39 results about "Negentropy" patented technology

The invention provides a rolling bearing fault feature extraction method based on an independent component analysis and cepstrum theory. The rolling bearing fault feature extraction method comprises the steps of acquiring a vibration acceleration testing signal of a rolling bearing by using an acceleration sensor; decoupling and separating the vibration acceleration testing signal by using FastICA based on negentropy maximization; selecting a separated signal capable of representing fault feather information to the maximum extent; carrying out cepstrum analysis on the selected separated signal, and drawing a cepstrum chart; observing whether the cepstrum chart has a fault feature frequency or an obvious peak value at a frequency multiplication position, and furthermore, judging whether the rolling bearing has a fault. By using the rolling bearing fault feature extraction method, the feature information of a fault signal of the rolling bearing can be effectively recognized from a complex sideband signal, a periodical fault component in a sideband can be conveniently extracted, the fault information is remarkably enhanced, the fault diagnosis precision is greatly improved, the fault diagnosis time period is shortened, and the spectral analysis difficulty is simplified; in addition, the rolling bearing fault feature extraction method is easy to realize and good in real-time property.

The invention relates to a wind turbine generator set bearing fault feature extraction method based on vibration data. The method includes the steps of: 1. using a JADE algorithm to perform blind source separation on an observation signal, so as to obtain a source signal; 2. calculating kurtosis and negentropy of the source signal; 3. calculating a singular value of a source signal envelope matrix; and 4. utilizing a local linear embedding method to extract fault features. The wind turbine generator set bearing fault feature extraction method based on vibration data combines the blind source separation with the local linear embedding method, and is particularly suitable for rotary mechanical equipment such as a bearing; and the method can effectively eliminate noise mixed in a bearing vibration signal process, and separate a fault source signal, thereby providing more accurate information for fault feature extraction.

Blind polarization demultiplexing algorithms based on complex independent component analysis (ICA) by negentropy maximization for quadrature amplitude modulation (QAM) coherent optical systems are disclosed. The polarization demultiplexing is achieved by maximizing the signal's non-Gaussianity measured by the information theoretic quantity of negentropy. An adaptive gradient optimization algorithm and a Quasi-Newton algorithm with accelerated convergence are employed to maximize the negentropy. Certain approximate nonlinear functions can be substitutes for the negentropy which is strictly derived from the probability density function (PDF) of the received noisy QAM signal with phase noise, and this reduces the computational complexity. The numerical simulation and experimental results of polarization division multiplexing (PDM)-quadrature phase shift keying (QPSK) and PDM-16QAM reveal that the ICA demultiplexing algorithms are feasible and effective in coherent systems and the simplified ones can also achieve equivalent performance.

The invention discloses a self-adaptation independent component analysis method for harmonic wave impedance estimation, relates to the field of power systems and aims to solve the problems that in theprior art a conventional power system harmonic wave impedance estimation method is low in precision, a novel rapid independent component analysis algorithm is low in convergence performance and source signals cannot be all recovered with an optimal effect. The method comprises the following steps: firstly, sampling a harmonic wave voltage and harmonic wave current at a public coupling point; secondly, carrying out centralization and whitening processing on a harmonic wave voltage sampling value and a harmonic wave current sampling value as known mixed signals; thirdly, with the criterion of negentropy maximization, carrying out iteration so as to obtain a primary separation matrix; finally carrying out self-adaptation selection on nonlinear functions, and carry outing progressivity analysis till an optimal nonlinear function, and calculating a harmonic wave impedance matrix, thereby finally obtaining harmonic wave impedance. By adopting the method, limits of conventional methods are overcome, meanwhile defects of rapid independent component analysis are made up, and the harmonic wave impedance estimation precision can be improved.

