CN112731086A - Method and system for comprehensively inspecting electric power equipment - Google Patents
Method and system for comprehensively inspecting electric power equipment Download PDFInfo
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Abstract
The invention discloses a method and a system for comprehensively inspecting electric power equipment, wherein the method comprises the following steps: acquiring a surface temperature signal and an ultrasonic signal of detection equipment and operation condition data of the detection equipment, and respectively generating an infrared thermal imaging image and a sound wave image based on the surface temperature signal and the ultrasonic signal; sending the infrared thermal imaging image, the sound wave image and the detection equipment operation condition data to a cloud platform for storage; compounding the positioning sound source signals in the sound wave image to the infrared thermal imaging image to generate a composite thermal image; extracting a sonic fingerprint based on the sonic image; and judging the fault severity of the detection equipment based on the operation condition data of the detection equipment and the composite thermal image, and judging the fault type of the detection equipment according to the acoustic fingerprint.
Description
Technical Field
The invention relates to the technical field of live detection of key equipment of an electric power system, in particular to a method and a system for comprehensively inspecting electric power equipment.
Background
The power equipment is an important component in the power system, the safe and reliable operation of the power equipment has important significance on the stability and the safety of the power system, and as the structure and the function of the power equipment are increasingly complicated, the state detection and fault diagnosis system of the power equipment is increasingly applied. The problem that how to effectively master the health state of key power equipment of a distribution network is a problem to be solved urgently in the power industry is just caused by the fact that the number of the equipment is continuously increased along with the continuous expansion of the scale of the distribution network.
The most intuitive and commonly used parameter for characterizing the abnormality of the power equipment is the temperature, most equipment faults can be detected by observing the change of the temperature value, and the thermal state distribution condition of the equipment is an important characteristic for judging the running condition of the equipment. The infrared imaging technology is a charged detection technology which is very suitable for being applied to power equipment, judges whether the equipment normally operates or not according to the thermal state distribution of the power equipment, and has the advantages of no contact, quick response, no stop, long distance, convenience in observation and the like, so that the fault of the power equipment can be detected through the infrared thermal imaging technology.
Besides the expression of heat generation, common faults of the electrical equipment are also usually expressed as mechanical faults and partial discharges, and when the electrical equipment vibrates mechanically, a sound wave signal is emitted, and a large amount of vibration information is contained in the signal. When the equipment normally runs, the sound emitted by the equipment is different corresponding to different states of mutual motion of the machine body, the firmware, the parts and the parts, the sound generated by the power equipment is changed when a fault occurs in the running process, and when the power equipment generates partial discharge, a corresponding ultrasonic signal can be generated at a partial discharge point. Therefore, the acoustic signal of the power equipment contains abundant information such as vibration and partial discharge, and is an important index for analyzing the operation state of the equipment.
The two detection methods have many advantages but many defects, the infrared thermal imaging technology is used for detecting the faults of the power equipment, the sensitivity and the accuracy are high, the coverage area is wide, but only the fault type with large surface temperature change can be detected, the internal defects of the equipment are difficult to detect, the positioning of the fault position is difficult to be accurate and can only be reduced to an approximate range, the acoustic wave imaging technology can realize the accurate positioning of the fault position and can further judge the fault type, and the combined use of the two methods can complement the advantages.
The prior art (application number CN201810850846.2) discloses an insulator detection unmanned aerial vehicle and a method based on infrared thermal imagery and visible light, the device relates to power transmission and transformation circuit maintenance equipment technical field, contain unmanned aerial vehicle, detection module, wireless transmission module and ground station, shoot through infrared thermal imagery and visible light and realize carrying out remote non-contact electrified detection to insulator chain internal degradation, outside damage and filth grade, improve the efficiency and the rate of accuracy that detect, and promote detection personnel's security, reduce working strength. According to the method, the unmanned aerial vehicle is used as a carrier, safety performance is greatly improved, two equipment faults of temperature abnormity and external damage are considered, but the fault judgment ground station draws a line graph through temperature information acquired by infrared equipment to judge, the judgment process is time-consuming and unintuitive, and only whether the equipment generates heat or not can be judged, and the reason and the position of generating heat cannot be judged.
The prior art (application number CN201811339724.3) discloses a method for detecting the electrification of high-voltage power equipment, which adopts a method of ultraviolet imaging and ultrasonic wave combined detection, wherein the detection equipment comprises an ultraviolet imager, an ultraviolet camera, an ultraviolet filter, an ultrasonic transmitting and receiving device, an ultrasonic imager and a light shielding plate.
