160 results about "Vibration signal processing" patented technology

The invention discloses a wind turbine gear box fault recognition method. The method comprises the following steps: historical wind turbine gear box operation data in a certain time range are acquired; autocorrelation analysis is adopted for carrying out wavelet de-noising processing on the historical data; through fast Fourier transform, time domain and frequency domain characteristic parameters in the historical data after de-noising are extracted; a kernel principal component analysis method is adopted to carry out dimensionality reduction on the characteristic parameters, and several nonlinear principal elements with the maximum variance cumulative contribution rate are extracted; the nonlinear principal elements extracted by the historical gear box normal operation data are used for building a normal model, a support vector machine is used for training to guide the nonlinear principal elements extracted by later gear box operation historical data to the model after training, and thus, the gear box fault is recognized. The vibration signal processing ability is improved, and an important role is played in gear box fault recognition.

The present invention relates to a vibration signal processing method and system that can be used to account for situations where impact or impulse events are hidden in a normal vibration reading by low frequency vibrations and high frequency noise. In one preferred form, the method of the present invention comprises the steps of obtaining electrical vibration signals that represent mechanical vibrations of a machine (102-106), converting the electrical vibration signals into digital vibration samples (108), dividing the digital vibration samples into equal time intervals and determining the average absolute amplitude of the digital vibration samples for each time interval (110), generating a time waveform comprising the determined average amplitudes (112, 114), and processing the time waveform as if it were an independently-detected signal (116-120).

A vibration signal processing method based on HHT (Hilbert-Huang Transformation) and related analyses includes steps as follows: using EMD (empirical mode decomposition) to decompose vibration signals; carrying out related analyses to each mode component obtained through decomposition; carrying out Hilbert transformation to denoised signals and obtaining a Hilbert spectrum. Aiming at the defect that noisy signals cannot be distinguished in signals if the HHT method is applied directly, the invention provides the method based on HHT and the related analyses, and denoises noisy signals. Through analyses on the Hilbert spectrum of the extracted noisy mode components and a marginal spectrum, the frequency and amplitude information of noisy vibration signals can be effectively extracted. The method can be used for processing signals of metallurgical machinery, aerospace, hydropower engineering, aeromancy and so on, and effectively remove noise.

The invention discloses a GIS fault diagnosis system and a method thereof. The system comprise a vibration signal acquisition module, a UHF signal acquisition module, an ultrasonic signal acquisition module and a personal computer. The vibration signal acquisition module comprises a vibration signal processing module, a vibration signal acquisition device and multiple vibration sensors; the vibration sensors acquire vibration signals and transmit to the vibration signal acquisition device after processing through the vibration signal processing module; the UHF signal acquisition module comprises a UHF signal processing module, a UHF signal acquisition device and multiple UHF antennas; the UHF antennas acquire UHF signals and transmit to the UHF signal acquisition device after processing through the UHF signal processing module; the ultrasonic signal acquisition module comprises an ultrasonic signal processing module, an ultrasonic signal acquisition device and multiple ultrasonic signal sensors; the ultrasonic signal sensors acquire ultrasonic signals and transmit to the ultrasonic signal acquisition device after the processing through the ultrasonic signal processing module. By the aid of the system, the problem that the GIS operation state cannot be estimated completely through one single diagnostic method is solved.

The invention discloses an EEMD-based automatic balancing machine vibration signal processing method. A mathematic morphological filter is adopted to pre-process an extracted vibration signal and eliminate pulse interference in the signal, and for the mode aliasing problem in empirical mode decomposition, an ensemble empirical mode decomposition method is adopted to extract the frequency and phase of unbalance. The method includes the following steps: firstly, a mathematic morphological method is utilized to pre-process a vibration signal measured by a sensor and filter pulse interference; secondly, an ensemble empirical mode decomposition method is utilized to decompose the signal processed by the mathematic morphological method in the first step, and the intrinsic mode function component of the signal is obtained; and thirdly, the amplitude phase of the vibration signal is obtained through Hilbert transform.

