22 results about "Waveform sampling" patented technology

This utility model relates to the field of electrical energy detection technology, and proposes a high-current electrical energy detection device with closed-loop control function. The device includes: a programmable power source module, including an output drive unit for outputting current, voltage signals, and waveforms within a large current range; a standard measurement module connected to the output drive unit for detecting the current, voltage signals, and waveform parameters output by the output drive unit; a waveform sampling module connected to the output drive unit for sampling the waveform output by the output drive unit; a closed-loop control module bidirectionally connected to the programmable power source module and the waveform sampling module for adjusting the current, voltage signals, and waveforms; and an external device detection interface connected to the output terminal of the output drive unit for connecting different types of high-current metering devices. This utility model solves the problems of measurement error superposition, unstable output, and insufficient measurement range in traditional detection devices.

The application discloses a kind of scintillator decay time test methods based on waveform sampling, the steps of test method include: scintillator is coupled to the optical window of photomultiplier tube placed in shielding box, using radioactive source excitation sample, open oscilloscope automatic acquisition not less than 100 pulse signals and transmission to control computer;Pulse waveform data acquired by oscilloscope is handled calculation, obtains the decay time constant corresponding to single pulse data;The above steps are repeated for processing all collected pulse data, obtain decay time constant set;With decay time constant set histogram, data should present normal distribution;Using Gaussian function to the normal distribution is fitted, the decay time value corresponding to the peak obtained is the decay time of the sample.The application can accurately test the decay time of different scintillating materials, especially suitable for high-throughput decay time measurement.

This invention provides a laser wavelength locking method based on waveform feature analysis, comprising the following steps: acquiring waveform sampling data of a laser detection signal; identifying signal feature points of the laser detection signal and calculating the average index and index change value of the signal feature points; adjusting the voltage range of the laser driving signal in real time until the voltage range of the laser driving signal matches the sampling point index range of the laser detection signal waveform; performing peak detection on the rising edge or falling edge waveform data to obtain multiple peak sampling points; selecting a target peak sampling point from the multiple peak sampling points based on the energy level transition type of the cesium atom D2 line, and using the voltage value corresponding to the target peak sampling point as the upper and lower limit thresholds of the voltage range of the laser driving signal to achieve laser wavelength locking. This invention solves the problems of slow locking response speed and insufficient dynamic adjustment capability in existing technologies.

The application discloses a kind of DC fault arc precision detection and efficient protection method under power electronic interference, based on system output current signal, the frequency information of the signal short-time Fourier transform is made variance processing to obtain first characteristic quantity, the common frequency band of fault arc is obtained by combining evidence classifier and with normal waveform sampling comparison, whether there is fault arc existence is judged from this, similarly, the difference frequency band of fault arc is obtained by evidence classifier, the topological structure and control strategy of fault arc difference frequency band identification device can be reached, and the purpose of efficient protection is further achieved.The application can significantly improve the effect of DC fault arc precision detection and efficient protection.

The invention provides a laser wavelength locking method based on waveform feature analysis. The method comprises the following steps: acquiring waveform sampling data of a laser detection signal, confirming signal feature points of the laser detection signal, and calculating an index average value and an index change value of the signal feature points; adjusting the voltage range of the laser driving signal in real time until the voltage range of the laser driving signal is consistent with the sampling point index range of the laser detection signal waveform; performing peak detection on the rising edge waveform data or the falling edge waveform data to obtain a plurality of peak sampling points; and based on the energy level transition type of the cesium atom D2 line, selecting a target peak sampling point from the plurality of peak sampling points, and taking the voltage value corresponding to the target peak sampling point as the upper and lower limit thresholds of the voltage range of the laser driving signal to realize laser wavelength locking. According to the invention, the problems of low locking response speed and insufficient dynamic adjustment capability in the prior art are solved.

This invention discloses a waveform sampling lidar ground feature classification method based on a hybrid kernel SVM and OvA strategy. The method includes the following steps: Step 1, preprocessing of the original stripe image; Step 2, multi-domain physical feature extraction; Step 3, feature selection based on the RFE algorithm; Step 4, construction of the hybrid kernel SVM model; Step 5, training and classification of the multi-classification model based on the OvA strategy. This method eliminates the need for point cloud inversion, significantly shortening the data processing cycle. The average recognition time per sample is only 0.34ms. It can achieve rapid and accurate identification of four typical ground features: buildings, slopes, flat land, and vegetation, with an overall classification accuracy of 95.71%. It can meet the requirements of airborne real-time processing and is suitable for scenarios requiring real-time imaging and target recognition, such as geographic surveying, military reconnaissance, and environmental monitoring.

