CN118130972B - Communication cable data management method and device - Google Patents
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Abstract
The invention discloses a communication cable data management method and a device, comprising the following steps: collecting sensor data; the sound wave generator generates sound waves and receives sound wave data transmitted through the cable through the sound wave receiver; transmitting the acquired sensor data and acoustic wave data to a communication subsystem, and converting the acquired sensor data and acoustic wave data into digital signals through an analog-to-digital converter of the communication subsystem; transmitting the digital signal to a data processing server, and processing the received digital signal through the data processing server; the data monitoring is comprehensive, a partial discharge sensor is also arranged, and the discharge condition of the cable joint position is monitored; converting the propagation characteristics of sound waves in the cable into image data by arranging a sound wave generator and a sound wave receiver, establishing a database, and identifying the fault type and the fault position of the cable by adopting an image identification technology; through comprehensive cable data monitoring and accurate fault judgment, the management and maintenance of the cable are facilitated.
Description
Technical Field
The invention belongs to the technical field of communication cable data management, and particularly relates to a communication cable data management method and device.
Background
In recent years, national economy continuously develops, the demand of the market for communication cables continuously rises, the scale of the communication cable industry is driven to be continuously enlarged, the production technology is also continuously improved, the types of products are increasingly abundant, and the domestic market demand can be basically met.
Communication cables are becoming more important as key carriers for information transmission and data management. However, in the prior art, a method of regular inspection is generally adopted to inspect the operation condition of the cable, but the growth speed of operation maintenance personnel is far from that of the power infrastructure, so that the overhaul maintenance work faces huge pressure and often has problems, and after the report of a user, the personnel are sent to perform investigation maintenance, the processing efficiency is low, the decision support is insufficient, and the high-efficiency operation requirement of the modern communication network is difficult to meet.
Disclosure of Invention
The invention aims to provide a communication cable data management method and device, which are used for solving the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: a method of communication cable data management comprising the steps of:
1) Collecting sensor data;
2) The sound wave generator generates sound waves and receives sound wave data transmitted through the cable through the sound wave receiver;
3) Transmitting the acquired sensor data and acoustic wave data to a communication subsystem, and converting the acquired sensor data and acoustic wave data into digital signals through an analog-to-digital converter of the communication subsystem;
4) Transmitting the digital signals to a data processing server, and processing the received digital signals through the data processing server, wherein the method comprises the following specific steps of:
4.1 Establishing a cable natural aging propagation acoustic wave characteristic database, acquiring acoustic wave characteristics of propagation of acoustic waves at different stages in the cable natural aging process, and converting the acoustic wave characteristics into images, wherein the cable natural aging propagation acoustic wave characteristic database is a database formed by the images;
4.2 Establishing a cable damage propagation sound wave characteristic database, acquiring sound wave characteristics of sound waves propagated in a damaged cable, and converting the sound wave characteristics into images, wherein the cable damage propagation sound wave characteristic database is a database formed by the images;
4.3 Establishing an acoustic wave characteristic superposition database, superposing acoustic wave characteristics of the cable damage propagation acoustic wave characteristic database with acoustic wave characteristics of the cable natural aging propagation acoustic wave at different stages, and converting the superposed acoustic wave characteristics into an image, wherein the acoustic wave characteristic superposition database is a database formed by the image;
4.4 Constructing a deep learning model;
4.5 Inputting a sound wave image to be detected into the constructed deep learning model, identifying a corresponding image from a sound wave feature superposition database through the deep learning model, and determining the cable damage type;
5) And recording and storing the detected sensor data and the cable damage type in a cloud platform in an image-text mode, so that the monitoring background and the real-time query and management of the mobile equipment are facilitated.
Preferably, the sensor data collected in the step 1) includes a temperature sensor, a methane sensor, a CO sensor and a water level sensor, which collect temperature, methane content, CO content and water level respectively;
preferably, the sensor data collected in the step 1) includes a discharge parameter collected by a partial discharge sensor; the local discharge sensor is arranged at the position of the cable joint, when the cable joint is provided with an explosion-proof shell, the main sensor and the auxiliary sensor of the local discharge sensor are respectively arranged at two sides of the cable joint, when the cable joint does not have the explosion-proof shell, the main sensor of the local discharge sensor is arranged at one side of the cable joint, and the auxiliary sensor is arranged on the outer cable body at the other side of the cable joint.
