abnormality of a cable joint based on image recognition according to claim 6, wherein, in a case where the temperature information is higher than a set temperature threshold, inputting the fitted image to an abnormality cause analysis model trained in advance to determine at least one cause of abnormality by the abnormality cause analysis model, comprising:
Under the condition that the temperature information is higher than a set temperature threshold value, dividing the fitted image into blocks according to a preset area;
identifying the highest temperature and average temperature of each divided block, and assigning values to the fitting image;
the fitted image with the block temperature assignments is input to a pre-trained abnormality cause analysis model to determine at least one cause of the abnormality from the abnormality cause analysis model.
8. The method for detecting abnormal temperature of a cable joint based on image recognition according to claim 7, wherein the causes of the abnormality include: abnormal material quality, loose contact, increased wiring resistance, electrochemical reaction of wiring and loose wrapping;
the abnormality cause analysis model is obtained by collecting and training a preset number of samples based on the temperature information reflected under the conditions of each cause causing the abnormality.
9. The method for detecting a temperature anomaly of a cable joint based on image recognition according to claim 6, wherein after the fitting image and the cause of anomaly are presented in association, the method further comprises:
and reading the serial number information of the cable connector through a connector position determining module, and determining the installation position of the cable connector based on a comparison table of the pre-stored serial number information and the installation position.
10. An electronic device comprising a processor, a memory and a program or instruction stored on the memory and executable on the processor, which when executed by the processor, implements the steps of the image recognition-based cable joint temperature anomaly detection method of any one of claims 6 to 9.
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| CN202211638095.0A CN116188752A (en) | 2022-12-20 | 2022-12-20 | Cable joint temperature anomaly detection device, method and equipment based on image recognition |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116839682A (en) * | 2023-09-01 | 2023-10-03 | 山东日辉电缆集团有限公司 | Cable processing and manufacturing real-time monitoring system based on Internet of things |
| CN116990321A (en) * | 2023-09-28 | 2023-11-03 | 广东新亚光电缆股份有限公司 | Image recognition-based sheath flat cable product quality analysis system |
-
2022
- 2022-12-20 CN CN202211638095.0A patent/CN116188752A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116839682A (en) * | 2023-09-01 | 2023-10-03 | 山东日辉电缆集团有限公司 | Cable processing and manufacturing real-time monitoring system based on Internet of things |
| CN116839682B (en) * | 2023-09-01 | 2023-11-21 | 山东日辉电缆集团有限公司 | Cable processing and manufacturing real-time monitoring system based on Internet of things |
| CN116990321A (en) * | 2023-09-28 | 2023-11-03 | 广东新亚光电缆股份有限公司 | Image recognition-based sheath flat cable product quality analysis system |
| CN116990321B (en) * | 2023-09-28 | 2023-12-22 | 广东新亚光电缆股份有限公司 | Image recognition-based sheath flat cable product quality analysis system |
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