The invention relates to a method for vibration signal processing and a system, for obtaining situation of collision or extrusion incident hidden in normal vibration through low-frequency and high-frequency noise. In a optimized embodiment manner, the method of the invention comprises the steps of: obtaining electrical vibration signals having amplitudes and frequencies that represent mechanical vibrations of a machine; converting the electrical vibration signals into digital vibration samples; dividing the digital vibration samples into equal time intervals; determining the average absolute amplitude of the digital vibration samples for each time interval; generating a time waveform comprising the determined average amplitudes; and processing the time waveform as if it were an independently-detected signal. The invention provides a method and a system for accomplishing detection type processing, with high signal to noise ratio (SNR), without strong signal processing, or at least provides available choice to the public.

A wind turbine includes a first vibration sensor for producing a first vibration signal; a second vibration sensor, displaced from the first vibration sensor, for producing a second vibration signal; and a processor for comparing the first vibration signal to the second vibration signal and controlling the wind turbine in response to the comparison.

The present invention provides a camera system which is provided with signal processing control means for changing the filter characteristic of parallel vibration signal processing means in conformity with the output signal of rotation vibration signal processing means and thereby can photograph an image suffering little from blur even during macro-photographing.

The embodiment of the invention discloses a rotating machinery rotor operation state modal analysis method based on order extraction, and relates to the field of vibration signal processing and system parameter recognition. According to the invention, harmonic interference generated by a rotating machinery rotor under the working states can be avoided, so reliability modal parameter recognition is improved and the method is suitable for vibration modal parameter recognition of the rotating machinery rotor under the working states. The method comprises steps of extracting order vibration signals of the rotating machinery rotor under the working states by use of the order tracing algorithm based on instantaneous estimation; and carrying out modal parameter recognition for the extracted the signal operation modal recognition algorithm.

The present invention relates to a vibration signal processing method and system that can be used to account for situations where impact or impulse events are hidden in a normal vibration reading by low frequency vibrations and high frequency noise. In one preferred form, the method of the present invention comprises the steps of obtaining electrical vibration signals that represent mechanical vibrations of a machine (102-106), converting the electrical vibration signals into digital vibration samples (108), dividing the digital vibration samples into equal time intervals and determining the average absolute amplitude of the digital vibration samples for each time interval (110), generating a time waveform comprising the determined average amplitudes (112, 114), and processing the time waveform as if it were an independently-detected signal (116-120).

The invention discloses a micro-vibration signal processing method for processing acquired micro-vibration signals and obtaining disturbance-vibration force and error analysis. The micro-vibration signal processing method comprises the following steps of: firstly, installing a calibration disc on a six-component eight-sensor disturbance-vibration-force testing platform fixedly, hammering 16 calibration points on the calibration disc by using a standard force hammer, and when hammering at every time, acquiring voltage time-domain signals of the force hammer and eight sensors and a frequency response function of the six-component disturbance-vibration force testing platform; obtaining a calibration matrix and calibration errors by the calibration process; secondly, acquiring time-domain data by a data acquisition system when moving parts on the six-component eight-sensor disturbance-vibration-force testing platform generate small disturbance for the testing platform, acquiring the time-domain data by the data acquisition system, obtaining a frequency-domain result by fast Fourier transform, obtaining a disturbance-vibration-force frequency-domain signal by the calibration matrix and obtaining disturbance-vibration-force time-domain data by inverse Fourier transform.