Preferably, the communication subsystem in the step 3) includes an analog-to-digital converter, a lower computer, an upper computer and a communication controller, the communication controller includes a CAN module and a CAN control module, the CAN module is disposed on the lower computer, the CAN control module is disposed on the upper computer, and the digital signal converted by the analog-to-digital converter is transmitted to the upper computer through a CAN bus protocol between the CAN module of the lower computer and the CAN control module of the upper computer.
Preferably, the upper computer is further provided with a storage module, a liquid crystal module and a keyboard module, wherein the storage module is used for storing data, the liquid crystal module is used for displaying, and the keyboard module is used for inputting by a keyboard.
Preferably, the data processing server in the step 4) sets an alarm threshold for detection data of a temperature sensor, a methane sensor, a CO sensor, a water level sensor and a partial discharge sensor, and when the detection data exceeds the alarm threshold, the data processing server alarms, and alarm information is sent to a monitoring background and mobile equipment to enable staff to deal with the detection in time; after processing, the staff uploads the processing mode to the data processing server in a text, picture or video mode.
Preferably, the specific method of the step 4.5) is as follows:
Converting received sound waves into image data, inputting the image data into an established image recognition model, comparing the image recognition model with a sound wave characteristic superposition database, performing image recognition, and if a corresponding image can be recognized, determining the cable damage type according to the recognized image, and reminding a worker of performing corresponding maintenance treatment; if the cable is not identified, comparing the cable with a natural aging propagation acoustic wave characteristic database, carrying out image identification, if the corresponding image can be identified, judging that the cable is normal and belongs to natural aging, determining the natural aging stage of the cable, and reminding a worker to carry out corresponding maintenance treatment when the cable is in a stage of serious aging, so that the problems of short circuit and breakdown of the cable caused by natural aging of a cable protection layer are avoided; if the damage type is not recognized, performing manual inspection, converting the sound wave characteristics into pictures, storing the pictures in a cable damage propagation sound wave characteristic database, and marking the corresponding damage type; the database capacity is increased so that the same type of cable damage type is again identifiable.
Preferably, the method for detecting the type and the position of cable damage by the data processing server is as follows:
dividing a cable between the sound wave generator and the sound wave receiver into a plurality of equidistant sections, and respectively acquiring sound wave characteristics of sound waves transmitted in different sections;
acquiring equidistant different types of damaged cables, and acquiring sound wave characteristics of sound waves propagating in the equidistant different types of damaged cables;
The method comprises the steps of taking the length of a cable between an acoustic wave generator and an acoustic wave receiver as a unit length, superposing the obtained acoustic wave characteristics to obtain superposed acoustic wave characteristics, wherein the sum of cable sections corresponding to the superposed acoustic wave characteristics is a unit length, converting the superposed acoustic wave characteristics into pictures and establishing a superposed acoustic wave characteristic database, and only establishing a corresponding relation as the superposed acoustic wave characteristics are different from actual acoustic wave characteristics propagated under the same conditions, namely, the superposed acoustic wave characteristics are in one-to-one correspondence with the actual acoustic wave characteristics and establishing the actual acoustic wave characteristic database;
The method comprises the steps of carrying out image conversion on sound waves received by a sound wave receiver, inputting the sound waves into an image recognition model, recognizing the same image from an actual sound wave characteristic database by the image recognition model, and recognizing the image in the corresponding superimposed sound wave characteristic database according to the corresponding relation, so as to determine the combination condition of cable segments corresponding to superimposed sound wave characteristics, and further recognize the damage types and the damage positions of the cables.