A method for filtering a non-Gaussian linear stochastic system based on the negentropy comprises the steps that firstly, a filter is designed according to a common linear stochastic system; secondly, due to the fact that an error equation is a non-Gaussian stochastic process, an indicator function is selected as a linear combination of a covariance matrix and the negentropy of an evaluated error, and the probability statistic characteristic of the evaluated error is represented as complete as possible; secondly, a probability density function of the evaluated error is worked out according to the characteristic of a characteristic function, and therefore a negentropy expression of the evaluated error is obtained; finally, a filter gain of the filter is solved and the indicator function is minimized. According to the method, the linear stochastic system state influenced by non-Gaussian noise can be estimated and the method can be applied to the fields of inertial navigation, a guiding system, target tracking, signal processing and the like.

A computer-implemented data processing system for blind extraction of more pure components than mixtures recorded in 1D or 2D NMR spectroscopy and mass spectrometry. Sparse component analysis is combined with single component points (SCPs) to blind decomposition of mixtures data X into pure components S and concentration matrix A, whereas the number of pure components S is greater than number of mixtures X. NMR mixtures are transformed into wavelet domain, where pure components are sparser than in time domain and where SCPs are detected. Mass spectrometry (MS) mixtures are extended to analytical continuation in order to detect SCPs. SCPs are used to estimate number of pure components and concentration matrix. Pure components are estimated in frequency domain (NMR data) or m / z domain (MS data) by means of constrained convex programming methods. Estimated pure components are ranked using negentropy-based criterion.

A method, system, and computer program product for identification of more than two pure components from two mixtures using sparse component analysis. Spectroscopic data for two mixtures X are analyzed in a recording domain or in a first new representation domain by using linear transform T1, wherein pure components in the first new representation domain are sparser than in the recording domain. The number of pure components and mixing matrix are estimated by means of a data clustering algorithm. The pure components are estimated by means of linear programming, convex programming with quadratic constraint (l2-norm based constraint) or quadratic programming method with l1-norm based constraint. The estimated pure components are ranked using negentropy based criterion.

An echo canceler includes an adaptable filter that is updated during double-talk and far-end talk. The echo canceler receives a microphone signal that includes a near-end signal and echoes resulting from a far-end signal. The echo canceler whitens the far-end signal and decorrelates the microphone signal. The whitening and decorrelating is done as a preprocessing step for the one-unit blind source separation algorithm. A criterion of measure is used to emphasize the statistical independence of the echo canceled signal and the far-end signal. The echo cancellation problem is cast as a one-unit blind source separation problem. A one-unit blind source separation algorithm such as negentropy maximization can be used to extract the echo canceled signal.

The invention discloses a DWT-SVD-ICA-based digital audio watermarking algorithm. The algorithm is performed according to the following steps: the first step, preprocessing is performed on an original audio signal, and a watermark is embedded in a selected appropriate segment; the second step, when the watermark is embedded, three-level wavelet conversion is performed on the original audio signal, singular value decomposition is performed on an approximate component of the wavelet conversion, and then watermark embedment is completed by utilizing a random mixing method; and the third step, when the watermark is extracted, wavelet conversion and singular value decomposition are performed on the audio signal embedded with the watermark, and then watermark blind detection is achieved by utilizing a negentropy maximization fixed point algorithm. Compared with a traditional ICA-based audio watermarking algorithm, the DWT-SVD-ICA-based digital audio watermarking algorithm is advantageous in that watermark robustness is improved to some extent, that is to say, the watermark robustness is high; and imperceptibility of the watermark can be guaranteed, and blind extraction of the watermark can also be guaranteed.

The invention discloses a multi-feature fusion cognitive underwater acoustic communication space-fast time adaptive processing algorithm. The algorithm includes the following steps: introducing an interference feature analysis-based interference cognitive function on the basis of a traditional space-fast time adaptive array processing algorithm; calculating the number of interference sources by using an array covariance matrix feature decomposition mode, and estimating the direction of a target user and the direction of interference incoming waves by adopting a MUSIC spatial spectrum analysismode; separating interference signals by using a negentropy maximized Fast-ICA based blind source separation algorithm, analyzing time domain features by using an envelope detection mode, analyzing the time-frequency spectrum by using a short-time Fourier transform mode, and further extracting interference features to identify interference types; and finally, selecting appropriate interference samples to perform space-fast time adaptive cancellation according to the interference types, and further improving the convergence speed of the adaptive algorithm. The beneficial effects are that: the dimensionality reduction processing and cancellation sample selection of the space-fast time adaptive algorithm can be realized, and the fast and reliable convergence of the space-fast time adaptive processing can be guaranteed.

