86 results about "High frequency transducer" patented technology

The invention relates to the technical field of power equipment state monitoring, and particularly discloses a power cable operation state real-time evaluation system based on multi-mode deep learning, and the system comprises the steps: synchronously collecting the load, partial discharge and temperature strain data of a cable through a current and voltage sensor, an ultrahigh frequency sensor and a distributed optical fiber sensor; feature extraction and cross-dimension fusion are carried out on the multi-source data, and a multi-dimensional feature matrix is constructed; a pre-trained deep learning model is utilized to analyze internal association between the features, and cable health degree scores, fault risk levels and defect type identification results are output; automatically generating and executing a load adjustment, loop switching or precise maintenance strategy according to an evaluation result; according to the method, the problems of inaccurate evaluation and early warning lag caused by data isolation analysis of a traditional monitoring method are solved, and real-time accurate evaluation and intelligent closed-loop operation and maintenance of the operation state of the cable are realized.

The invention provides a partial discharge on-line monitoring method and system based on multi-modal fusion and adaptive noise reduction, and the method comprises the steps: employing an ultrahigh frequency UHF sensor, a miniature ultrasonic sensor, and a miniature detector for gas dissolved in oil, which are disposed on a transformer; synchronously acquiring electric signals, sound signals and characteristic gas concentration data in oil generated in the partial discharge process; performing format unification, abnormal value elimination and time alignment processing on the electric signal, the sound signal and the gas concentration data in an edge calculation unit to obtain aligned multi-source original data; performing adaptive wavelet noise reduction processing on the electric signal to obtain a de-noised UHF signal; respectively extracting time domain, frequency domain and chemical features from the de-noised UHF signal, the aligned sound signal and the gas concentration data to form a multi-dimensional feature vector; and inputting the multi-dimensional feature vector into a pre-trained defect traceability model, and outputting a partial discharge defect type, severity level and development trend prediction result.

The invention discloses a live detection method for insulation defects of high-voltage power equipment. The method comprises the following steps: firstly, synchronously arranging ultrahigh frequency sensors and acoustic emission sensors on a plurality of monitoring points on the surface of a gas insulated switchgear shell to form an array, and synchronously acquiring signals for filtering pretreatment; then, pulse events are extracted from the two types of signals respectively, and associated pulses in a time window are matched into matched pulse pairs representing the same discharge source; then, carrying out time-frequency transformation on the ultrahigh frequency and acoustic emission pulse waveform in each matched pulse pair, carrying out joint noise reduction by calculating a coherence coefficient between time-frequency distribution matrixes, and extracting a joint feature vector containing an energy ratio, a time parameter ratio and a frequency difference from the denoised time-frequency matrix; according to the invention, multi-source signals are fused, and high-sensitivity detection, high-precision positioning and high-accuracy identification of insulation defects are realized.

The invention discloses a multi-mode signal fusion switch cabinet partial discharge detection and positioning method and device, and belongs to the technical field of power equipment monitoring, and the method comprises the steps: arranging an ultrahigh frequency sensor, an ultrasonic sensor and a traveling wave signal sensor on a switch cabinet, and synchronously collecting electromagnetic wave, sound wave and traveling wave signals; filtering the electromagnetic wave signal, the sound wave signal and the traveling wave signal, and enhancing the filtered signal to obtain a filtered enhanced signal; carrying out the positioning and classification of the partial discharge signals through the multi-modal feature fusion of the filtered enhanced signals; and triggering graded alarm according to a positioning result, and periodically starting a self-checking program to verify the reliability of the sensor and the algorithm. Physical characteristics of different discharge types are covered, the detection comprehensiveness is improved, the noise interference problem is solved, and the data fusion efficiency and the positioning precision are improved; the system health state is monitored in real time, and long-term operation stability is ensured.

The invention discloses a GIS ultrahigh frequency sensor ultrasonic cooperative detection system based on piezoelectric energization, and relates to the field of electric power detection, and the system comprises an excitation module which is used for transmitting a piezoelectric excitation signal with a specific frequency to a preset detection region in GIS equipment, so as to trigger the potential partial discharge acoustoelectric signal radiation of the region; the sensing module is used for receiving ultrahigh-frequency electromagnetic signals and ultrasonic vibration signals radiated by partial discharge in the GIS equipment; the excitation frequency, the filtering bandwidth and the sampling rate are dynamically optimized according to the detection result, the detection accuracy and efficiency are continuously improved, and reliable and effective guarantee is provided for safe operation and defect early warning of GIS equipment.