A communication cable data management apparatus comprising:
The data acquisition module is used for acquiring sensor data;
the sound wave receiving module is used for generating sound waves according to the sound wave generator and receiving sound wave data transmitted through the cable through the sound wave receiver;
The data transmission module is used for transmitting the acquired sensor data and acoustic wave data to the communication subsystem, and converting the acquired sensor data and acoustic wave data into digital signals through an analog-to-digital converter of the communication subsystem;
The data processing module is used for transmitting the digital signals to the data processing server, and the data processing server processes the received digital signals, and specifically comprises the following steps:
establishing a cable natural aging propagation acoustic wave characteristic database, acquiring acoustic wave characteristics of propagation of acoustic waves at different stages in the cable natural aging process, and converting the acoustic wave characteristics into images, wherein the cable natural aging propagation acoustic wave characteristic database is a database formed by the images;
Establishing a cable damage propagation sound wave characteristic database, acquiring sound wave characteristics of sound waves propagated in a damaged cable, and converting the sound wave characteristics into images, wherein the cable damage propagation sound wave characteristic database is a database formed by the images;
Establishing an acoustic wave characteristic superposition database, superposing acoustic wave characteristics of the cable damage propagation acoustic wave characteristic database with acoustic wave characteristics of the cable natural aging propagation acoustic wave at different stages, and converting the superposed acoustic wave characteristics into an image, wherein the acoustic wave characteristic superposition database is a database formed by the image;
constructing a deep learning model;
And inputting an acoustic wave image to be detected into the constructed deep learning model, identifying a corresponding image from an acoustic wave characteristic superposition database through the deep learning model, and determining the cable damage type.
The invention has the technical effects and advantages that: the data monitoring is comprehensive, and the temperature, the methane content, the CO content and the water level height of the cable are respectively monitored through a temperature sensor, a methane sensor, a CO sensor and a water level sensor; a partial discharge sensor is also arranged to monitor the discharge condition of the cable joint position;
converting the propagation characteristics of sound waves in the cable into image data by arranging a sound wave generator and a sound wave receiver, establishing a database, and identifying the fault type and the fault position of the cable by adopting an image identification technology;
Through comprehensive cable data monitoring and accurate fault judgment and fault position judgment, the management and maintenance of the cable are convenient, the efficiency is high, and the coping time is more sufficient.
Drawings
FIG. 1 is a flow chart of a communication cable data management method of the present invention;
FIG. 2 is a block diagram of a communication subsystem of the present invention;
FIG. 3 is a flowchart of image recognition based on an acoustic signature overlay database;
Fig. 4 is a schematic diagram showing the identification of the type of cable damage and the damage position according to the present invention.
Detailed Description
The following describes the embodiments of the present invention further with reference to the drawings. The description of these embodiments is provided to assist understanding of the present invention, but is not intended to limit the present invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
The invention provides a communication cable data management method as shown in fig. 1, which comprises the following steps:
step one, collecting sensor data, namely installing a temperature sensor, a methane sensor, a CO sensor and a water level sensor at a proper position of a communication cable, and respectively measuring the temperature, the methane content, the CO content and the water level at the position;
A partial discharge sensor is arranged at the position of the cable joint, and the discharge parameter of the communication cable is measured from the outside through the partial discharge sensor; specifically, when the cable joint is provided with an explosion-proof shell, the main sensor and the auxiliary sensor of the partial discharge sensor are respectively arranged at two sides of the cable joint, and the installation positions are within the range of 1 meter at two sides of the cable joint; the main function of this mounting is to ensure that the partial discharge signal can be accurately captured and measured; the matching work of the main sensor and the auxiliary sensor can realize the whole coverage of discharge signals, thereby improving the accuracy and the reliability of detection; when the cable joint has no explosion-proof shell, the main sensor of the partial discharge sensor is arranged on one side of the cable joint, the auxiliary sensor is arranged on the outer cable body on the other side of the cable joint, and the installation position is also kept within the range of 1 meter on two sides of the cable joint. The main sensor is responsible for directly measuring the discharge signal at the cable joint, and the auxiliary sensor is used as a supplement to measure the signal on the cable body, so that more comprehensive discharge information is provided; coupling a partial discharge pulse current signal of the cable joint through a partial discharge sensor; if no other cables are nearby the monitored cable, a noise sensor can be installed at the position, which is 5m away from the local discharge sensor, of the monitored cable and used for collecting noise signals, and through analysis of the noise signals, factors which possibly interfere with the local discharge signals, such as an external electromagnetic field, mechanical vibration and the like, can be identified, so that the noise sensor is helpful for filtering out the interference signals in subsequent data processing, and the detection accuracy is improved.