A mobile relay station that moves in the air, the mobile relay station comprising: a waveform sampling unit that receives a signal transmitted from each of one or more transmission devices located on the ground and samples the received signal to thereby generate waveform data of the signal; a control unit that determines a down-sampling rate on the basis of predetermined criteria; a waveform data compression unit that down-samples, at the down-sampling rate determined by the control unit, the waveform data generated by the waveform sampling unit or waveform data obtained by frequency-shifting the waveform data; and a communication unit for a base station that transmits the waveform data down-sampled by the waveform data compression unit to the base station.　

The invention relates to the technical field of circuit simulation waveform data visualization, and particularly discloses a circuit simulation waveform sampling method based on MinMaxLTTB. The method aims at solving the problems of display lagging and waveform distortion caused by the fact that data volume simplification and key feature point reservation cannot be considered in mass waveform data visualization in a traditional sampling technology. The method comprises the following steps: (1) dynamic bucket division: adaptively creating data buckets with different sizes based on target resolution and simulation duration; (2) MinMax extremum pre-extraction: extracting extremum points in each bucket in a layered manner to form a simplified data set; (3) sampling LTTB characteristic values, and selecting an optimal characteristic point based on a triangle area maximum principle; and (4) integrating the sampling points in sequence to generate visual special data. According to the method, dynamic bucket division and a two-stage sampling strategy are combined, the data volume is greatly reduced, meanwhile, the waveform key features are accurately reserved, the real-time visualization performance and accuracy of large-scale circuit simulation waveforms are remarkably improved, and the method is suitable for waveform display modules of various EDA tools.

The application provides a signal testing method, device and equipment of an I2C bus, the method comprising: determining signal quality parameters and signal timing parameters of the I2C bus based on the high level position of the SCL edge pair, the low level position of the SCL edge pair, the high level position of the SDA edge pair, the low level position of the SDA edge pair and the waveform sampling time interval; and performing signal testing on the I2C bus based on the signal quality parameters and the signal timing parameters. Through the application, a feature screening model is constructed based on the high and low level positions of the SCL and SDA edge pairs and the waveform sampling interval, invalid data is accurately removed first, the effective I2C bus signal waveform is locked, then the signal quality and timing key parameters are automatically calculated, the intelligent identification and full-process automatic testing of the I2C bus signal are realized, the testing efficiency is significantly improved, and the consistency and accuracy of the testing results are ensured.

This invention relates to the field of condition monitoring technology, specifically disclosing a mold condition monitoring method for early warning of abnormalities in automotive plastic molding. The method involves simultaneously acquiring displacement change signals of the monitored component relative to the mold template and pressure change signals within the cavity during injection molding. The impact trigger moment is determined based on the pressure change, and the displacement signal is captured within the corresponding time window to form an impact response waveform. By converting the waveform sampling points into a two-dimensional point set and performing normalization, the spatial connectivity of each sampling point at different scales is further analyzed using a persistent cohomology method. A persistent graph is constructed, and topological feature values ​​reflecting the waveform structure are extracted to form an impact response feature vector. This feature vector is compared with a pre-obtained baseline feature vector. When the difference exceeds a set threshold, an abnormality in the mold component is determined, thereby achieving monitoring and early warning of mold condition changes during automotive plastic molding.

The application provides a laser radar aliasing waveform decomposition method based on waveform characteristics, constructs a waveform mathematical model according to seed light characteristics of a laser radar, combines an LM curve fitting algorithm, decomposes aliasing echoes into multiple single echo data, and achieves the purpose of accurately extracting multi-target ranging information. The technical basis of the application is a laser radar full waveform detection technology, that is, a laser radar detection system can sample analog electric signals converted from optical signals into digital waveform signals, and the processing object of the application is a waveform sampling point sequence of seed light and return light detected by the laser radar.

The invention discloses a waveform generation method and system, and the method is executed by a large-scale simulation system, and comprises the steps: responding to a simulation request for a large-scale chip design circuit through each sub-device, and executing simulation operation on a distributed local design circuit in parallel, and sending the local debugging data sampled in the simulation process to the matched slave. And processing the received local debugging data in parallel through each slave to obtain a local waveform file and locally storing the local waveform file. And the host aggregates and stores the local waveform files locally stored by the slaves into the target storage space and forms an index file. And the host responds to the simulation waveform viewing request, calls waveform viewing software to analyze the index file, positions all local waveform files, and merges and presents a complete waveform in a graphical user interface. According to the technical scheme, independent waveform sampling can be carried out on each local design circuit, the waveform file generation time is shortened, and the debugging efficiency of chip simulation is remarkably improved.