The invention provides a multi-mode fusion switch cabinet partial discharge on-line monitoring system and method, and the system comprises a space setting module which employs a preset space analysis algorithm, obtains an installation point position set according to the space structure of a switch cabinet, and carries out the installation of the installation point position set; the data acquisition module is used for acquiring data acquired by the ultrahigh frequency sensor, the ultrasonic sensor and the temperature sensor, preprocessing the data and then sending the data to the signal processing module; carrying out power frequency noise suppression on the ultrahigh frequency signal and the ultrasonic signal through a self-adaptive filter circuit, and extracting partial discharge characteristics from the filtered signal by adopting a wavelet transform algorithm; and the AI model fusing the convolutional neural network and the long-short-term memory network performs fusion analysis on the partial discharge characteristics and the temperature sensor data, realizes partial discharge mode identification and insulation degradation trend prediction, and outputs early warning information. According to the technical scheme provided by the invention, high-precision and anti-interference discharge detection can be realized.

The invention relates to the technical field of mechanical arm vibration suppression, in particular to a mechanical arm tail end active vibration suppression method and system based on predictive compensation, and the method comprises the following steps: S1, collecting the three-axis acceleration, angular velocity and vibration spectrum data of a mechanical arm in real time through a high-frequency IMU sensor; monitoring a rolling angle, a pitch angle and a yaw angle of a base attitude through an auxiliary IMU sensor, and fusing double IMU data through a Kalman filtering algorithm; s2, generating a pre-compensation torque based on the fused data, optimizing a model gain coefficient in combination with a real-time deviation between a frequency spectrum actually measured by a high-frequency IMU sensor and a model prediction frequency spectrum, and correcting and outputting the pre-compensation torque in real time; and S3, the corrected compensation torque is injected into a feed-forward channel of a joint motor control loop, vibration suppression torque is output to a joint execution mechanism through a high-gain controller, and residual vibration at the tail end of the mechanical arm is counteracted in real time. According to the invention, an active vibration suppression system can be constructed to solve the problem of real-time vibration suppression under multi-source disturbance coupling.

The invention relates to the technical field of partial discharge detection and sensor verification, and particularly discloses an ultrahigh frequency sensor relative amplitude online verification method for transformer bushing defects. The method comprises the following steps: firstly, spraying conductive paint into a lower porcelain bushing of the transformer bushing to form a creeping discharge channel, and constructing a transformer bushing operation simulation device; then, a standard calibration pulse generator is utilized to inject a discharge signal equivalent to a 10pC electric charge quantity at the defect position of the sleeve; then, the ultrahigh frequency sensor to be tested receives a partial discharge signal, and a relative amplitude model is established based on sensor frequency response, dielectric constant, signal propagation attenuation and installation conditions; and finally, comparing the actually measured signal amplitude with the calculated relative amplitude threshold, and if the amplitude is lower than the threshold, judging that the performance of the sensor is degraded. According to the method, the installation condition correction model is introduced, online evaluation of the sensitivity of the ultrahigh-frequency sensor under the condition that equipment is not disassembled is achieved, the real performance of the sensor in a complex field environment can be accurately reflected, and the reliability and maintenance efficiency of a transformer bushing partial discharge monitoring system are remarkably improved.

The invention provides a transformer internal partial discharge detection method, device and equipment and a storage medium, and belongs to the field of transformer monitoring, and the method comprises the steps: obtaining an ultrahigh frequency electric signal, an optical signal and an acoustic signal generated by transformer internal partial discharge through an ultrahigh frequency sensor, an optical sensor and an optical fiber Fabry-Perot ultrasonic sensor; a multi-state quantity integrated sensing SoC chip on the circuit board is used for conditioning and digitizing the signals to generate a digitized signal flow; inputting the signal flow into a state sensing special edge computing NPU chip, processing the signal flow by using a graph attention network algorithm, calculating an attention coefficient between sensor nodes, and fusing the multi-modal signals to generate a fusion signal; and determining the partial discharge type according to the fusion signal. According to the invention, three sensors are internally integrated, signal conditioning digitalization is carried out by using the SoC chip, multi-mode signals are fused through the NPU chip, high-precision and high-reliability identification is realized, and the difficulty of an external sensor is overcome.