An echo canceler includes an adaptable filter that is updated during double-talk and far-end talk. The echo canceler receives a microphone signal that includes a near-end signal and echoes resulting from a far-end signal. The echo canceler whitens the far-end signal and decorrelates the microphone signal. The whitening and decorrelating is done as a preprocessing step for the one-unit blind source separation algorithm. A criterion of measure is used to emphasize the statistical independence of the echo canceled signal and the far-end signal. The echo cancellation problem is cast as a one-unit blind source separation problem. A one-unit blind source separation algorithm such as negentropy maximization can be used to extract the echo canceled signal.

The invention provides a rotating machine fault diagnosis method based on Fast ICA-spectrum kurtosis-envelope spectrum analysis. The method includes the steps that (1), an acceleration sensor is used for obtaining vibration acceleration test signals of a rotating machine; (2), the test signals are separated in a decoupling mode by the adoption of a Fast ICA method with negentropy maximized; (3), the spectrum kurtosis of the separated signals is calculated, and the separated signals capable of representing fault information best are screened out; (4), Hilbert envelope spectrum analysis is performed on the selected separated signals; (5), the frequency corresponding to the peak value of an envelope spectrum is compared with the fault character frequency of a bearing, so that a concrete fault is diagnosed. The effectiveness of the method is verified well by the inner ring fault diagnosis of a rolling bearing of the rotating machine, the fault information is obviously increased, the precision of the fault diagnosis is greatly improved, the fault diagnosis method is easy to achieve and good in real-time performance, and it is illustrated that the rotating machine fault diagnosis method has good application prospects.

The invention provides a multi-robot grid map splicing method based on optimal graph matching. The multi-robot grid map splicing method comprises the following steps: extracting key points and featuredescriptors of a to-be-spliced grid map; retrieving a key point with the most similar feature descriptor for each to-be-matched key point as a rough matching point pair; constructing a characteristicdissimilarity matrix and calculating a residual matrix; combining and normalizing the residual matrix and the characteristic dissimilarity matrix to generate a transmission cost matrix; introducing atransmission cost matrix to construct an optimal transmission target function, performing negentropy regularization on the optimal transmission target function, and solving optimal matching through aSinkhorn-Knopp algorithm; solving rigid body change parameters between the optimal matching points through a least square method, transforming the whole grid map, and obtaining a fused map. Accordingto the multi-robot grid map splicing method, the splicing speed and precision of the grid map are effectively improved, the number of correct matching point pairs in the result is large, and the to-be-spliced grid map can be spliced without a large overlapping area.

The invention provides a blind source separation method based on a quantum rhinoceros search mechanism, and designs a hybrid optimization objective function designed based on two different independence criteria, i.e., the hybrid optimization objective function is designed based on two independence criteria of maximization kurtosis and maximization negentropy, and the two criteria are endowed withcorresponding weight coefficients. The optimal criterion of the intelligent calculation method can be judged according to the change condition of the hybrid optimization objective function value alongwith the weight coefficient, so that a more accurate blind source separation result is obtained. Furthermore, a blind source separation method based on a quantum rhinoceros search mechanism and a hybrid optimization objective function is designed. The method designed by the invention can realize blind source separation of aliasing signals, has the advantages of the high convergence speed, high separation precision, stable performance and the like, and has a wide application prospect.

The invention discloses a heart impact artifact signal extraction device and method, and belongs to the technical field of biomedicine signal processing. The method includes the steps that electrocardiosignals and electroencephalogram signals synchronously collected by EEG-fMRI are transmitted to a heart impact artifact signal extraction module; the heart impact artifact signal extraction module processes the electroencephalogram signals with a fast ICA blind signal processing algorithm based on negentropy and a heart impact artifact signal extraction method with the electrocardiosignals as reference signals, and heart impact artifact signals are obtained through extraction; a signal display module is used for displaying the heart impact artifact signals in real time. The heart impact artifact signal extraction device has the advantages that a lead system is simple in design and convenient to obtain, and the heart impact artifact signal extraction device is capable of extracting the heart impact artifact signals in real time, facilitates clinical application, and is small in size and convenient to carry.