The invention provides a current steering type digital-to-analog converter linearity test system and method, and the test system provides configuration information through an upper computer, transmits the configuration information through an FPGA mainboard, and provides test data. The tested digital-to-analog converter performs digital-to-analog conversion on test data under the driving of configuration information to obtain a plurality of test currents, the conversion module converts the plurality of test currents into a plurality of test voltages, the waveform sampling module samples the plurality of test voltages under the configuration of the configuration information, and transmits the sampled voltages to the upper computer through the FPGA mainboard. And performing fitting processing on the plurality of sampling voltages through the upper computer, and determining a linearity error according to the sampling voltages and a voltage fitting value. The linearity error test system provided by the invention is simple in overall structure, small in size and low in cost, does not need to be connected with other additional measurement equipment, remarkably improves the linearity test precision and efficiency through the high-precision waveform sampling module, greatly shortens the test time, and enables the test process to be more accurate.

The invention discloses a single-chain multiplexing high-resolution TDC design method and system based on an FPGA and a medium, and the method comprises the steps: carrying out the specific signal configuration of a Carry4 module in a single tap delay chain, and converting a single jump edge of a tested pulse signal into a composite waveform signal containing four jump edges in the chain; sampling the waveform by using a global clock to obtain a composite sequence; the method comprises the following steps: dividing a sequence into two subsequences by adopting a sliding window method, coding two one-hot codes from each subsequence by adopting a neighborhood detection method, and converting to obtain four initial fine count values; and finally, a high-precision fine counting result is obtained through fusion. The method has the advantages that multiple times of multiplexing of a single delay chain is innovatively achieved, consumption of hardware logic resources such as a Carry4 module and a trigger is greatly reduced while the high resolution of an equivalent multi-chain averaging method is achieved, and integration with other functional modules in an FPGA is facilitated.

The application provides a LoRa signal physical layer security method based on fractional domain phase pseudo-randomization. Step 1: generating a LoRa signal, obtaining a modulated waveform s(t) based on the LoRa signal including a bandwidth B and a spreading factor SF; step 2: sampling the modulated waveform s(t) of step 1 to obtain a discrete signal s(n); step 3: generating a fractional domain signal under an alpha' angle based on the discrete signal s(n) of step 2; step 4: performing phase pseudo-randomization on the fractional domain signal of step 3, and transforming the obtained fractional domain signal into a time domain, so that the amplitude of each point of the time domain FRPLM signal is affected by the pseudo-random phase e jθ Step 5: demodulating the time domain FRPLM signal of step 4 to obtain the original physical layer bit sequence of the LoRa signal. The application reduces the existence detection of the transmission signal by an illegal interception party, and at the same time, without affecting the demodulation performance of a legal receiving party, makes the illegal interception party unable to demodulate effective information.

The invention provides a multi-wave sequence generation method and system for a waveform generator, a storage medium and electronic equipment, and the method comprises the steps: obtaining multiple segments of digital waveforms, converting the actual sampling rate of each segment of digital waveform into the inherent sampling rate of the waveform generator, sampling each segment of digital waveform, and splicing the sampled waveform data, to form an initial digital waveform; and performing waveform processing on each segment of waveform data of the initial digital waveform to obtain a playing digital waveform, wherein the playing digital waveform is used for playing of a waveform generator. The sampling rate conversion method is adopted, sampling, splicing and generation of waveform data of various digital waveforms with different sampling rates are achieved, the digital waveforms generated through splicing are subjected to waveform processing, the continuity of playing the digital waveforms is guaranteed, the head data point and the tail data point of each segment of digital waveform are continuous, and therefore the processing efficiency of the digital waveforms is improved. Distortion of digital waveform head and tail amplitudes is reduced, and the signal quality of multi-wave sequence continuous playing is improved.

The present application relates to a kind of digital pulse energy extraction methods based on multi-section pulse integration, including step 1, extracting digital signal, triggering filtering algorithm is used for the discrimination of signal;Step 2, according to the time of pulse arrival, determine the five-section / seven-section interval integral value of waveform sampling point recorded by firmware and two timestamp information;Step 3, according to the interval integral value and timestamp information in step 2, calculate baseline value;Step 4, according to the interval integral value and timestamp information in step 2 and baseline value in step 3, calculate pulse area.The algorithm is simplified to calculate the integral value of multi-section continuous pulse, which is convenient to realize on FPGA;The method based on five-section integration can solve baseline evaluation under high accumulation rate, and dead time is small;The method based on seven-section integration can improve the energy resolution when containing low-frequency noise.