The invention relates to the technical field of GIS basin-type insulator performance evaluation, and discloses a GIS basin-type insulator performance evaluation method and system, and the method comprises the steps: synchronously collecting multi-physical field monitoring data through an ultrahigh frequency UHF sensor, an ultrasonic sensor array, an SF6 gas decomposition product detection unit and a thermal infrared imager; performing preprocessing and feature extraction on the monitoring data to obtain a multi-dimensional feature parameter set; performing weighted fusion calculation on the feature parameter set based on a fusion model of combined weighting of an analytic hierarchy process (AHP) and an entropy weight method, and outputting a health state evaluation index; comparing the evaluation index with a preset threshold interval to determine a performance grade and sending out an early warning; and automatically generating an evaluation report containing historical trends and maintenance suggestions. According to the GIS basin-type insulator performance evaluation method and system, multi-source information fusion and intelligent evaluation are achieved, the accuracy and reliability of state evaluation are remarkably improved, and technical guarantee is provided for safe operation of a power grid.

The invention relates to a high-precision sensing device capable of being used for GIS accidental partial discharge positioning and type diagnosis. The high-precision sensing device comprises an ultrahigh frequency sensor and a data acquisition system. The ultrahigh frequency sensor is responsible for capturing weak accidental partial discharge signals generated in the GIS equipment; the captured original signal is then sent to a filtering and amplifying module and a synchronization module for hardware preprocessing, and is digitalized through a high-speed sampling assembly; the digitized mass data are transmitted to the high-performance GPU parallel computing unit, and the data are efficiently analyzed by utilizing the strong parallel processing capability of the high-performance GPU parallel computing unit. According to the invention, the equipment sampling rate is improved to a high sampling rate of 5GHz, so that the partial discharge pulse sampling interval of the GIS partial discharge monitoring equipment reaches 0.2 ns, and the sampling points and the data volume are greatly increased; gPU parallel computing is combined and utilized to greatly improve the pulse processing capacity, so that the system can effectively find and capture intermittent and accidental partial discharge signals, and the detection rate of the intermittent and accidental signals is remarkably improved.

The invention provides a self-adaptive denoising method based on Meyer wavelets and an improved smooth threshold function in order to solve the problem that a transformer partial discharge high-frequency current sensor field calibration signal is seriously polluted by field electromagnetic noise interference. The method comprises the following steps: firstly, arranging a standard sensor according to an optimal cross-core distance to obtain an original noisy signal; then adaptively determining a decomposition series according to a data length, selecting Meyer wavelets to perform multi-scale decomposition, performing smooth contraction on wavelet coefficients by adopting a continuously derivable, progressive and unbiased improved threshold function, and finally reconstructing a high signal-to-noise ratio verification signal through wavelet inverse transformation; the method does not need manual intervention of the threshold value, keeps orthogonality and high-order derivability in the whole process, and is beneficial to improving the accuracy of the verification result of the high-frequency sensor to be tested.

The utility model belongs to the field of GIS partial discharge detection, and particularly relates to an optical fiber ultrasonic-ultrahigh frequency composite sensor for GIS partial discharge detection, which comprises a cover plate, an ultrasonic sensor and an ultrahigh frequency sensor, the ultrasonic sensor comprises an induction optical fiber, an input connector and an output connector, the cover plate is provided with an annular groove, the induction optical fiber is fixed in the annular groove, and the output connector is fixed in the annular groove. Two ends of the sensing optical fiber are respectively connected with the input connector and the output connector, the input connector is used for inputting an external optical signal into the sensing optical fiber, and the output connector is used for outputting the optical signal in the sensing optical fiber to external detection equipment; the ultrahigh frequency sensor comprises an inductive probe, a pressing ring, a base and an N-type connector, the base is fixed on the cover plate, the pressing ring and the inductive probe are installed on the base, the inductive probe is mushroom-shaped and comprises a head part and a connecting part, and the connecting part sequentially penetrates through the pressing ring, the base and the cover plate and is electrically connected with the N-type connector; the problems that an existing composite sensor is low in measurement precision and sensitivity and poor in anti-interference capacity are solved.

This invention provides a partial discharge detection method based on the insertion depth constraint of an ultra-high frequency (UHF) sensor. The method includes: obtaining the physical parameters of an external UHF sensor; detecting the return loss curve of the external UHF sensor in a laboratory environment using a GTEM chamber; calculating the minimum insertion depth of the external UHF sensor at the joint based on the physical parameters of the transformer equipment; calculating the maximum allowable insertion depth of the external UHF sensor based on the internal structural dimensions and insulation safety requirements of the transformer; determining the effective insertion depth range of the external UHF sensor; and measuring the partial discharge signal of the transformer. This invention utilizes a formula to calculate the reasonable insertion depth range of the external UHF sensor at the transformer tank joint, thereby solving the problems of installation depth dependence on experience and poor detection consistency in existing technologies.

