Wan Wanglong

Bio: Wan Wanglong is an academic researcher. The author has contributed to research in topics: Partial discharge & Electromagnetic interference. The author has an hindex of 1, co-authored 2 publications receiving 9 citations.

GIS risk evaluation method and GIS risk evaluation system based on partial discharge live detection

Abstract: The invention discloses a GIS risk evaluation method and a GIS risk evaluation system based on partial discharge live detection. According to the method of the invention, a partial discharge signal is acquired through an ultrahigh-frequency antenna and an ultrasonic wave sensor, and through analyzing partial discharge type and analyzing partial discharge severity , the type and severity of a certain partial discharge are obtained; furthermore accurate positioning on a partial discharge source is realized according to two ultrahigh-frequency signals or two ultrasonic wave signals; and risk grade can be accurately evaluated comprehensively according to operation information and maintenance information of the GIS. The GIS risk evaluation method prevents a defect in evaluation according to single kind of data such as partial discharge amplitude or partial discharge frequency. Furthermore the GIS risk evaluation method and the GIS risk evaluation system have advantages of high partial discharge detection sensitivity and high risk evaluation accuracy. The GIS risk evaluation system realizes simple structure and convenient operation and supplies technical guidance for improving partial discharge live detection risk evaluation accuracy, thereby realizing advantages of high detection sensitivity and high evaluation accuracy.

Method for grading transformer station partial discharge live detection electromagnetic interference signals

Abstract: The invention discloses a method for grading transformer station partial discharge live detection electromagnetic interference signals. The method performs classified statistic on various kinds of electromagnetic interference signals in various detection methods, uses the interference signal intensity and discrete degree thereof as the basis of interference grading, objectively and accurately grades the interference grades of the electromagnetic interference signals, quantitatively describes the electromagnetic interference signals, and provides a reference basis for a standardized interference test platform and establishment of a partial discharge detection device anti-interference performance evaluation system.

Switch cabinet big data state evaluation method and system based on intelligent partial discharge live-line detection

Abstract: The invention provides a switch cabinet big data state evaluation system based on intelligent partial discharge live-line detection. The system comprises an intelligent inspection unit, a partial discharge diagnosis and positioning unit, an equipment state evaluation unit, an intelligent terminal and a control unit, wherein the equipment state evaluation unit comprises a communication unit, a signal storage unit, a characteristic signal extraction unit, a defect type identification unit and an equipment defect severity analysis unit. The system is advantaged in that the system has properties of high intelligentization level, good partial discharge detection sensitivity and high risk evaluation accuracy, and powerful technical support is provided for developing power-on maintenance of the switch cabinet.

GIS (Gas Insulated Switchgear) internal partial discharge defect recognition method based on PRPS signals

Abstract: The invention discloses a GIS (Gas Insulated Switchgear) internal partial discharge defect recognition method based on PRPS signals. The GIS internal partial discharge defect recognition method comprises the steps: obtaining a lot of partial discharge signals PRPS through a GIS built-in sensor; extracting a plurality of characteristics of a discharge capacity mean value, a discharge duality rate,initial discharge phase window difference, a discharge width ratio, a discharge phase mean value, discharge phase standard deviation, discharge phase skewness and the like; utilizing extreme gradientto improve a classification tress to achieve establishment of a PRPS defect type recognition model. According to the method disclosed by the invention, machine learning is utilized to perform discharge defect recognition on PRPS atlases obtained through an ultrahigh frequency method, a traditional time-consuming complex process that a GIS partial discharge defect recognition system is achieved byconverting PRPS to PRPD is avoided, effects caused by period inconformity can be well eliminated, a defect type recognition accuracy rate can be remarkably improved, and defect types can be judged according to calculation results.

Partial discharge diagnosis method and system of GIS device

Abstract: The embodiment of the invention discloses a partial discharge diagnosis method and system of a GIS device. The method and system perform similarity analysis on the monitoring data of UHF sensors at equal intervals to determine whether the monitoring data originate from the same signal source, avoids misjudging the partial discharge severity and a fault type of respective UHF sensors due to the interference from multiple signal sources, determine whether a fault is the internal fault of the GIS device, avoids false alarms due to external faults; accurately determine a partial discharge positionaccording to UHF signal amplitudes in the monitoring data, equipment structure information, and operating data at the same detection intervals, analyze the discharge severity in combination with thedischarge amplitude change trend, positioning information, operating data and discharge types so as to make the analysis result more accurate, timely and effectively give early warning, provide important reference for workers, and solve a technical problem that a traditional partial discharge monitoring system cannot diagnose the partial discharge faults of the GIS device or timely give warning because of incomprehensive reference factors.

Method and apparatus for optimum channel combination for NFC transceivers

Abstract: Various embodiments relate to a method and circuit for combining channels, the method including receiving, by a matching and smoothing filter, a signal from an analog to digital converter and extracting a root mean square signal level, receiving, by a noise power detector (“NPD”), the signal from the ADC and assessing noise contribution on the signal and receiving, by a maximum ratio combiner, the signal from the matching and smoothing filter wherein a combiner selects between using a geometric sum and an arithmetic sum to combine the channels.

Cable oscillating wave local discharge fault positioning system

Abstract: The invention discloses a cable oscillating wave local discharge fault positioning system. The cable oscillating wave local discharge fault positioning system comprises a high-frequency current sensor; the high-frequency current sensor inputs a sensed local discharge signal to a presignal wave detector; the presignal wave detector judges the signal, and controls a subsequent variable gain amplifier to select direct connection or an amplification factor; then, the signal is amplified by the variable gain amplifier and then enters a high-speed AD collection card for AD conversion; and data are transmitted to an upper computer for analysis, processing and display. According to the cable oscillating wave local discharge fault positioning system, by increasing the presignal wave detector and the variable gain amplifier, an amplitude of a reflection signal is significantly improved, and an AD collection effect is improved; and meanwhile, correlation operation is adopted for sampled data andwaveform matching is performed on a waveform characteristic algorithm, so that a matching effect is improved to the utmost extent, an identification effect on the sensed signal in two times is greatlyimproved, and the fault positioning precision is effectively improved.