The invention discloses a distributed optical fiber circumference vibration signal processing and recognizing method based on an image. The distributed optical fiber circumference vibration signal processing and recognizing method comprises the following steps that disturbance data of all detection point positions within a whole distributed circumference detection range are collected in real time; when the disturbance data of a certain detection point position are larger than a set threshold value, the disturbance data of the detection point and the disturbance data within the M*N regional range around the detection point are collected, and the numerical values of the disturbance data are mapped in the range of 0-255; a grey level co-occurrence matrix is calculated according to the mapping values, and texture feature statistic parameters in multiple directions in the grey level co-occurrence matrix are calculated; the texture feature statistic parameter numerical values in multiple directions are compared, and if the texture feature statistic parameter numerical values in multiple directions are similar, it is determined that variable system noise is generated in the section; if deviation exceeds a preset value, it is determined that intrusion disturbance occurs at the moment; mode recognition is carried out on the intrusion disturbance signals so as to judge the variety of intrusion behaviors.

The invention discloses a distributed optical fiber vibration signal noise reduction method based on variational mode decomposition. The method comprises the steps that distributed optical fiber vibration signals are acquired, variational mode decomposition is conducted on the distributed optical fiber vibration signals, original signals can be divided into components of different modes, high-frequency noise in the vibration signals can be filtered out in the decomposition process, high-frequency noise of the vibration signals is filtered out, and good signal-to-noise separation performance isachieved; Wavelet packet threshold denoising is carried out on each modal component, and types of noise such as granular noise and low-frequency noise in environment noise can be further filtered out. And the processed signal is reconstructed to obtain the denoised optical fiber vibration data, so that the signal-to-noise ratio of the optical fiber vibration data and the optical fiber vibration signal processing accuracy can be effectively improved.

The invention discloses an automobile vibration fault detection system and a detection data analysis method thereof. The automobile vibration fault detection system comprises a vibration signal acquisition device and a vibration signal processing device. The vibration signal acquisition device is arranged on an automobile. The vibration signal acquisition device comprises at least one acceleration sensor which is connected with the vibration signal input end of a controller. The wireless transmitting end of the controller is connected with a wireless transmitter. The vibration signal processing device comprises a wireless transmission device which is used for receiving the vibration signal transmitted by the wireless transmitter. The wireless transmission device is connected with a processor. The processor is also connected with a data analyzer and a data storage device. The data analyzer is used for performing data analysis on the vibration signal. The data storage device is used for storing the vibration signal. The beneficial effects are that the automobile operation safety factor is great, the vibration signal detection accuracy is high, the vibration signal processing speed is fast and the maintenance speed is fast.

The invention discloses an automatic balancing machine vibration signal processing method. Aiming to solve common problems of frequency multiplication interference, non-integral harmonic interference and strong noise interference to vibration signals to be processed, the method includes fitting general frequency values of different frequency components of the signals by the least square method to obtain wavelet transform scale factors, performing band-pass filtering on the signals through the Morlet complex continuous wavelet transform to accurately extract unbalanced vibration signals with revolving speed the same with that of a rotor, and finally calculating amplitude and frequency of the vibration signals with both measurement precision and speed increased. Since phase of the vibration signals is calculated by the full-phase FFT (fast Fourier transform) spectral analysis, initial phase of the vibration signals can be acquired accurately by the method.

The invention belongs to the technical field of structural strength and environment reliability tests, in particular to a multi-dimensional random vibration control method. The method comprises the steps of setting a reference spectrum matrix and the number of control spectral line number; generating real random drive signals; calculating a control spectrum matrix, and driving and rectifying the real random drive signals; and returning to the former step until the control spectrum matrix is located in a tolerance zone of the reference spectrum matrix. The method solves the technical problem that an existing multi-dimensional random vibration control method is slow in processing speed. According to the method, a multi-dimensional random vibration signal processing module is used to rectify the signals, and the signals do not need transmitting from a lower computer to an upper computer to be rectified, processing speed is improved, and real-time requirements are better met.