Step two, installing an acoustic wave generator and an acoustic wave receiver on the cable, wherein the acoustic wave generator is used for generating fixed-frequency acoustic waves, and the acoustic wave receiver is used for receiving the acoustic waves; the sound wave generated by the sound wave generator is received by the sound wave receiver after being transmitted by different protective layers of the cable, and the transmission characteristics of the sound wave in different media are different, so that the sound wave in different cable protective layers can be distinguished;
Step three, the acquired analog signals are transmitted to a communication subsystem, the analog signals are converted into digital signals through an analog-to-digital converter of the communication subsystem, the communication subsystem further comprises a lower computer, an upper computer and a communication controller, the communication controller comprises a CAN module and a CAN control module, the CAN module is arranged on the lower computer, the CAN control module is arranged on the upper computer, the digital signals are transmitted to the upper computer through a CAN bus protocol by the CAN module of the lower computer and the CAN control module of the upper computer, and the module structure is shown in figure 2;
Specifically, the upper computer is also provided with a storage module, a liquid crystal module and a keyboard module, wherein the storage module is used for storing data, the liquid crystal module is used for displaying, and the keyboard module is used for inputting by a keyboard; the data information can be displayed through the liquid crystal module, and the keyboard module is used for configuring parameters of the upper computer;
The data processing server receives data information from the upper computer through the Ethernet and integrates, processes and stores the collected data information;
The method comprises the steps of setting corresponding alarm thresholds for detection data such as a temperature sensor, a methane sensor, a CO sensor and a water level sensor in a data processing server, alarming when the detection data exceeds the alarm thresholds, and sending alarm information to a monitoring background and mobile equipment in a wired mode and a wireless mode, so that staff can deal with the alarm in time; after processing, the staff uploads the processing mode to a data processing server in a text, picture or video mode;
Detecting basic partial discharge parameters such as discharge capacity, discharge phase, discharge times and the like through data acquired by the partial discharge sensor, alarming if the discharge parameters are abnormal, and reporting a worker to carry out corresponding maintenance treatment;
Specifically, after the upper computer collects the data, judging whether a link with the data processing server is smooth, if so, uploading the data to the data processing server through an Ethernet after packaging the data, and if not, temporarily storing the data in a storage module of the upper computer; when the link with the data processing server is detected to be unobstructed, the data stored in the storage module is continuously transmitted to the data processing server.
Wherein, the collected sound wave information is processed;
Establishing a cable natural aging propagation acoustic wave characteristic database: acquiring the acoustic wave characteristics of the acoustic wave transmitted at different stages in the natural aging process of the cable, converting the acoustic wave characteristics into images, and storing the images in a natural aging transmission acoustic wave characteristic database of the cable;
Establishing a cable damage propagation acoustic wave characteristic database: acquiring sound wave characteristics of sound waves transmitted in a damaged cable, converting the sound wave characteristics into images, and storing the images in a cable damage transmission sound wave characteristic database;
Acoustic wave feature superposition database: superposing the acoustic wave characteristics of the cable damage propagation acoustic wave characteristic database with the acoustic wave characteristics of the cable natural aging propagation acoustic wave at different stages, and converting the superposed acoustic wave characteristics into images to obtain a database of the cable damage propagation acoustic wave characteristics at different stages of cable aging;
the method comprises the steps of constructing a deep learning model, wherein a convolutional neural network is adopted as the deep learning model for image recognition;
data division, namely extracting image data in a database, and dividing the image data into a training set, a verification set and a test set; the training set is used for training the model, the verification set is used for adjusting the super parameters of the model, and the test set is used for evaluating the performance of the model;