The prior art (application number CN201921931562.2) discloses a hand-held power ultrasonic imaging detection device, which is characterized in that an ultrasonic receiver is installed in a detection shell, a display screen is installed at the other end of the detection shell, a light screen and a handle grip are respectively and detachably installed at the upper side and the lower side of the detection shell, and a wave gathering tube is further arranged at one end of the ultrasonic receiver extending out of the detection shell. The system realizes the detection of the electrical equipment fault by using the sound wave imaging technology, solves the problem that the display screen of the current power failure sound wave imaging device is easy to reflect light seriously under strong light, but the detection device needs to be held by an operator, has low safety factor, is only limited to the faults of mechanical vibration or local discharge and the like which generate sound waves, is not perfect in system setting, only stops at the electrified detection and does not consider the whole system structure, and does not have a record part of historical data.
The prior art (application number CN202010501236.9) discloses a method and a system for intelligently diagnosing defects of a power transformation device based on infrared images, which analyze infrared images of the power transformation device by using a YOLO deep learning model and a data analysis method, and realize automatic identification and intelligent diagnosis of the defects of the components of the power transformation device in the infrared images through the steps of component positioning of the power transformation device, temperature feature extraction, temperature threshold judgment and the like. The method solves the problems of the infrared diagnosis method of simple image analysis or manual threshold setting, improves the reliability and accuracy of the infrared image defect diagnosis of the power transformation equipment, but is not accurate enough for fault positioning and not visual enough for presenting results.
Therefore, a technique is needed to realize comprehensive inspection of the electric power equipment.
Disclosure of Invention
The technical scheme of the invention provides a method and a system for comprehensively inspecting electric power equipment, which aim to solve the problem of how to comprehensively inspect the electric power equipment.
In order to solve the above problems, the present invention provides a method for comprehensive inspection of electric power equipment, the method including:
acquiring a surface temperature signal and an ultrasonic signal of detection equipment and operation condition data of the detection equipment, and respectively generating an infrared thermal imaging image and a sound wave image based on the surface temperature signal and the ultrasonic signal;
sending the infrared thermal imaging image, the sound wave image and the detection equipment operation condition data to a cloud platform for storage; compounding the positioning sound source signals in the sound wave image to the infrared thermal imaging image to generate a composite thermal image; extracting a sonic fingerprint based on the sonic image;
and judging the fault severity of the detection equipment based on the operation condition data of the detection equipment and the composite thermal image, and judging the fault type of the detection equipment according to the acoustic fingerprint.
Preferably, the method further comprises the following steps: the mobile equipment is provided with a power supply module, a GPS navigation module, a control module, an infrared acquisition module, a sound wave acquisition module, a data processing module and a signal transmission module.
Preferably, the method comprises the following steps:
sending a routing inspection route instruction to a control module of the mobile equipment;
navigating the mobile equipment according to the routing inspection instruction based on a GPS navigation module;
acquiring a surface temperature signal of the detection equipment through the infrared acquisition module, and generating the infrared thermal imaging image;
and acquiring an ultrasonic signal of the detection equipment through the sound wave acquisition module, and generating the sound wave image.
Preferably, the fault is located through the sound wave image, and a sound source locating signal is obtained, wherein the sound source locating method includes: time difference of arrival methods, steerable beamforming methods, and high resolution spectrum estimation methods.
Preferably, wherein the acquisition of localized sound source signals using the high resolution spectral estimation method comprises:
establishing a sound source signal matrix of an ultrasonic signal, and performing phase compensation on the sound source signal matrix;
calculating the compensated sound source signal matrix to obtain a covariance matrix of the sound source signal;
decomposing the covariance matrix to obtain a signal subspace and a noise subspace;
establishing a spatial search function based on the signal subspace and the noise subspace;
carrying out space search on the space search function to obtain a function spectrum peak direction, and determining a direction of arrival angle of a sound source signal in the ultrasonic signal according to the function spectrum peak direction;
and determining a positioning sound source signal according to the direction of arrival angle of the sound source signal.
Based on another aspect of the present invention, the present invention provides a system for comprehensive inspection of electric power equipment, the system comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a surface temperature signal of detection equipment, an ultrasonic signal and operation condition data of the detection equipment, and respectively generating an infrared thermal imaging image and a sound wave image based on the surface temperature signal and the ultrasonic signal;
the processing unit is used for sending the infrared thermal imaging image, the sound wave image and the detection equipment operation condition data to a cloud platform for storage; compounding the positioning sound source signals in the sound wave image to the infrared thermal imaging image to generate a composite thermal image; extracting a sonic fingerprint based on the sonic image;
and the judging unit is used for judging the fault severity of the detection equipment based on the operation condition data of the detection equipment and the composite thermal image and judging the fault type of the detection equipment according to the acoustic fingerprint.
Preferably, the acquisition unit is further configured to: the mobile equipment is provided with a power supply module, a GPS navigation module, a control module, an infrared acquisition module, a sound wave acquisition module, a data processing module and a signal transmission module.