The invention relates to a series of devices with the upward water flow function under the situation that conventional energy consumption does not exist, in particular to a simple channel device achieving spontaneous lighting. The problem that entropy production is irreversible in the energy circulation process is mainly solved, and in other words, negentropy is achieved. The potential energy of water is increased and changed into water flow kinetic energy, the water flow kinetic energy promotes a water turbine to generate power, and electric energy is output to lighting lamps to emit light for lighting after passing a control system and an energy storage system. The device comprises a device body with the upward water flow function, a downward water flow channel, a water turbine generator, an electric control system, the lighting lamps, and an anti-seepage and anti-evaporation closed system. By means of the whole system, the potential energy of the water can be increased under the situation that conventional energy is not consumed, the conversion between the potential energy and the kinetic energy, conversion between the kinetic energy and the electric energy and conversion between the electric energy and visible radiation can be achieved, the light spontaneous lighting is achieved, other energy is not additionally consumed, negentropy is achieved on the basis of the thermodynamics entropy production aspect, and the frequent happening frequency of the earth natural disasters can be finally reduced through the negentropy path.

The invention provides an autonomous underwater robot propeller weak fault feature extraction method, which belongs to the technical field of underwater robot fault diagnosis and comprises two parts: fault feature enhancement and feature fusion. Firstly, Gaussian properties of all modes of a multi-source state signal and a control signal are judged through negentropy, so that parameters are optimized, noise reduction is completed, and fault features are extracted and enhanced based on a modified Bayesian algorithm. Afterwards, the characteristic signals are divided into a plurality of time intervals, faults occurring in all the intervals serve as focal elements, first-time characteristic fusion is conducted on all the signals except for the longitudinal speed, second-time fusion is conducted on the result of the first-time fusion and the characteristic signals of the longitudinal speed, and the fault characteristics are further enhanced; and meanwhile, monotonicity is presented between the fault feature and the fault degree. The method can provide a basis for subsequent fault detection and identification, and is especially suitable for state monitoring of an autonomous underwater robot propeller.

The invention discloses a CNG (compressed natural gas) compressor rolling bearing fault feature extraction method, which comprises the following steps of: constructing a frequency spectrum trend according to a frequency spectrum of an acquired complex bearing signal, and dividing the frequency spectrum by taking a minimum value point of the trend as a boundary so as to realize self-adaptive decomposition of the signal to obtain sub-bands of the signal. According to the method, the modal aliasing phenomenon is avoided, and it is ensured that excessive invalid components do not appear in the decomposition result. Besides, singular value decomposition is carried out on the signal sub-bands to obtain singular values of all the sub-bands, and then the singular values are selected by using amplitude filtering characteristics of singular value decomposition and combining a time domain negentropy index, so that noise reduction processing is realized. And carrying out envelope demodulation on the denoised sub-bands, extracting a fault characteristic frequency, and finally realizing fault diagnosis of the CNG compressor rolling bearing.

The invention discloses a method for generating electricity by means of low temperature exhaust heat of a power plant and relates to an unconventional electricity generating method. The problems of excessively large exhaust heat discharge and environment pollution caused by heat of a thermal power plant or a nuclear power plant are mainly solved, and the waste heat is converted to electric energy is achieved through exhaust heat electricity generation. Theoretically, the situation of nonreversible entropy production during energy cycle is solved, that is, the entropy production direction is changed, and negentropy is achieved. Water potential energy is increased through equipment with the upward flowing function; the potential energy is converted to kinetic energy through water fall, and a water turbine is driven to generate electricity; meanwhile, the upward-flowing equipment absorbs a large amount of heat, including low temperature heat, during upward flowing; rapid upward flowing of water can be achieved through a certain structure, and finally energy cycle is achieved. The electricity is generated in the process and supplied to people, a beneficial energy cycle of the nature can be achieved, that is, negentropy is achieved on the basis of thermodynamics entropy production, and the frequency of natural disasters on the earth can be reduced finally.