A transformer partial discharge positioning detection method based on ultrahigh frequency signals is characterized by comprising the following steps: S1, estimating time delay of signals obtained by an ultrahigh frequency (UHF) sensor array based on a generalized cross-correlation method; and S2, arranging and combining signals of the UHF sensor array, and solving coordinates of a positioning point based on an improved multi-moth optimization (MFO) algorithm according to the time delay obtained in the step S1. And S3, clustering the coordinates of the plurality of positioning points obtained in the step S2 based on a density clustering algorithm (DBSCAN), and selecting the geometric center position of the category with the maximum sample number as the final local discharge source coordinate.

The application discloses a GIS partial discharge positioning method and device, electronic equipment and a storage medium, and is used for solving the technical problems that the existing GIS partial discharge positioning method depends on manual real-time measurement, the labor cost is high, historical data cannot be positioned, and missed detection is easy. The application comprises the following steps: collecting pulse signals on a GIS channel according to a preset sampling length; calculating a first pulse arrival time of the pulse signals reaching a preset first ultrahigh frequency sensor; calculating a second pulse arrival time of the pulse signals reaching a preset second ultrahigh frequency sensor; calculating a time difference between the first pulse arrival time and the second pulse arrival time; and positioning a partial discharge point on the GIS according to the time difference.

The invention discloses a basin-type insulator with a partial discharge detection function for a GIS (Gas Insulated Switchgear), and relates to the technical field of equipment detection, the basin-type insulator comprises a basin-type insulator and a metal flange which are coaxially arranged, and the metal flange is fixed on the outer edge of the basin-type insulator; the outer edge of the basin-type insulator is provided with a grounding electrode assembly. The ultrahigh-frequency self-sensor is fixed on the outer side of the edge of the metal flange and penetrates through the metal flange to be connected with the grounding terminal. The ultrahigh frequency sensor is integrally fused in the basin-type insulator, so that the problems that existing built-in sensors are few in distribution points and small and micro defects are difficult to find are solved on the basis that the original performance of the GIS is not affected.

The application discloses a kind of partial discharge identification method and system of extra-high voltage GIS disconnecting switch gas chamber, comprising: three outside extra-high frequency sensors are arranged in the gas chamber of extra-high voltage GIS disconnecting switch, wherein, first sensor is placed on the upper end of the lower part of the gas chamber basin type insulator, second sensor is placed on the lower end of the upper part of the gas chamber basin type insulator, third sensor is placed on the lower end of the lower part of the gas chamber basin type insulator;When the partial discharge time difference received by sensor and second sensor is within the first preset threshold range, and the partial discharge time difference received by first sensor and sensor is greater than the second preset threshold, and the partial discharge signal in the gas chamber of the extra-high voltage GIS disconnecting switch meets the discharge characteristics of solid insulation, it is determined that there is partial discharge between the switching resistance insulation support rod or the outer sheath and the grading ring of the gas chamber of extra-high voltage GIS disconnecting switch.The demand problem of the current partial discharge judgment method of extra-high voltage GIS disconnecting switch gas chamber is solved.

The invention relates to the field of power equipment monitoring, and discloses an oiled paper insulation capacitive bushing full fault detection early warning system, which comprises a multi-parameter sensor module, a data acquisition and transmission module, a data processing and analysis module and an early warning and decision module, the multi-parameter sensor module comprises an ultrahigh frequency (UHF) sensor which is installed near a sleeve flange plate and is used for monitoring a partial discharge signal in a frequency range of 300MHz-3GHz in the sleeve in real time; a plurality of high-precision optical fiber temperature sensors are arranged on a bushing capacitor core, an insulating oil layer and the surface of a bushing, and various types of sensors such as a partial discharge sensor, a temperature sensor, a pressure sensor, a humidity sensor and the like are integrated; according to the invention, parameter changes of electrical, thermal, mechanical, humidity and the like of the oil-paper insulation capacitive bushing in the operation process can be comprehensively monitored, so that comprehensive detection of various faults is realized, and the limitation of a single detection method is effectively avoided.