Preferably, the method comprises the following steps:
sending a routing inspection route instruction to a control module of the mobile equipment;
navigating the mobile equipment according to the routing inspection instruction based on a GPS navigation module;
acquiring a surface temperature signal of the detection equipment through the infrared acquisition module, and generating the infrared thermal imaging image;
and acquiring an ultrasonic signal of the detection equipment through the sound wave acquisition module, and generating the sound wave image.
Preferably, the processing unit is further configured to: and positioning the fault through the sound wave image to obtain a positioning sound source signal, wherein the positioning sound source method comprises the following steps: time difference of arrival methods, steerable beamforming methods, and high resolution spectrum estimation methods.
Preferably, wherein the acquisition of localized sound source signals using the high resolution spectral estimation method comprises:
establishing a sound source signal matrix of an ultrasonic signal, and performing phase compensation on the sound source signal matrix;
calculating the compensated sound source signal matrix to obtain a covariance matrix of the sound source signal;
decomposing the covariance matrix to obtain a signal subspace and a noise subspace;
establishing a spatial search function based on the signal subspace and the noise subspace;
carrying out space search on the space search function to obtain a function spectrum peak direction, and determining a direction of arrival angle of a sound source signal in the ultrasonic signal according to the function spectrum peak direction;
and determining a positioning sound source signal according to the direction of arrival angle of the sound source signal.
The invention can select and use various charged detection methods to monitor the fault aiming at the problem of partial discharge defects of different equipment, find abnormal phenomena existing in the equipment in time by playing the role of various advanced sensors, and diagnose the fault position and type. By comprehensively using different online monitoring methods, the reliability of the detection result can be improved, and more detailed reference information can be provided for equipment maintenance after diagnosis, so that the power failure maintenance time is saved, and the stable supply of electric power is ensured.
Drawings
A more complete understanding of exemplary embodiments of the present invention may be had by reference to the following drawings in which:
FIG. 1 is a flow chart of a method for comprehensive inspection of electrical equipment in accordance with a preferred embodiment of the present invention;
fig. 2 is a schematic diagram of a layered architecture of an unmanned aerial vehicle inspection system according to a preferred embodiment of the invention;
fig. 3 is a schematic structural view of a drone according to a preferred embodiment of the invention;
FIG. 4 is a schematic diagram of the principle of infrared thermographic inspection according to a preferred embodiment of the present invention;
FIG. 5 is a schematic diagram of the principles of acoustic imaging detection according to a preferred embodiment of the present invention;
fig. 6 is a schematic view of the inspection operation flow of the unmanned aerial vehicle according to the preferred embodiment of the invention;
fig. 7 is a schematic diagram of a field case test according to a preferred embodiment of the present invention; and
fig. 8 is a diagram illustrating a system for performing comprehensive inspection of electric power equipment according to a preferred embodiment of the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
Fig. 1 is a flowchart of a method for comprehensive inspection of electrical equipment according to a preferred embodiment of the present invention. The power inspection unmanned aerial vehicle system based on infrared detection and sound wave imaging detection can realize comprehensive physical examination of important electrical equipment and provide scientific and accurate basis for state detection. The invention discloses an overall design scheme of an electric power inspection unmanned aerial vehicle system based on infrared detection and acoustic imaging detection, which mainly comprises four layers, namely a data sensing layer, a network communication layer, a platform layer and an application layer, wherein the overall architecture of the system is shown in figure 2.
As shown in fig. 1, the present invention provides a method for comprehensive inspection of electrical equipment, the method comprising:
step 101: the method comprises the steps of collecting a surface temperature signal and an ultrasonic signal of detection equipment and operation condition data of the detection equipment, and respectively generating an infrared thermal imaging image and a sound wave image based on the surface temperature signal and the ultrasonic signal. Preferably, the method further comprises the following steps: the mobile equipment is provided with a power supply module, a GPS navigation module, a control module, an infrared acquisition module, a sound wave acquisition module, a data processing module and a signal transmission module. Preferably, the method comprises the following steps: sending the routing inspection route instruction to a control module of the mobile equipment; navigating the mobile equipment according to the routing inspection instruction based on the GPS navigation module; acquiring a surface temperature signal of the detection equipment through an infrared acquisition module, and generating an infrared thermal imaging image; and acquiring an ultrasonic signal of the detection equipment through the sound wave acquisition module, and generating a sound wave image.
The data perception layer mainly comprises a set of information acquisition equipment, an unmanned aerial vehicle is taken as a mobile equipment carrier for example, an infrared imager and an acoustic signal acquisition array are installed, and surface temperature signals and ultrasonic signals of the equipment are acquired and images are generated.
