35results about "Form factor measurements" patented technology

The invention relates to a lightning stroke fault determination method based on a waveform difference degree and a lightning stroke fault sample database. According to the method, when a fault occurs at a power transmission line, a travelling-wave fault range finding apparatus records a fault waveform; calculation is carried out by using a cubic b-spline wavelet to obtain an initial traveling wave arrival time of the fault; data 5ms after the initial traveling wave arrival time are selected to carry out normalization processing; the fault waveform after normalization processing is compared with all waveforms in the lightning stroke fault sample database and waveform difference degrees are calculated; and if a minimum value of difference degrees of the fault waveform and all waveforms in the lightning stroke fault sample database is less than a set threshold value, the fault type is determined to be a lightning stroke fault type; and otherwise, the fault type is determined to a non-lightning stroke fault type. According to the invention, compared with the existing lightning stroke fault identification method, the provided determination method has the following beneficial effects: confirmation of fault points by field line patrol workers is not required; the accuracy is high; and the method is simple and effective.

The invention relates to a full lightning cloud cloud-to-ground lightning recognition method. The method can be used for recognizing different lightning types, includes intracloud discharging and cloud-to-ground discharging recognition and recognition of a special cloud lightning event (NBE) and can be used for conventional cloud-to-ground lightning and position cloud lightning. A specific waveform parameter extraction method is adopted to extract collected lightning field waveform parameters, the extracted lightning waveform parameters are utilized for comprehensive judgment, and lightning discharging types are given according to judgment results.

The invention belongs to the field of testing devices and discloses a periodic signal waveform testing device. The periodic signal waveform testing device is featured by comprising a signal input unit, a keyboard unit, a PLC unit, a signal collecting and processing unit, a programmable controller and a display unit. The programmable controller controls the PLC unit according to a received signal input channel message, and inputs a corresponding to-be-tested periodic signal wave into the signal collecting and processing unit through the PLC unit. The signal collecting and processing unit comprises a first functional circuit and a second functional circuit. The invention controls the testing process by the programmable controller. The overall testing process can be automatically conducted, the testing time is short, and the accuracy is high.

The invention relates to a method for determining a correlated waveform on a real time oscilloscope. A method for determining a correlated waveform, includes acquiring a generalized waveform record with a repeating pattern, determining a possibly corrected recovered clock signal for the generalized waveform record, selecting a new sample rate that is higher than the clock rate by N time, where N is an integer greater than 1, resampling the generalized waveform so that the new samples fall precisely on two clocks instants of the recovered clock signal that define each unit interval, and on N-1 additional instants equally spaced between the two clock instants of each unit interval to create a resampled waveform, and forming the correlated waveform by taking the mean values of all samples from the resampled waveform having the same offset into a pattern repeat in unit intervals or fractions thereof.

The present invention relates to a method for detecting oscillations of signals, including evaluating signals to be analyzed concerning to occurrence of maximum or minimum values, by considering determined number of values in an evaluation section of the signals. The maximum or minimum values are filtered by low pass transfer functions with time constants, and the maximum or minimum values are reprocessed by differentiation of amplitude value, where the amplitude value is evaluated for analyzing oscillations of the signals. Furthermore, the invention also relates to a diagnosing device for detecting oscillations of signals, having a first evaluating unit to select maximum or minimum values from the signal section, the maximum or minimum values is filtered by a low pass filter unit respectively, and the filtered values are input to a difference calculating unit as input paremeters. The amplitude value can be processed as an output parameter of the difference calculating unit and is filtered by a following low pass filter unit, and/or the amplitude value is compared with a prescribed value by another processing unit.

The invention discloses a DC bias calibration apparatus and method of a zero-intermediate-frequency waveform generation system, and relates to the technical field of signal processing. The device comprises a measurement module, a feedback module, a processing module and a compensation module. The measurement module is used for measuring waveform signals output by a zero intermediate frequency waveform generation system; the feedback module is connected with the measurement module and used for feeding back a measurement result to a data processing unit of the zero intermediate frequency waveform generation system; the processing module is connected with the feedback module, is deployed in a data processing unit of the zero intermediate frequency waveform generation system and is used for processing the measurement data so as to obtain a DC bias compensation amount; and the compensation module is connected with the feedback module, is deployed in a data processing unit of the zero intermediate frequency waveform generation system, and is used for calibrating an output waveform signal according to the DC bias compensation amount. According to the invention, the measurement of the amplitude is converted into the measurement of the time delay, and then the calibration of the DC bias is completed.

Embodiments of the present invention provide systems, devices and methods for efficiently calculating a true RMS values (either voltage or current) of an AC signal. The RMS value is generated from both high and low frequency components of the AC signal without a high speed ADC being integrated within the system. The high frequency component is processed by calculating an average current waveform of the high frequency component and approximating a corresponding RMS value using a waveform factor. The waveform factor is effectively a scalar that relates the average current waveform of the high frequency component to an appropriate RMS value.