The invention provides a fault diagnosis method and system for a gearbox, and the method comprises the steps: dividing an original composite fault signal of the gearbox into different frequency bands through a 1 / 3 binary tree strategy, calculating the kurtosis values and singular value negentropies of different frequency bands, so as to define an SVN-Kurtosis diagram, and selecting an optimal frequency band from the SVN-Kurtosis diagram; acquiring filtering signals according to the center frequency and the bandwidth of the optimal frequency band, making multi-point kurtosis spectrum analysis on the filtering signals, and performing separation and extraction by an MOMEDA algorithm according to the fault period interval extracted from the multi-point kurtosis spectrum; and making fault feature enhanced analysis on the result of separation and extraction by adopting a composite cross-correlation spectrum. According to the fault diagnosis method and the diagnosis system, fault diagnosis can be better realized, and important information can be fully reserved.

The invention provides a microseism signal first arrival picking up method based on approximate negentropy, and belongs to the technical field of physical geography. The microseism signal first arrival picking up method based on approximate negentropy designs a suitable approximate negentropy function according to the characteristics of a microseism signal, and combines with a weighting function of the extremum difference of a negentropy-spectrum curve to set a threshold so as to realize accurate division of a signal area and a noise area and accurate pick-up of microseism signal first arrival. The microseism signal first arrival picking up method based on approximate negentropy has the advantages that according to the characteristics of the microseism signal, an approximate negentropy theory in the information theory is cited and a microseism signal first arrival picking up new method based on approximate negentropy is provided; compared with a current pick-up method, the new method can realize accurate pick-up of first arrival time in the lower signal to noise ratio condition and the signal to noise ratio can be as low as -12dB; and the calculating process is simple, and has high speed and high accuracy.

The invention discloses a negative entropy pump, which relates to the technical field of life and health equipment. The device is composed of a negative entropy source, a lifting platform and a reflection chamber. The negative entropy source includes a sealed box, a first gans body, and a second gans Body and nano coils, the GANS material of the present invention will automatically release the magnetic gravitational field as the prime mover to continuously provide energy, supplement negative entropy to the human body, and improve the life and health of the human body.

The invention discloses a DWT-SVD-ICA-based digital audio watermarking algorithm. The algorithm is performed according to the following steps: the first step, preprocessing is performed on an original audio signal, and a watermark is embedded in a selected appropriate segment; the second step, when the watermark is embedded, three-level wavelet conversion is performed on the original audio signal, singular value decomposition is performed on an approximate component of the wavelet conversion, and then watermark embedment is completed by utilizing a random mixing method; and the third step, when the watermark is extracted, wavelet conversion and singular value decomposition are performed on the audio signal embedded with the watermark, and then watermark blind detection is achieved by utilizing a negentropy maximization fixed point algorithm. Compared with a traditional ICA-based audio watermarking algorithm, the DWT-SVD-ICA-based digital audio watermarking algorithm is advantageous in that watermark robustness is improved to some extent, that is to say, the watermark robustness is high; and imperceptibility of the watermark can be guaranteed, and blind extraction of the watermark can also be guaranteed.

The invention discloses spontaneous illumination equipment and relates to a series of devices with the function of upward flowing under the condition that conventional energy consumption is absent. The situation of irreversible entropy production during energy cycle is mainly avoided, that is, negentropy is achieved, water potential energy is increased, the potential energy is converted into water flowing energy which then drives a water turbine to generate electricity, and electric energy is output after passing through a control system and an energy storing system and supplied to an illumination lamp for light emitting and illumination. The equipment comprises a device with the upward flowing function, a downward-flowing drain pipeline, a hydro-generator, an electrical control system, the illumination lamp and a water seepage and evaporation preventing closed system. The water potential energy of the whole system can be increased without conventional energy consumption, conversion from the potential energy to kinetic energy, conversion from the kinetic energy to the electric energy and conversion from the electric energy to visible radiation are achieved, spontaneous illumination is achieved, no extra energy source is consumed, that is, negentropy is achieved on the basis of thermodynamics entropy production, and the frequency of natural disasters on the earth can be reduced finally through the negentropy path.