The invention discloses an insulation degradation positioning device of a cable terminal and a control method, and relates to the technical field of cable terminal insulation detection and fault positioning. A signal sensing unit adopts a single built-in ultrahigh-frequency sensor to capture a high-frequency harmonic signal generated at the initial stage of insulation aging of the cable terminal to be detected; the signal acquisition and processing unit pre-processes the signal, then the pre-processed signal is injected into a preset cable terminal digital twin electromagnetic model by means of the digital twin and inversion analysis and calculation unit to carry out electromagnetic wave back propagation simulation, and total-space electromagnetic field distribution data is obtained based on simulation. The space coordinate of the insulation degradation point is determined through the preset positioning criterion, the positioning precision equivalent to that of a traditional multi-sensor system is achieved through a single-sensor scheme, the cost and the deployment difficulty are remarkably reduced, deep integration with a digital twin platform is achieved, and efficient and accurate technical support is provided for intelligent operation and maintenance of the cable terminal.

The utility model provides a state detection device for a power distribution cabinet, and belongs to the technical field of electrical engineering. According to the structure, a high-frequency current transformer, an ultrasonic sensor, an ultrahigh-frequency sensor and a signal amplifier are arranged on a main PCB, the ultrasonic sensor is electrically connected with the high-frequency current transformer and the ultrahigh-frequency sensor in sequence, the ultrahigh-frequency sensor is electrically connected with the signal amplifier, a main inserting rod and a main mounting plate are arranged on the main PCB, and the signal amplifier is electrically connected with the main inserting rod. The main insertion rod is in insertion connection with the machine body, the main installation plate is fixedly connected with the machine body, the data exchange module comprises an auxiliary PCB, the auxiliary PCB is provided with a wifi module, a controller, a data line interface and a memory card slot, and the wifi module, the data line interface and the memory card slot are electrically connected with the controller. The power distribution cabinet partial discharge signal acquisition device has stronger acquisition capability for partial discharge signals of a power distribution cabinet, can be interconnected and intercommunicated with a remote control end in real time, and is compact in structure and stable and reliable in operation.

1. The name of the design product: external ultrahigh frequency sensor. 2. The use of the design product: the design is suitable for partial discharge detection of high-voltage electrical equipment, receiving ultrahigh frequency electromagnetic wave signals generated by partial discharge in a non-contact manner, and installing on the equipment basin insulator or grounding port to realize detection and positioning of insulation defects. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The invention provides a GIS ultrahigh frequency online monitoring device and method based on signal multiplexing, and relates to the technical field of power grids. The online monitoring device is designed, the ultrahigh-frequency sensors are arranged on the inner walls of the GIS air chambers, the non-contact directional couplers are arranged on the outer walls of the GIS air chambers, ultrahigh-frequency signal transmission is achieved through coupling of the non-contact directional couplers and the ultrahigh-frequency sensors, and partial discharge detection can be achieved without perforating the GIS air chambers. The local detection box is arranged on the ground of the area where each GIS air chamber is located, and the multi-channel intelligent switching matrix in the local detection box is connected with the non-contact directional coupler of each GIS air chamber, so that polling switching detection of partial discharge in each GIS air chamber is realized, and operation and maintenance personnel do not need to climb to work; the problem of low GIS partial discharge detection efficiency caused by single-channel serial operation, high-altitude operation dependence and the like in the GIS partial discharge detection technology is solved, and the detection efficiency of GIS partial discharge detection is improved.

This invention discloses a device and method for extracting ultra-high frequency (UHF) sensor signals, relating to the field of UHF detection technology. It includes: a sensor connection module for connecting to the output terminal of an UHF sensor to extract the sensor's detection signal; a housing containing the detection module, which provides a detection interface for the extracted UHF sensor detection signal; and a transmission wire, one end of which is connected to the sensor connection module, and the other end of which is connected to the housing. This invention facilitates measurement by operators, eliminating the need for climbing or using ladders, thus reducing measurement time and improving efficiency.

According to a first aspect of the invention, a loudspeaker drive unit (1000) is proposed, comprising a frame (400) comprising an outer frame portion (401) and an inner frame portion (402), the inner frame portion (402) defining an opening (404). The loudspeaker drive unit (1000) further comprises a low frequency transducer (100). The low frequency transducer (100) has a diaphragm (110) suspended between an outer frame portion (401) and an inner frame portion (402) to form part of a waveguide. The loudspeaker drive unit (1000) further comprises a compression transducer as a high-frequency transducer (200), which is connected to the inner frame portion (402).