The invention discloses a blind crutch with a stretchable cross rod. The blind crutch comprises a handle, a crutch body and a crutch tip; the stretchable cross rod is arranged at the crutch tip; idler wheels are arranged at two ends of the cross rod; when being stretched, the stretchable cross rod is vertical to the crutch body for probing a road surface, and when being contracted, the stretchable cross rod is parallel with the crutch body; a corresponding limiting device is used for positioning when the cross rod is in the stretching or contracting states. The blind crutch further comprises an input module for detecting obstacles around the blind crutch, an output module for outputting a sound or vibration signal, a processor for controlling the system to work, a stretching-contracting switch for detecting the state of the cross rod, and a battery module for providing energy for the work of the blind crutch. The processor can learn the obstacle condition around the blind crutch by detecting the information of the input module, and then the processor can feeds the obstacle condition back to a user by the output module, the user can stretch the cross with the idler wheels to push or contract and recover the cross rod to the traditional use state, and the blind crutch has high practicability by conveniently changing the use state and visually outputting the signal.

The invention provides a needling machine transmission mechanism vibration signal processing method based on combination of MEEMD and an exponential wavelet threshold. The needling machine transmission mechanism vibration signal feature extraction method comprises the steps of: carrying out endpoint continuation processing on an acquired needling machine transmission mechanism vibration signal byadopting a waveform matched self-adaptive endpoint continuation method; performing wavelet decomposition, and denoising and reconstructing the acquired signal by utilizing an exponential wavelet threshold function to obtain the denoised signal; performing envelope line fitting on the denoised vibration signal by adopting a cubic B-spline method, and then carrying out MEEMD decomposition on the signal to obtain cross correlation coefficients and kurtosis values of a plurality of IMF components and the denoised signal; performing correlation analysis on the IMFs and the original signal to selectthe useful IMF; and finally performing Hilbert transform on the IMF components to obtain a Hilbert spectrum of the signal, and regarding the Hilbert spectrum as a signal feature of the needling machine transmission mechanism vibration signal. The needling machine transmission mechanism vibration signal feature extraction method is suitable for fault diagnosis of a needling machine transmission mechanism in the industrial field.

The invention provides a method for separating vibration signals of planetary gears of a main reducer of a helicopter, belonging to vibration signal processing for a helicopter. The method includes the steps: obtaining position parameters of an acceleration sensor and position parameters of planetary gears; determining a meshing timing sequence of a separation angle matrix and the planetary gears;acquiring original vibration signals of a plurality of vibration sensors, and according to a cycle period of a planet carrier, segmenting and resampling the plurality of original vibration signals toobtain a plurality of planet carrier periodic signals; performing windowing on the plurality of planet carrier periodic signals to obtain vibration signals of the plurality of planetary gear teeth; and splicing the vibration signals to obtain a planetary gear reconstruction vibration signal. The method for separating vibration signals of planetary gears of a main reducer of a helicopter can extract the signals of the single planetary gear from the vibration signals of the complex planetary transmission system, and can separate the gear signals of each planetary gear, so as to lay the foundation for fault diagnosis of the planetary gears.

The invention provides a bridge stay cable force online detection method and system based on fiber sensing. The system comprises a fiber grating vibration sensor group, a fiber grating vibration demodulation instrument and a stay cable vibration signal processing unit. The fiber grating vibration sensor group comprises a plurality of fiber grating vibration sensors connected in series with the same fiber, each fiber grating vibration sensor is designed based on a cantilever structure and a double-raster coupling method, and chirp rasters are used to replace Bragg rasters, such that the detection scope of the sensors is enlarged, the stability and the anti-interference capability of the sensors are improved, and at the same time, the manufacturing difficulty of the sensors is reduced. The fiber grating vibration demodulation instrument is based on an edge filtering demodulation principle and employs a wavelength division multiplexing technology to realize distributed measurement of a stay cable force, and multiple fiber grating vibration sensors can be multiplexed in one fiber signal, such that the detection capability of the system is improved, the distributed measurement of the stay cable force is made possible, and a more reliable technical means is provided for online detection of a wide-span bridge stay cable.