The invention discloses an electric vehicle with a safe circuit structure. Compared with the prior art, by arranging a security module in a vehicle circuit, detection is conducted through the security module; when something dangerous happens, the security module sends a signal to an alarm module which gives an alarm, and a driver knows danger in time and disposes the dangerous situation in time.

The invention provides a distribution line early fault severity evaluation method based on waveform characteristics, and the method comprises the steps: monitoring an early fault of a kth distributionline, and obtaining an original voltage waveform of the distribution line; according to the original voltage waveform of the distribution line, respectively calculating to obtain a voltage determination coefficient and a voltage approximate entropy; calculating to obtain a comprehensive evaluation index of the early fault degree of the distribution line according to the voltage determination coefficient and the voltage approximate entropy; and determining the severity of the kth early fault according to the interval range to which the comprehensive evaluation index of the early fault degree of the distribution line belongs. Through the design, the function of predicting and early warning the distribution network line is realized, so that the overhaul and maintenance of the distribution line is guided, permanent faults are avoided, and the power supply reliability is improved.

The invention discloses an SF6 spark discharge energy analysis method. The method comprises the following steps: rectifying a high-voltage alternating-current power supply through a high-voltage silicon stack to obtain a required direct-current power supply; adopting a direct-current power supply to charge the charging capacitor, and enabling the charging capacitor to store energy of different voltage levels; storing energy charging capacitors with different voltage levels to respectively discharge the defects of the spark discharge simulation tank body and generate sparks; and measuring the voltage and the current of the spark discharge gap at the spark moment to calculate the SF6 spark discharge energy. According to the method, quantitative discharge can be carried out on the defects ofthe spark discharge simulation tank body, and regular sparks are generated, so that subsequent research on SF6 spark discharge can be carried out under a quantitative condition.

The embodiment of the invention provides an arc fault detection method, device and equipment, and a storage medium. The method comprises the steps of obtaining a current waveform of a current signal of a current period and a current waveform of a current signal of a previous period; determining current waveform deviation characteristics of the current waveform of the current period current signal and the current waveform of the previous period current signal; and determining whether an arc fault occurs in the circuit according to the current waveform deviation characteristic and the first zeroing zone duration of the current waveform of the current period current signal. In the prior art, a large number of samples are needed to train an intelligent algorithm or a neural network model for arc fault detection. A large number of samples are not needed, and the early-stage investment of arc fault detection is reduced; sample limitation is eliminated, the method is suitable for most arc fault detection scenes, and the universality and accuracy of the detection method are improved; and an intelligent algorithm and a neural network model do not need to be set and operated in the detection equipment, so that the performance requirements of memory and the like of the detection equipment are reduced.

The invention discloses a waveform data processing device, and the device comprises: a host end which is used for storing target waveform data in a first storage unit, and transmitting a synchronous starting signal to a waveform data generation module and a waveform data measurement module at the same time; a waveform data generation module which is used for carrying out DA waveform output according to the target waveform data in the first memory after receiving the synchronous starting signal; a waveform data measurement module which is used for performing AD waveform measurement to obtain measurement data after receiving the synchronous starting signal, and storing the measurement data into a second memory, wherein the waveform data generation module and the waveform data measurement module are modules in a target FPGA board card. According to the invention, generation and measurement of waveform data can be synchronously achieved. The invention further discloses a waveform data processing method, a storage medium and electronic equipment, which have the above beneficial effects.

A method and an input signal level detection apparatus that correctly detect a level of an input signal while consuming low power apparatus including: a full-wave rectifier outputting a full-wave rectified waveform by performing a full-wave rectification on a first signal corresponding to an input signal, and on a second signal having a phase difference of 180 degrees from the first signal; a common voltage detector detecting a common voltage of the first signal and the second signal; and a level detection unit detecting a level of the input signal, based on a subtraction result obtained by subtracting the common voltage from the full-wave rectified waveform.

The invention provides a test board structure for IGBT device current waveform detection. The invention aims to effectively capture a discharge current waveform consistent with a typical waveform in internationally accepted test specifications. The structure includes a pogo probe for directly contacting a discharge device, a filter for filtering out high-frequency interference, an attenuator for reducing current peaks to facilitate testing, a test resistor for converting current signals, and a grounding plate for connecting all the parts, wherein the filter and the attenuator are located on the grounding plate, and the grounding plate is connected with a metal socket so as to connect an oscilloscope, and the grounding plate contains a structure which enables a fixing effect and is used forconnecting the other parts of the test system.

The invention relates to a distortion current detection error calibration method of an electric release. By use of a peak coefficient K

and a waveform coefficient K<W> of distortion currents, influences exerted by two typical distortion current waveforms, i.e., triangular waves and rectangular waves on detection errors of the electric release under peak value current detection and mean value current detection methods are analyzed. Errors of peak value detection and mean value detection under different distortion current waveforms can be seen through a peak value detection error curve and a mean value detection error curve. According to a current waveform feature and a detection error curve of a nonlinear load, action current setting values are properly adjusted, and the phenomenon of frequent misoperation of the electronic release due to the distortion currents can be avoided to a certain degree.