The invention relates to the technical field of energy efficiency data acquisition and analysis oriented to factory management, in particular to an intelligent factory standardized production line energy efficiency data acquisition and analysis method and system, and the method comprises the following steps: a multi-source data perception interaction module captures a component pose and thermal parameters to construct a data set; the thermal energy efficiency dynamic analysis module calculates thermal demand and energy supply deviation based on a process stage; the logistics transmission power consumption evaluation module constructs a damping loss model and distinguishes effective work and abnormal loss, and the global energy efficiency optimization decision-making module executes an adaptive weighted fusion algorithm, solves an optimal working point and generates a closed-loop feedback energy-saving regulation and control strategy. The energy flow relation of production nodes is analyzed in real time through a high-frequency sensor and a dynamic thermodynamic model, hidden energy waste points are accurately positioned, process-level standardized energy efficiency indexes are formed, and energy consumption optimization, abnormity tracing and production line energy utilization rate improvement are achieved.

The application discloses a partial discharge detection method and device and a nonvolatile storage medium. The method comprises the following steps: based on a plurality of preset sensors, absolute field strength data and electromagnetic wave space-time data inside a cavity of a target device are acquired at a plurality of preset positions inside the cavity of the target device, wherein the plurality of sensors comprise a plurality of Rydberg sensors and a plurality of ultrahigh frequency sensors; the absolute field strength data and the electromagnetic wave space-time data at the same time are integrated to obtain a plurality of joint data frames; and based on the joint data frames, a partial discharge detection result of the target device is determined, wherein the partial discharge detection result comprises a discharge type, a defect position and an insulation state. The application solves the technical problem that the traditional technology is difficult to realize high-precision, multi-parameter and traceable monitoring requirements in a complex electromagnetic environment.

The embodiment of the invention discloses a multi-band ultrahigh frequency detection device, a multi-band ultrahigh frequency detection method and a computer readable storage medium. The multi-band ultrahigh frequency detection device comprises an ultrahigh frequency sensor, a front-end processing module and an acquisition module. The ultrahigh frequency sensor is used for collecting an electric signal sent by a measured object. The front-end processing module comprises a band-pass filter circuit and a detection filter circuit, and the band-pass filter circuit is used for separating the electric signal into multiple sub-band signals of different wavebands; the detection filter circuit is used for collecting effective content in each sub-band signal to obtain a detection signal. And the acquisition module is used for converting the multiple paths of detection signals into ultrahigh-frequency acquisition information and uploading the ultrahigh-frequency acquisition information, and the ultrahigh-frequency acquisition information is used for representing the working condition state of the detected object. Therefore, the ultrahigh frequency acquisition information under different frequency bands can be effectively acquired, and synchronous acquisition of the ultrahigh frequency acquisition information of multiple independent frequency bands can be realized.

The invention belongs to the field of transformer equipment, and discloses a test monitoring system and method for an ultra-high voltage wire outlet device, and the system is characterized in that various sensor units are arranged on key parts of the ultra-high voltage wire outlet device, namely a high-voltage ascending flanged base, a housing and a test device; comprising ultrahigh-frequency, optical, ultrasonic and high-frequency sensors and an oil chromatography and single hydrogen monitoring device, and synchronous monitoring of discharge signals and changes of chemical components in oil is achieved. By utilizing the complementary characteristics of different sensors, abnormal information generated by insulation defects is captured from multiple dimensions of electromagnetism, acoustics, optics, chemistry and the like, and through multi-source data fusion analysis, the insulation performance of the wire outlet device in an independent test state can be comprehensively diagnosed. According to the system, the problem that the insulation reliability cannot be accurately evaluated due to the lack of effective monitoring means in the traditional method is effectively solved, and the coverage range and the fault detection precision of the test are remarkably improved, so that the risks of manufacturing and quality control of the ultra-high voltage equipment are reduced, and the operation safety of the equipment is ensured.

The embodiment of the invention provides a live inspection robot for a combined electric appliance. The method is applied to the technical field of intelligent inspection of power grid equipment, and comprises the steps that a path planning system identifies obstacles and topographic features in a combined electric appliance environment in real time by using an airborne sensor array, dynamically adjusts a path, and plans a path to a specified inspection point according to preset content. After the inspection robot arrives at an inspection point, the target recognition system recognizes specific components needing to be detected by analyzing visual features and structural information of the combined electric appliance. After specific components are identified, the mechanical arm cooperative operation system is matched with sensing signal sampling, and the mechanical arm places an ultrahigh frequency sensor and an ultrasonic sensor at key parts of a combined electric appliance for physical contact detection; meanwhile, the mechanical arm processes data collected by the ultrahigh frequency sensor and the ultrasonic sensor and transmits the data back to a data processing center of the robot in real time. And a technical support is provided for the robot to realize automatic and intelligent live inspection.