Establishing a model, inputting the model into a convolutional neural network by using a training set, and training the model; the trained model uses the image of the verification set to verify, and the super parameters of the model are adjusted; inputting a test set to the model to test the model, and determining the availability, performance and accuracy of the model;
As shown in fig. 3, after the upper computer sends a detection signal, the sound wave generator sends sound waves, the sound wave receiver receives the sound waves, converts the received sound waves into image data, inputs the image data into an established image recognition model, firstly compares the image recognition model with a sound wave feature superposition database to perform image recognition, and if a corresponding image can be recognized, determines the type of cable damage according to the recognized image, and reminds a worker to perform corresponding maintenance treatment; if the cable is not identified, comparing the cable with a natural aging propagation acoustic wave characteristic database, carrying out image identification, if the corresponding image can be identified, judging that the cable is normal and belongs to natural aging, determining the natural aging stage of the cable, and reminding a worker to carry out corresponding maintenance treatment when the cable is in a stage of serious aging, so that the problems of short circuit, breakdown and the like of the cable caused by natural aging of a cable protection layer are avoided; if the sound wave characteristics are not recognized, performing manual inspection, converting the sound wave characteristics into pictures, storing the pictures in a cable damage propagation sound wave characteristic database, overlapping the sound wave characteristics of the cable natural aging propagation sound waves in different stages, converting the sound wave characteristics into picture data, storing the picture data in the sound wave characteristic overlapping database, and marking corresponding damage types; the database capacity is increased so that the same type of cable damage type is again encountered and identifiable.
As shown in fig. 4, as an embodiment of the present invention, the cable between the acoustic wave generator and the acoustic wave receiver is divided into 5 equidistant segments, acoustic wave characteristics of acoustic waves propagating in different segments, such as acoustic wave characteristic a, are obtained respectively, different equidistant damaged cables are obtained, acoustic wave characteristics of acoustic waves propagating in the different equidistant damaged cables, such as acoustic wave characteristic b, are obtained, and the cable segment corresponding to the acoustic wave characteristic b is the damaged cable; the length of a cable between the sound wave generator and the sound wave receiver is used as a unit length, the obtained sound wave characteristics are overlapped to obtain overlapped sound wave characteristics, in the embodiment, the first 4 sections are taken as sound wave characteristics a, the 5 th section is taken as sound wave characteristics b, and the combination is carried out, wherein the sum of cable sections corresponding to the overlapped sound wave characteristics is used as a unit length L, the overlapped sound wave characteristics are converted into pictures, an overlapped sound wave characteristic database is built, as the overlapped sound wave characteristics are different from the actual sound wave characteristics propagated under the same condition, only a corresponding relation is needed to be built, namely, the overlapped sound wave characteristics c are in one-to-one correspondence with the actual sound wave characteristics d, an actual sound wave characteristic database is built, the sound wave received by the sound wave receiver is input into an image recognition model after being subjected to image conversion, the image recognition model recognizes the same images as the images corresponding to the sound wave characteristics d from the actual sound wave characteristic database, and the images corresponding to the sound wave characteristics c are recognized according to the corresponding relation, so that the images corresponding to the overlapped sound wave characteristics database, namely, the images corresponding to the sound wave characteristics c are recognized, the combination situation of the cable sections corresponding to the overlapped sound wave characteristics can be determined, namely, the damage positions of cable sections corresponding to the overlapped sound wave characteristics are recognized, namely, the damage positions of cable sections 1, cable sections 2, cable sections 3, cable sections 4 and cable sections 5 can be recognized as the damage positions of the cable sections.
And fifthly, recording and storing the detected sensor data, the cable damage types, the cable damage positions and the personnel maintenance conditions on the cloud platform in an image-text mode, so that the monitoring background and the mobile equipment can be conveniently inquired and managed in real time.