The invention relates to a metallurgical industry, which comprises classifying the vibrating signal into without dreg, mixed dreg and all dreg period as the training data, vectorization the signal frequency amplitude, forming model base, inputting observation data into each model by the vibrating signal in the pouring process, selecting the max. output probability working status as the identification result, with the system composed of treatment control unit module, power supply management unit module, electronic appliance control unit module, alarming unit module and front end control unit module. It can better solve the random issue of steel melt vibrating signal, with low cost, convenient seal, dismantle, transportation, maintenance, and easy mastery of the operator, with higher accuracy and stability.

The present invention relates to a coal mine ventilator real-time fault diagnosis and early warning device based on a virtual instrument development platform (LabVIEW), including an integrated industrial computer, a vibration signal detection module, an ARM processor, a stabilized power supply module, an SD storage module, and a USB interface chip. The vibration signal detection module processes the detected vibration signal and transmits it to the A / D analog-to-digital converter of the ARM processor, and the ARM processor transmits the processed digital signal to the integrated industrial computer through the USB interface chip or stores it in the SD storage module . The LabVIEW platform of the integrated industrial computer calls the algorithm program in MATLAB through the MatlabScript node, and performs wavelet denoising filtering, CEEMDAN feature extraction, Hilbert transform, and improved support vector machine classification and recognition on the fan vibration signal transmitted to the industrial computer. , the final result of fault diagnosis is displayed on the front panel interface, and the early warning module is called to sound and light alarm for fault information, and sound and light early warning for hidden faults. The device has good real-time performance, high openness, friendly man-machine interface and high reliability.

The invention relates to a mini-type vibration sensor array and application thereof to ground target tracking. The mini-type vibration sensor array is characterized in that: a plurality of same mini-type MEMS (Micro-electromechanical System) vibration sensor chips are integrated and packaged on a PCB (Printed Circuit Board) and corresponding vibration signal processing circuits are also integrated on the same PCB. The plurality of the vibration sensor chips are distributed as a cross array to form a mini-type array. When a certain ground target is measured, only a sensor is put into the plane and distance and direction of a target can be determined according to coordinates of each array element of the sensor and time correlations of each output signal; and the type of the target can be determined according to frequency spectrum characteristics of each array element output signal, such as whether the type is people or vehicle and the like, so as to realize the comprehensive detection and positioning of the target. The mini-type vibration sensor array provided by the invention can be used for detecting the distance, the direction and the type of a ground moving target at the same time.

The embodiment of the invention discloses a harmonic component detection method based on enhanced spectrum kurtosis, and relates to the field of vibration signal processing and system parameter recognition. The method can detect a pseudo resonance component generated by a periodic excitation force in a vibration system, thereby improving the recognition reliability of system parameters. The method comprises the steps: proposing the enhanced harmonic component detection method according to the multichannel vibration response conditions, i.e., comprehensively considering all vibration response information in each calculation; and calculating the enhanced spectrum kurtosis corresponding to different resonance peaks based on the resonance peaks. The method is suitable for the processing of a vibration signal of a mechanical structure system in a working state.

The invention discloses a wind turbine generator gear case combined fault diagnosis method based on support vector machine probability estimate. The wind turbine generator gear case combined fault diagnosis method based on support vector machine probability estimate mainly includes two modules: the first module is vibration signal processing and a fault feature extraction algorithm, based on ensemble empirical mode decomposition (EEMD); and the second module is a training model method and a probability estimate algorithm of the support vector machine. The wind turbine generator gear case combined fault diagnosis method based on support vector machine probability estimate respectively establishes models for different sensors, integrates the results of all the classifiers during the analysis process, and improves the accuracy of diagnosis. The wind turbine generator gear case combined fault diagnosis method based on support vector machine probability estimate takes a simulation signal as a test object, provides a detailed algorithm description, and verifies the validity of the algorithm at the gear case combined fault diagnosis aspect through the experiment.