Step 102: sending the infrared thermal imaging image, the sound wave image and the detection equipment operation condition data to a cloud platform for storage; compounding a positioning sound source signal in the sound wave image to an infrared thermal imaging image to generate a composite thermal image; extracting the acoustic fingerprint based on the acoustic image. Preferably, the fault is located through the sound wave image, and a sound source locating signal is obtained, wherein the sound source locating method includes: time difference of arrival methods, steerable beamforming methods, and high resolution spectrum estimation methods. Preferably, wherein the localized sound source signal is acquired using a high resolution spectral estimation method, comprising: establishing a sound source signal matrix of the ultrasonic signal, and performing phase compensation on the sound source signal matrix; calculating the compensated sound source signal matrix to obtain a covariance matrix of the sound source signal; decomposing the covariance matrix to obtain a signal subspace and a noise subspace; establishing a spatial search function based on the signal subspace and the noise subspace; carrying out space search on the space search function to obtain a function spectrum peak direction, and determining a direction of arrival angle of a sound source signal in the ultrasonic signal according to the function spectrum peak direction; and determining a positioning sound source signal according to the direction of arrival angle of the sound source signal.
The network communication layer is used as an intermediate connection part and is connected with the data sensing layer and the platform application layer, and the 4G wireless communication technology is mainly utilized to transmit the acquired data in the unmanned aerial vehicle to the platform. The platform layer provides cloud service, all collected data are integrated mainly by using a server cluster, and the problems of data and image storage, retrieval, calling, classification, safety protection and the like are solved through a database management technology.
Step 103: and judging the fault severity of the detection equipment based on the operation condition data of the detection equipment and the composite thermal image, and judging the fault type of the detection equipment according to the acoustic fingerprint.
The application layer is used as a system management layer, analyzes various information through interaction with the platform layer, judges the current equipment running state, makes an alarm decision according to a set threshold, predicts by combining historical data, makes an early warning decision according to the set threshold, is provided with a fault type analysis module, judges the fault type by using an RBF neural network according to the extracted sound wave fingerprint, can control the unmanned aerial vehicle of the sensing layer, and sets the routing inspection times and routing inspection routes of the unmanned aerial vehicle.
The invention realizes situation perception, state early warning, fault analysis and trend prediction of the electrical equipment by the mutual cooperation of four layers of networks and the interaction of actual detection data and the system.
The invention is exemplified by using the unmanned aerial vehicle as a carrier, but the embodiment of the invention is not limited to the unmanned aerial vehicle as the carrier. The invention is characterized in that a power supply module, a GPS module, a flight control module, an infrared acquisition module, a sound wave acquisition module, a data processing module and a signal transmission module are arranged on an unmanned aerial vehicle, the unmanned aerial vehicle is reasonably patrolled and routed to the flight control module of the unmanned aerial vehicle in an application layer, the GPS navigation module navigates according to a specified route, infrared thermal imaging detection and sound wave imaging detection are adopted in the patrolling and routing process, an infrared thermal imager takes pictures and generates a thermal image, meanwhile, the sound wave imaging detection carries out fault location, temperature information and sound wave information are simultaneously transmitted to the data processing module for processing, the signal transmission module transmits the thermal image, the temperature and location information to a database, the database finishes the storage and the calling of data and images, utilizes edge calculation to eliminate error data, and compounds the location information into the thermal image to generate a compound thermal image, and the cloud platform analyzes by calling the data in the database, and making an alarm decision. The specific invention content is as follows:
1) and establishing a power inspection unmanned aerial vehicle system framework. The system mainly comprises a data perception layer, a network communication layer, a platform layer and an application layer.
2) And establishing a data perception layer. The unmanned aerial vehicle is used as a carrier, two detection methods of infrared thermal imaging and acoustic imaging are comprehensively used, and the method is used for acquiring the running state and working condition of equipment and mainly comprises temperature information, acoustic positioning information and a thermography.
3) And establishing a network communication layer. The unmanned aerial vehicle adopts wireless data transmission and picture transmission technology, guarantees the transmission with the high definition composite map.
4) And establishing a platform layer. The unmanned aerial vehicle online operation detection data are stored in a patrol inspection database configured based on a cloud platform, the problems of data and image storage, retrieval, calling, classification, safety protection and the like are solved, meanwhile, sound wave positioning information is compounded in the thermal image, a compound thermal image is generated, sound wave fingerprints are extracted according to a large amount of detection data, and the extracted sound wave fingerprints serve as a fault type judgment basis.
5) And establishing an application layer. The cloud platform calls data information and images in the routing inspection database to perform real-time analysis, alarm judgment is made according to a system preset method, fault severity is judged according to temperature conditions in the infrared thermography, fault types are judged according to sound wave fingerprints obtained through calculation, and meanwhile early warning judgment is made on non-fault parts by combining historical record data.