The invention also provides a communication cable data management device, which comprises:
The data acquisition module is used for acquiring sensor data;
the sound wave receiving module is used for generating sound waves according to the sound wave generator and receiving sound wave data transmitted through the cable through the sound wave receiver;
The data transmission module is used for transmitting the acquired sensor data and acoustic wave data to the communication subsystem, and converting the acquired sensor data and acoustic wave data into digital signals through an analog-to-digital converter of the communication subsystem;
The data processing module is used for transmitting the digital signals to the data processing server, and the data processing server processes the received digital signals, and specifically comprises the following steps:
establishing a cable natural aging propagation acoustic wave characteristic database, acquiring acoustic wave characteristics of propagation of acoustic waves at different stages in the cable natural aging process, and converting the acoustic wave characteristics into images, wherein the cable natural aging propagation acoustic wave characteristic database is a database formed by the images;
Establishing a cable damage propagation sound wave characteristic database, acquiring sound wave characteristics of sound waves propagated in a damaged cable, and converting the sound wave characteristics into images, wherein the cable damage propagation sound wave characteristic database is a database formed by the images;
Establishing an acoustic wave characteristic superposition database, superposing acoustic wave characteristics of the cable damage propagation acoustic wave characteristic database with acoustic wave characteristics of the cable natural aging propagation acoustic wave at different stages, and converting the superposed acoustic wave characteristics into an image, wherein the acoustic wave characteristic superposition database is a database formed by the image;
constructing a deep learning model;
And inputting an acoustic wave image to be detected into the constructed deep learning model, identifying a corresponding image from an acoustic wave characteristic superposition database through the deep learning model, and determining the cable damage type.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (8)
1. A method of managing data of a communication cable, comprising the steps of:
1) Collecting sensor data;
2) The sound wave generator generates sound waves and receives sound wave data transmitted through the cable through the sound wave receiver;
3) Transmitting the acquired sensor data and acoustic wave data to a communication subsystem, and converting the acquired sensor data and acoustic wave data into digital signals through an analog-to-digital converter of the communication subsystem;
4) Transmitting the digital signals to a data processing server, and processing the received digital signals through the data processing server, wherein the method comprises the following specific steps of:
4.1 Establishing a cable natural aging propagation acoustic wave characteristic database, acquiring acoustic wave characteristics of propagation of acoustic waves at different stages in the cable natural aging process, and converting the acoustic wave characteristics into images, wherein the cable natural aging propagation acoustic wave characteristic database is a database formed by the images;
4.2 Establishing a cable damage propagation sound wave characteristic database, acquiring sound wave characteristics of sound waves propagated in a damaged cable, and converting the sound wave characteristics into images, wherein the cable damage propagation sound wave characteristic database is a database formed by the images;
4.3 Establishing an acoustic wave characteristic superposition database, superposing acoustic wave characteristics of the cable damage propagation acoustic wave characteristic database with acoustic wave characteristics of the cable natural aging propagation acoustic wave at different stages, and converting the superposed acoustic wave characteristics into an image, wherein the acoustic wave characteristic superposition database is a database formed by the image;
4.4 Constructing a deep learning model;
4.5 Inputting a sound wave image to be detected into the constructed deep learning model, identifying a corresponding image from a sound wave feature superposition database through the deep learning model, and determining the cable damage type; the specific method comprises the following steps:
converting received sound waves into image data, inputting the image data into an established image recognition model, comparing the image recognition model with a sound wave characteristic superposition database, performing image recognition, and if a corresponding image can be recognized, determining the cable damage type according to the recognized image, and reminding a worker of performing corresponding maintenance treatment; if the cable is not identified, comparing the cable with a natural aging propagation acoustic wave characteristic database, carrying out image identification, if the corresponding image can be identified, judging that the cable is normal and belongs to natural aging, determining the natural aging stage of the cable, and reminding a worker to carry out corresponding maintenance treatment when the cable is in a stage of serious aging, so that the problems of short circuit and breakdown of the cable caused by natural aging of a cable protection layer are avoided; if the damage type is not recognized, performing manual inspection, converting the sound wave characteristics into pictures, storing the pictures in a cable damage propagation sound wave characteristic database, and marking the corresponding damage type; increasing the database capacity so that the same type of cable damage type can be identified when the same type of cable damage type is encountered again;
5) And recording and storing the detected sensor data and the cable damage type in a cloud platform in an image-text mode, so that the monitoring background and the real-time query and management of the mobile equipment are facilitated.