The invention relates to a seismic-while-drilling drill bit vibration signal measurement system which can meet the application requirements of seismic-while-drilling engineering. The system comprises a drill bit vibration signal acquisition part, a drill bit vibration signal transmission part and a drill bit vibration signal processing part. The drill bit vibration signal acquisition part adopts an independent drill bit vibration signal acquisition sub. Drill bit vibration signal processing is performed by a computer in which drill bit vibration signal acquisition and analysis software is pre-installed. Transmission between the drill bit vibration signal acquisition sub and the computer is realized through a wireless local area network. The drill bit vibration signal acquisition sub is provided with a sensor chamber, a battery chamber, a circuit board chamber and a wireless module chamber in advance on the outer circumference of the middle part of the sub, wherein the sensor is a three-component accelerometer; circuits of a circuit board comprise circuits for filtering and conditioning, signal amplification, A / D (Analog-to-Digital) modulation, digital filtering, a microprocessor, a real-time clock, D / A (Digital-to-Analog) testing, a memory and a GPS (Global Positioning System). The seismic-while-drilling drill bit vibration signal measurement system has the advantages that since a method of rigidly connecting with a drill stem is adopted, the signal quality is good, the construction is convenient to perform and the drilling construction safety is guaranteed.

An artificial intelligence cooking device includes a plate including a heater configured to heat ingredients in a cooking vessel placed on the plate; a vibration sensor disposed below the plate configured to detect a vibration signal of the ingredients in the cooking vessel transmitted through the plate; and a processor configured to determine, via an artificial intelligence model having learned properties of the vibration signal, whether or not the ingredients in the cooking vessel are boiling based on the detected vibration signal provided to the artificial intelligence model and the learned properties of the vibration signal; and output information indicating whether or not the ingredients are boiling based on the determination.

The invention provides a vibration signal reconstruction method for mechanical fault diagnosis. In a non negative condition, sparser coding is carried out on original vibration signals, the signal spectrum detection effectiveness is improved, and the method belongs to the technical field of vibration signal processing. The method comprises steps: 1, vibration signals of a mechanical system are sampled, and the original vibration signals are overlapped and segmented to obtain column vectors to form a training sample; 2, a learning dictionary is initialized, sparse coding is carried out on the training sample based on a non negative-base tracking algorithm to obtain an initial sparse coding matrix; 3, the sparse coding matrix is fixed, and the learning dictionary is optimized and updated based on a non negative K singular value decomposition algorithm; 4, the learning dictionary is fixed, and sparse coding is carried out based on the non negative-base tracking algorithm to update a corresponding sparse coding matrix; 5, the former two steps are circulated, alternate iterative updating is carried out to obtain the final learning dictionary and the final sparse coding matrix; 6, an updating sample is calculated, and reconstructed signals are inversely overlapped; and 7, an envelope spectrum for the reconstructed signals is extracted for fault diagnosis. The method of the invention is used for mechanical fault diagnosis.

The invention relates to a gear box vibration signal processing and analyzing method, which comprises the following steps: synchronously collecting a reference shaft rotating speed signal, a referenceshaft vibration signal and a non-reference shaft vibration signal; identifying the rotating speed pulse edge by the reference shaft rotating speed signal, calculating the instantaneous rotating speedbetween every two pulses, and simultaneously carrying out interpolation calculation on the pulse edge time sequence to obtain an equal angle sampling time sequence; carrying out anti-mixing filteringon the vibration signal of the reference shaft, and carrying out interpolation sampling on the vibration signal of the reference shaft by the equal angle sampling time sequence to obtain an equal angle vibration signal of the reference shaft; obtaining a non-reference axis virtual pulse along time sequence from a reference axis pulse along time sequence, and obtaining an equal angle waveform of anon-reference axis vibration signal through instantaneous rotation speed calculation, equal angle sampling time sequence calculation, digital anti-aliasing filtering and digital resampling. The gearbox vibration signal processing and analyzing method is very suitable for the analysis, fault characteristic extraction and diagnosis of the vibration signals of the intermediate shaft, the planetarywheel shaft and the sun wheel shaft in the gear box and any multi-shafting rotating mechanical system.