The implementation mode of the invention is easy to operate and has high safety: the system adopts the whole-course machine live detection, does not need power failure or short-distance detection of detection personnel, and has simple operation and stronger safety. The invention has short detection time and high sensitivity: and analyzing and judging the data information acquired by the equipment in real time through the cloud platform to reflect the running condition of the equipment. The invention has high reliability: the infrared thermal imaging and acoustic wave imaging double-method detection is adopted, and the reliability is high.
The following illustrates embodiments of the invention:
1. an electric power inspection unmanned aerial vehicle system based on infrared detection and sound wave imaging detection is established.
(1) The data requirements and important detection methods of the power inspection unmanned aerial vehicle system are extracted from the aspects of design, construction, operation and the like. The implementation mode of the invention mainly comprises four layers, namely a data perception layer, a network communication layer, a platform layer and an application layer.
(2) The digital source is solved through the data perception layer, mainly refer to the infrared thermal imaging and the online operational data of sound wave joint detection equipment that use unmanned aerial vehicle as the carrier.
(3) According to the data collected by the data perception layer, the network communication layer comprehensively uses various communication modes of image transmission and data transmission to transmit the collected information to the platform layer.
(4) The platform layer establishes a database according to the transmitted data to realize storage, data cleaning, query, calling and image processing of the data and the images, marks abnormal data by utilizing an edge computing technology, reduces the computing pressure of a central processing unit, and realizes all-round detection of the electrical equipment by comprehensively analyzing two detection results.
(5) The application layer is used as a system top layer, and by using an artificial intelligent algorithm cluster, a decision is made on whether to alarm or not, fault degree, fault location and fault type, and meanwhile fault prediction and unmanned aerial vehicle routing inspection planning are considered, so that data visualization is achieved. Wherein the data transmission is as shown in figure 6.
2. Establishing a data awareness layer
(1) The establishment uses four rotor unmanned aerial vehicle to equip as the detection of carrier, unmanned aerial vehicle installs power module, the GPS module, fly control module, infrared acquisition module, sound wave acquisition module, data processing module and signalling module, rationally patrol and examine the route planning and send unmanned aerial vehicle to and fly control module at the application layer to unmanned aerial vehicle, it takes off and stable to fly control module control unmanned aerial vehicle, GPS navigation module navigates according to appointed route, patrol and examine the route in-process and detect equipment. The structure of which is shown in figure 3.
(2) The unmanned aerial vehicle adopts the joint detection method of infrared thermal imaging detection and sound wave imaging detection, and the infrared thermal imaging instrument shoots and generates the thermograph, and conveys temperature information and sound wave information to the data processing module simultaneously for processing, and the signal transmission module sends the thermograph, the temperature and the positioning information to the database.
In the aspect of detection equipment, the principle of the thermal infrared imager is that infrared rays radiated by a receiving device are heated and converted into electric signals by utilizing a photoelectric element, and finally, a thermal image is displayed. During the detection, the infrared camera shoots, the light shielding plate is arranged on the camera, the imaging influence caused by strong light is avoided, on the equipment selection type, the thermal infrared imager for XM6A unmanned aerial vehicle adopting the company of Megao is an uncooled thermal infrared imaging temperature measuring device, the infrared detector model of the thermal infrared imager is UL04071, the thermal infrared imager is simple to operate but powerful and can be used for being carried on the unmanned aerial vehicle to collect infrared images, and the principle diagram of the thermal infrared imager is shown in figure 4.
The invention utilizes sound wave imaging detection to carry out accurate fault location, the sound wave imaging adopts a beam forming technology, selectable methods comprise an Arrival time difference method, a controllable beam forming method, a high resolution spectrum estimation method and the like, a high resolution spectrum estimation method is mainly introduced, the core Of the high resolution spectrum estimation is Direction Of Arrival angle (DOA) detection Of a sound source, the principle Of the method is that a microphone unit receives a sound source signal, a correlation matrix Of the sound source signal is obtained through calculation, a space spectrum is obtained through mathematical processing Of the matrix so as to complete space scanning, and the Direction with the maximum Arrival energy is considered to be the DOA Of a sound source point, so that the sound source is located, and a flow chart Of the method is shown in figure 5. The microphone array arrangement mode for receiving sound wave signals can adopt a one-dimensional array, a two-dimensional array, a three-dimensional array and the like, a cross linear array is adopted, and a sound tube is additionally arranged on each microphone collecting unit to collect sound waves and strengthen the sound wave collecting effect.
3. Establishing a network communication layer
(1) The communication between unmanned aerial vehicle and the database includes picture transmission and data transmission, adopts wireless transmission's mode, and the data of transmission mainly include infrared thermal image, temperature information and fault location information.
(2) The image transmission adopts a wireless transmission mode, and the compression module adopts an H.265 hard compression mode, so that the time is less and the effect is better compared with other modes. The wireless transmitting end in the unmanned aerial vehicle signal transmission module consists of two parts of an information modulation part and a power amplifier part, and the platform layer wireless receiving part consists of a buffer area and 3 modules of demodulation, decoding and display, so that the transmission and the transmission of high-quality video and focal length information can be completed, and the distance is up to 5 km.