The application discloses a kind of underwater LiDAR full waveform sampling methods based on FPGA timing control.This full waveform sampling method controls the timing of each module according to sampling requirements, avoids timing conflicts in the sampling process, and achieves the requirements of large data storage and high-speed read-write.The method solves the problems of slow speed and excessive delay in the sampling process controlled by single-chip microcomputer, greatly improves the collection speed and operating frequency of the laser radar collection module, and expands the application range of the laser radar, providing more possibilities for the application field of laser radar.

The application provides a steady-state power quality data compression method, a decompression method and a compression and decompression device, comprising the following steps: S1, sampling the waveform of an electric energy signal according to a preset sampling point number and a sampling time length to obtain a time-domain waveform data sequence of the electric energy signal to be measured; S2, obtaining the amplitude and phase of different cycles within a preset time length according to the sampling time length, wherein the time-domain waveform data sequence is decomposed into linear superposition of sinusoidal signals according to an analysis formula, and the amplitude and phase of the fundamental wave and the amplitude and phase of each harmonic component in a preset number of times are calculated; S3, calculating the root mean square of the amplitude within the preset time length to obtain an amplitude sequence, and storing the amplitude sequence and the phase of the first cycle. The above method can obtain a higher compression ratio, reduce the storage space, and be decompressed through a decompression method matched with the above method, and during the decompression, a compression and reading device matched with each other is arranged.

The invention discloses a waveform sampling laser radar underwater echo signal enhancement method based on MASFCycleGAN, so as to obtain more accurate pixel-by-pixel three-dimensional space coordinates of an underwater target. According to the method, a multi-scale feature loss function is fused, learnable parameters are dynamically adjusted, it is ensured that in the neural network training process, an image is forcibly enhanced to restore an original stripe image on the pixel level, learning of a local texture structure and edge high-frequency information is enhanced, and the image quality is improved. Meanwhile, the similarity of the enhanced image and the original image in the aspect of high-level semantics is enhanced and measured, so that the pixel-level consistency, the structural consistency and the semantic consistency of the underwater stripe image are kept before and after enhancement; a multiple attention mechanism is provided, and a selective kernel attention mechanism improves the perception ability of the model for different scale information in the image; the extrusion and excitation module of the multi-layer perceptron is aggregated to automatically obtain the importance degree of each feature channel, and useful features are selectively emphasized by using global information.

The invention relates to the technical field of integrated circuits, and discloses a 5G baseband signal processing method based on an ASIC (Application Specific Integrated Circuit). The method comprises the following steps: receiving a 5G wireless signal and converting the 5G wireless signal into a digital baseband signal stream, and generating an initial waveform sampling sequence; performing multi-dimensional feature extraction on the sequence, and separating a time domain feature vector and a frequency domain feature matrix; dynamically configuring a cut-off frequency parameter of the first filter according to a peak fluctuation interval in the time domain feature vector; and adaptively adjusting the stopband attenuation depth of the second filter based on the subcarrier energy distribution in the frequency domain characteristic matrix. And when it is detected that the synchronization deviation between the time domain feature vector and the frequency domain feature matrix exceeds a tolerance threshold, activating a waveform reconstruction engine to generate a compensation coefficient. And loading the compensation coefficient to a register block of the ASIC, and correcting the waveform distortion component of the digital baseband signal flow in real time. According to the invention, the adaptability of the system to the complex signal environment is enhanced, and the stability and accuracy of the signal in the transmission process are ensured.

The application provides a power sound source equipment test system and method, wherein the power sound source equipment test system is connected with a power sound source equipment, and the power sound source equipment test system comprises a detection sampling module, a waveform sampling module, a signal sampling and holding module and a control module. The application collects sound source signals of the power sound source equipment through the detection sampling module and respectively feeds back the sound source signals to the waveform sampling module and the signal sampling and holding module. The waveform sampling module outputs waveform signals to the control module according to the sound source signals. The signal sampling and holding module outputs current signals to the control module according to the sound source signals. The control module obtains audio waveform information and current information according to the waveform signals and the current signals, and judges whether the sound source frequency and the sound source power are qualified according to the audio waveform information and the current information. Thus, the application not only realizes accurate definition of the sound source frequency and the sound source power, but also avoids damage to the hearing of the test personnel caused by the high-power sound source.