2.A method of communication cable data management according to claim 1, wherein: the sensor data acquired in the step 1) comprise a temperature sensor, a methane sensor, a CO sensor and a water level sensor which are respectively used for acquiring temperature, methane content, CO content and water level height.
3. A method of communication cable data management according to claim 2, wherein: the sensor data acquired in the step 1) comprise discharge parameters acquired by a partial discharge sensor; the local discharge sensor is arranged at the position of the cable joint, when the cable joint is provided with an explosion-proof shell, the main sensor and the auxiliary sensor of the local discharge sensor are respectively arranged at two sides of the cable joint, when the cable joint does not have the explosion-proof shell, the main sensor of the local discharge sensor is arranged at one side of the cable joint, and the auxiliary sensor is arranged on the outer cable body at the other side of the cable joint.
4. A method of communication cable data management according to claim 1, wherein: the communication subsystem in the step 3) comprises an analog-to-digital converter, a lower computer, an upper computer and a communication controller, wherein the communication controller comprises a CAN module and a CAN control module, the CAN module is arranged on the lower computer, the CAN control module is arranged on the upper computer, and digital signals converted by the analog-to-digital converter are transmitted to the upper computer through a CAN bus protocol between the CAN module of the lower computer and the CAN control module of the upper computer.
5. A method of communication cable data management according to claim 4, wherein: the upper computer is also provided with a storage module, a liquid crystal module and a keyboard module, wherein the storage module is used for storing data, the liquid crystal module is used for displaying, and the keyboard module is used for inputting by a keyboard.
6. A method of communication cable data management according to claim 3, wherein: the data processing server in the step 4) sets an alarm threshold value of detection data of a temperature sensor, a methane sensor, a CO sensor, a water level sensor and a partial discharge sensor, and alarms when the detection data exceeds the alarm threshold value, and alarm information is sent to a monitoring background and mobile equipment so that staff can timely deal with the detection data; after processing, the staff uploads the processing mode to the data processing server in a text, picture or video mode.
7. A method of communication cable data management according to claim 1, wherein: the method for detecting the damage type and the damage position of the cable by the data processing server comprises the following steps:
dividing a cable between the sound wave generator and the sound wave receiver into a plurality of equidistant sections, and respectively acquiring sound wave characteristics of sound waves transmitted in different sections;
acquiring equidistant different types of damaged cables, and acquiring sound wave characteristics of sound waves propagating in the equidistant different types of damaged cables;
The method comprises the steps of taking the length of a cable between an acoustic wave generator and an acoustic wave receiver as a unit length, superposing the obtained acoustic wave characteristics to obtain superposed acoustic wave characteristics, wherein the sum of cable sections corresponding to the superposed acoustic wave characteristics is a unit length, converting the superposed acoustic wave characteristics into pictures and establishing a superposed acoustic wave characteristic database, and only establishing a corresponding relation as the superposed acoustic wave characteristics are different from actual acoustic wave characteristics propagated under the same conditions, namely, the superposed acoustic wave characteristics are in one-to-one correspondence with the actual acoustic wave characteristics and establishing the actual acoustic wave characteristic database;
The method comprises the steps of carrying out image conversion on sound waves received by a sound wave receiver, inputting the sound waves into an image recognition model, recognizing the same image from an actual sound wave characteristic database by the image recognition model, and recognizing the image in the corresponding superimposed sound wave characteristic database according to the corresponding relation, so as to determine the combination condition of cable segments corresponding to superimposed sound wave characteristics, and further recognize the damage types and the damage positions of the cables.