In terms of bandwidth and protocol selection, the bandwidth is selected to be 2.4GHz or 5.8GHz, the latter can be made wider, but 5.8G is only 41.4% of 2.4G under the same transmission power and receiving sensitivity, the attenuation is more sensitive to water vapor, and the actual communication distance is less than 30%. And an RTP protocol is selected, and is simple and easy to incorporate.
4. Building a platform layer
(1) The tasks mainly completed by the platform layer mainly comprise the collection of raw data, the processing of image data and network security protection.
(2) Storing the original data into a database, selecting a MySQL database, and finishing the storage, query and call of the original data and the image.
(3) The data processing stage includes data cleaning, image processing and image compositing.
The invention adopts the technologies of edge calculation and the like to screen the temperature data and the positioning data, relieves the calculation pressure of network bandwidth and a central processing unit, marks obviously abnormal data and performs data cleaning, accelerates the data processing flow and provides a high-quality data source for subsequent composite images.
The invention adopts the edge processing technology to process the infrared thermal image, and the edge detection method is to strengthen the edge effect of the image, then utilize an edge detection operator to calculate the edge point set in a gradient way, finally judge the edge point set according to the set threshold value, and connect the points to form the edge. The classical edge detection operators include a Laplace operator, a Sobel operator, a Robert operator, a Canny operator and the like, and wavelet transformation and other methods can also be adopted.
The method compounds the obtained sound wave positioning information into the infrared thermograph to generate a compound thermograph, simultaneously displays multiple fault types such as temperature abnormity, mechanical vibration, partial discharge and the like in the image, realizes accurate positioning of the fault, combines two electrified detection methods, has complementary advantages, enables the detection result to be more visual, and realizes data visualization.
5. Establishing an application layer
(1) The application layer is used as a system top layer, the realization functions of the application layer mainly comprise fault alarm, fault early warning, fault degree judgment and fault type judgment, and the system functions are perfected from all aspects.
(2) And the fault alarm unit judges according to a threshold value set by the system. When the operating temperature of the equipment is detected to exceed a set threshold value or the phase temperature difference exceeds 20 ℃ in the infrared thermograph, the system alarms. When the acoustic wave signal exceeding 7dB is detected in the acoustic wave imaging detection, the system alarms.
(3) And the system calls the detected temperature and sound wave positioning data within 15 days, and makes a fault early warning decision by using an intelligent algorithm cluster for prediction.
(4) And dividing the fault severity into a general heating fault, a heating fault and a serious heating fault according to the temperature detection data standard. The temperature rise is defined as the difference between the fault operating temperature and the normal operating temperature.
The temperature rise range of the heating fault is 10-20 ℃ generally, or the actual temperature of the equipment is 30-60 ℃, and only slight thermal image characteristics exist on a thermal image. Such defects should enhance tracking and prevent deepening of the defect level.
The heating fault temperature rise range is 20-40 ℃, or the actual temperature is 60-90 ℃, the thermal image characteristics are obvious, the defect part has caused serious thermal damage, and the serious threat to the equipment operation is formed. Such defects should be monitored strictly and the shut down process should be scheduled as soon as conditions permit.
The temperature rise of a heating point of a serious heating fault exceeds 40 ℃ or the actual temperature is more than 90 ℃, and serious burn traces can be seen through appearance inspection. The defects can cause sudden accidents at any time, and the operation should be immediately applied for quitting, so that the complete overhaul is carried out.
(5) The fault severity is divided into general sound fault, sound fault and serious sound fault according to the sound wave signal detection data standard.
Typically, a sound fault detects 3-6dB decibels. Such defects should enhance tracking and prevent deepening of the defect level.
The sound fault is detected to be 7-15dB, the sound wave signal characteristic is obvious, and the defect part generates serious partial discharge or mechanical vibration, which seriously threatens the operation of equipment. Such defects should be monitored strictly and the shut down process should be scheduled as soon as conditions permit.
When serious heating faults are detected, decibel is larger than 15dB, sudden accidents can be caused by the defects, and the operation is immediately applied for quitting, so that thorough maintenance is carried out.
(5) And extracting fault sound wave fingerprints according to a large number of fault sound wave detection records and mathematical modeling analysis, and replacing a large number of data with a few representative parameters to be used as the basis for fault type diagnosis.