8. A communication cable data management apparatus, comprising:
The data acquisition module is used for acquiring sensor data;
the sound wave receiving module is used for generating sound waves according to the sound wave generator and receiving sound wave data transmitted through the cable through the sound wave receiver;
The data transmission module is used for transmitting the acquired sensor data and acoustic wave data to the communication subsystem, and converting the acquired sensor data and acoustic wave data into digital signals through an analog-to-digital converter of the communication subsystem;
The data processing module is used for transmitting the digital signals to the data processing server, and the data processing server processes the received digital signals, and specifically comprises the following steps:
establishing a cable natural aging propagation acoustic wave characteristic database, acquiring acoustic wave characteristics of propagation of acoustic waves at different stages in the cable natural aging process, and converting the acoustic wave characteristics into images, wherein the cable natural aging propagation acoustic wave characteristic database is a database formed by the images;
Establishing a cable damage propagation sound wave characteristic database, acquiring sound wave characteristics of sound waves propagated in a damaged cable, and converting the sound wave characteristics into images, wherein the cable damage propagation sound wave characteristic database is a database formed by the images;
Establishing an acoustic wave characteristic superposition database, superposing acoustic wave characteristics of the cable damage propagation acoustic wave characteristic database with acoustic wave characteristics of the cable natural aging propagation acoustic wave at different stages, and converting the superposed acoustic wave characteristics into an image, wherein the acoustic wave characteristic superposition database is a database formed by the image;
constructing a deep learning model;
inputting an acoustic wave image to be detected into the constructed deep learning model, identifying a corresponding image from an acoustic wave feature superposition database through the deep learning model, and determining the cable damage type; the specific method comprises the following steps:
Converting received sound waves into image data, inputting the image data into an established image recognition model, comparing the image recognition model with a sound wave characteristic superposition database, performing image recognition, and if a corresponding image can be recognized, determining the cable damage type according to the recognized image, and reminding a worker of performing corresponding maintenance treatment; if the cable is not identified, comparing the cable with a natural aging propagation acoustic wave characteristic database, carrying out image identification, if the corresponding image can be identified, judging that the cable is normal and belongs to natural aging, determining the natural aging stage of the cable, and reminding a worker to carry out corresponding maintenance treatment when the cable is in a stage of serious aging, so that the problems of short circuit and breakdown of the cable caused by natural aging of a cable protection layer are avoided; if the damage type is not recognized, performing manual inspection, converting the sound wave characteristics into pictures, storing the pictures in a cable damage propagation sound wave characteristic database, and marking the corresponding damage type; the database capacity is increased so that the same type of cable damage type is again identifiable.
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Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104090214A (en) * | 2014-07-31 | 2014-10-08 | 成都高斯电子技术有限公司 | Cable fault detection and aging analysis method |
CN113917278A (en) * | 2021-09-08 | 2022-01-11 | 西安理工大学 | Cable fault positioning method based on sound wave temperature measurement |
Family Cites Families (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2016099280A (en) * | 2014-11-25 | 2016-05-30 | 住友電気工業株式会社 | Abnormality detection method for water bottom cable, water bottom cable and abnormality detection device for water bottom cable |
CN111999382A (en) * | 2020-09-17 | 2020-11-27 | 海南电网有限责任公司电力科学研究院 | Cable partial discharge characteristic parameter extraction method considering insulation aging |
CN112615311B (en) * | 2020-12-28 | 2022-05-24 | 海南电网有限责任公司琼海供电局 | Fault point positioning device for power transmission line inspection |
CN113391166A (en) * | 2021-06-18 | 2021-09-14 | 国网吉林省电力有限公司吉林供电公司 | Portable overhead distribution line fault detection device based on ultrasonic intelligent detection |
CN217157706U (en) * | 2022-04-11 | 2022-08-09 | 威海威高医疗影像科技有限公司 | Active noise reduction medical equipment |
KR20230152936A (en) * | 2022-04-28 | 2023-11-06 | 주식회사 싸이콤 | Method for contactless diagnosing power facility using artificial intelligence and signal processing technology and device using the same |
CN115047290A (en) * | 2022-06-07 | 2022-09-13 | 国网山西省电力公司大同供电公司 | Cable fault discharge sound detection method based on deep learning |
CN116297835A (en) * | 2023-02-15 | 2023-06-23 | 国网河北省电力有限公司石家庄供电分公司 | Ultrasonic detection device and method for detecting cable aging |
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Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104090214A (en) * | 2014-07-31 | 2014-10-08 | 成都高斯电子技术有限公司 | Cable fault detection and aging analysis method |
CN113917278A (en) * | 2021-09-08 | 2022-01-11 | 西安理工大学 | Cable fault positioning method based on sound wave temperature measurement |
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