In this application, unmanned aerial vehicle tries to fly in three points in the afternoon, whole 60 minutes consuming time, unmanned aerial vehicle is through flying control center and GPS navigation module, the route according to the application layer planning detects overhead line part, utilize XM6A for unmanned aerial vehicle that loads on the unmanned aerial vehicle to take a candid photograph and combine the sound wave formation of image to jointly detect in the testing process, the discovery detects 8dB sound wave signal, no temperature variation, will generate the picture and adopt H.265 hard compression mode and carry out wireless picture with 2.4 GHz's frequency together with the locating data and pass. The platform layer decodes and processes the received image, and combines the positioning information detected by the acoustic imaging into a picture, and the processed picture is shown in fig. 7. And the platform layer uploads the pictures to the application layer, the application layer sets a threshold value of 7dB according to sound wave fault alarm, judges that the fault needs to be alarmed, and classifies the fault into a sound production fault according to preset fault degree. Meanwhile, the judgment is carried out according to the acoustic fingerprints, the application layer judges that the acoustic fingerprints belong to partial discharge faults rather than mechanical vibration, and finally, the detection and analysis results are put into a database to guide a subsequent maintenance plan.
Fig. 8 is a diagram illustrating a system for performing comprehensive inspection of electric power equipment according to a preferred embodiment of the present invention. As shown in fig. 8, the present invention provides a system for comprehensive inspection of electric power equipment, the system comprising:
the acquisition unit 801 is configured to acquire a surface temperature signal of the detection device, an ultrasonic signal, and operation condition data of the detection device, and generate an infrared thermal imaging image and an acoustic image based on the surface temperature signal and the ultrasonic signal, respectively. Preferably, the acquisition unit 801 is further configured to: the mobile equipment is provided with a power supply module, a GPS navigation module, a control module, an infrared acquisition module, a sound wave acquisition module, a data processing module and a signal transmission module. Preferably, the method comprises the following steps: sending the routing inspection route instruction to a control module of the mobile equipment; navigating the mobile equipment according to the routing inspection instruction based on the GPS navigation module; acquiring a surface temperature signal of the detection equipment through an infrared acquisition module, and generating an infrared thermal imaging image; and acquiring an ultrasonic signal of the detection equipment through the sound wave acquisition module, and generating a sound wave image.
The data perception layer mainly comprises a set of information acquisition equipment, an unmanned aerial vehicle is taken as a mobile equipment carrier for example, an infrared imager and an acoustic signal acquisition array are installed, and surface temperature signals and ultrasonic signals of the equipment are acquired and images are generated.
The processing unit 802 is configured to send the infrared thermal imaging image, the acoustic image and the detection device operating condition data to the cloud platform for storage; compounding a positioning sound source signal in the sound wave image to an infrared thermal imaging image to generate a composite thermal image; extracting the acoustic fingerprint based on the acoustic image. Preferably, the processing unit 802 is further configured to: positioning the fault through the sound wave image to obtain a positioning sound source signal, wherein the positioning sound source method comprises the following steps: time difference of arrival methods, steerable beamforming methods, and high resolution spectrum estimation methods.
Preferably, wherein the localized sound source signal is acquired using a high resolution spectral estimation method, comprising: establishing a sound source signal matrix of the ultrasonic signal, and performing phase compensation on the sound source signal matrix; calculating the compensated sound source signal matrix to obtain a covariance matrix of the sound source signal; decomposing the covariance matrix to obtain a signal subspace and a noise subspace; establishing a spatial search function based on the signal subspace and the noise subspace; carrying out space search on the space search function to obtain a function spectrum peak direction, and determining a direction of arrival angle of a sound source signal in the ultrasonic signal according to the function spectrum peak direction; and determining a positioning sound source signal according to the direction of arrival angle of the sound source signal.
The network communication layer is used as an intermediate connection part and is connected with the data sensing layer and the platform application layer, and the 4G wireless communication technology is mainly utilized to transmit the acquired data in the unmanned aerial vehicle to the platform. The platform layer provides cloud service, all collected data are integrated mainly by using a server cluster, and the problems of data and image storage, retrieval, calling, classification, safety protection and the like are solved through a database management technology.
And the judging unit 803 is used for judging the fault severity of the detection equipment based on the operation condition data of the detection equipment and the composite thermal image, and judging the fault type of the detection equipment according to the acoustic fingerprint.
The application layer is used as a system management layer, analyzes various information through interaction with the platform layer, judges the current equipment running state, makes an alarm decision according to a set threshold, predicts by combining historical data, makes an early warning decision according to the set threshold, is provided with a fault type analysis module, judges the fault type by using an RBF neural network according to the extracted sound wave fingerprint, can control the unmanned aerial vehicle of the sensing layer, and sets the routing inspection times and routing inspection routes of the unmanned aerial vehicle.
The invention realizes situation perception, state early warning, fault analysis and trend prediction of the electrical equipment by the mutual cooperation of four layers of networks and the interaction of actual detection data and the system.
The invention has been described with reference to a few embodiments. However, other embodiments of the invention than the one disclosed above are equally possible within the scope of the invention, as would be apparent to a person skilled in the art from the appended patent claims.
Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a// the [ device, component, etc ]" are to be interpreted openly as at least one instance of a device, component, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.
Claims (10)
1. A method for integrated inspection of electrical equipment, the method comprising:
acquiring a surface temperature signal and an ultrasonic signal of detection equipment and operation condition data of the detection equipment, and respectively generating an infrared thermal imaging image and a sound wave image based on the surface temperature signal and the ultrasonic signal;
sending the infrared thermal imaging image, the sound wave image and the detection equipment operation condition data to a cloud platform for storage; compounding the positioning sound source signals in the sound wave image to the infrared thermal imaging image to generate a composite thermal image; extracting a sonic fingerprint based on the sonic image;
and judging the fault severity of the detection equipment based on the operation condition data of the detection equipment and the composite thermal image, and judging the fault type of the detection equipment according to the acoustic fingerprint.
2. The method of claim 1, further comprising: the mobile equipment is provided with a power supply module, a GPS navigation module, a control module, an infrared acquisition module, a sound wave acquisition module, a data processing module and a signal transmission module.
3. The method of claim 2, comprising:
sending a routing inspection route instruction to a control module of the mobile equipment;
navigating the mobile equipment according to the routing inspection instruction based on a GPS navigation module;
acquiring a surface temperature signal of the detection equipment through the infrared acquisition module, and generating the infrared thermal imaging image;
and acquiring an ultrasonic signal of the detection equipment through the sound wave acquisition module, and generating the sound wave image.
4. The method of claim 1, locating a fault with the sonic image, obtaining a localized sound source signal, wherein the localized sound source method comprises: time difference of arrival methods, steerable beamforming methods, and high resolution spectrum estimation methods.
5. The method of claim 4, wherein acquiring a localized sound source signal using the high resolution spectral estimation method comprises:
establishing a sound source signal matrix of an ultrasonic signal, and performing phase compensation on the sound source signal matrix;
calculating the compensated sound source signal matrix to obtain a covariance matrix of the sound source signal;
decomposing the covariance matrix to obtain a signal subspace and a noise subspace;
establishing a spatial search function based on the signal subspace and the noise subspace;
carrying out space search on the space search function to obtain a function spectrum peak direction, and determining a direction of arrival angle of a sound source signal in the ultrasonic signal according to the function spectrum peak direction;
and determining a positioning sound source signal according to the direction of arrival angle of the sound source signal.
6. A system for comprehensive inspection of electrical equipment, the system comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a surface temperature signal of detection equipment, an ultrasonic signal and operation condition data of the detection equipment, and respectively generating an infrared thermal imaging image and a sound wave image based on the surface temperature signal and the ultrasonic signal;
the processing unit is used for sending the infrared thermal imaging image, the sound wave image and the detection equipment operation condition data to a cloud platform for storage; compounding the positioning sound source signals in the sound wave image to the infrared thermal imaging image to generate a composite thermal image; extracting a sonic fingerprint based on the sonic image;
and the judging unit is used for judging the fault severity of the detection equipment based on the operation condition data of the detection equipment and the composite thermal image and judging the fault type of the detection equipment according to the acoustic fingerprint.
7. The system of claim 6, the acquisition unit further to: the mobile equipment is provided with a power supply module, a GPS navigation module, a control module, an infrared acquisition module, a sound wave acquisition module, a data processing module and a signal transmission module.
8. The system of claim 7, comprising:
sending a routing inspection route instruction to a control module of the mobile equipment;
navigating the mobile equipment according to the routing inspection instruction based on a GPS navigation module;
acquiring a surface temperature signal of the detection equipment through the infrared acquisition module, and generating the infrared thermal imaging image;
and acquiring an ultrasonic signal of the detection equipment through the sound wave acquisition module, and generating the sound wave image.
9. The system of claim 6, the processing unit to further: and positioning the fault through the sound wave image to obtain a positioning sound source signal, wherein the positioning sound source method comprises the following steps: time difference of arrival methods, steerable beamforming methods, and high resolution spectrum estimation methods.
10. The system of claim 9, wherein acquiring a localized sound source signal using the high resolution spectral estimation method comprises:
establishing a sound source signal matrix of an ultrasonic signal, and performing phase compensation on the sound source signal matrix;
calculating the compensated sound source signal matrix to obtain a covariance matrix of the sound source signal;
decomposing the covariance matrix to obtain a signal subspace and a noise subspace;
establishing a spatial search function based on the signal subspace and the noise subspace;
carrying out space search on the space search function to obtain a function spectrum peak direction, and determining a direction of arrival angle of a sound source signal in the ultrasonic signal according to the function spectrum peak direction;
and determining a positioning sound source signal according to the direction of arrival angle of the sound source signal.
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Application publication date: 20210430 |