The invention relates to a rotating machine fault diagnosis technology, in particular to a rotating machine abnormal vibration source identification method based on VT-ANM-SWT. The method comprises the steps of: obtaining vibration excitation source mixed signals of the surface of a rotating machine through a vibration acceleration sensor; performing independent component analysis on the vibration signals by using an optimized self-adaptive negentropy maximization blind source separation algorithm, and setting the number of results needing to be output by the algorithm according to the pre-estimated number of main vibration sources; and carrying out time-frequency analysis on each separated independent signal by using the SWT steady-state wavelet transform technology. Based on priori knowledge of a rotating machine, the method can effectively identify the vibration sources of the rotating machine, and can also effectively identify the abnormal vibration sources in abnormal operation. The method successfully solves the problem of abnormal vibration sources of a rotating machine, and provides a set of system for analysis of the problems in the future.

The invention provides a manufacturing method of an 'upward water flowing' energy circulator and relates to a device having an 'upward water flowing' function. Under the circumstance that no conventional energy consumption is produced, the problem that the entropy increase in the energy circulation process is irreversible is mainly solved in addition to the achievement of a function of 'enabling water to flow from a low position to a high position', namely negentropy and energy circulation are achieved. The device comprises an immersion body (1), a pipeline shell supporting body (2), in-pipeline capillary pipes (3) and a pipeline water outlet body (4), wherein the material for the in-pipeline capillary pipes (3) is a hydrophilic molecular material easily forming hydrogen bonds with H2O, and the pipeline water outlet body (4) is located at the upper-middle portion or the upper portion in a system. The device can achieve the 'upward water flowing' function, increases potential energy of water under the circumstance that no conventional energy consumption is produced, achieves beneficial energy circulation of the natural world, namely achieves the negentropy based on the aspect of thermodynamic entropy increase, and finally reduces frequently occurred natural disasters on the earth.

The invention discloses a negentropy instrument which comprises a battery pack, a negentropy separator and an electrode plate group, and the negentropy instrument can perform integral formatting recombination on a microstructure of a human body through a particle level so as to achieve an original health state of the human body. The composition can activate standby cells of a human body, repair damaged body cells, change the disordered state of entropy increase, enable the entropy increase of the human body to be ordered, and play roles in delaying senescence, keeping healthy and prolonging life.

The invention discloses an MIMO-EDM wireless communication system and method. The MIMO-EDM wireless communication system comprises a hybrid system and a separation system. Multiple-input multiple-output technology and MIMO technology are combined, and multiple paths of signals can be separated from entropy domains by using an entropy division multiplexing algorithm. The MIMO-EDM wireless communication method comprises the following processes: transmitting n paths of source signals; receiving the aliasing signals through a receiving end; and separating the multiple paths of aliasing signals through the separation system. According to the MIMO-EDM wireless communication system and method, the utilization rate of spectrum resources and the capacity of wireless channels are improved; negentropy is used as the criterion of statistical independence, and the separation of the multiple paths of aliasing signals is realized in the information entropy domains for the first time; and high-speed and high- quality broadband wireless communication is realized.

The invention provides a granular and tubular structure combined device with the function of making water flow upwards and relates to a series of devices with the function of making water flow upwards under the condition that no conventional energy is consumed. The device mainly solves the irreversible entropy increasing condition in the energy circulating process, namely, negentropy is achieved, potential energy of water is increased, and energy circulation is achieved. The device comprises an immersed body (1), a pipeline shell supporter (2), pipeline inner capillary pipelines (3) and a pipeline water outlet body (4). The pipeline inner capillary pipelines (3) are made from a hydrophilic molecular material capable of easily forming hydrogen bonds with H2O, and the pipeline water outlet body (4) is located on the upper middle portion or the upper portion of a system. The device can achieve the function of making water flow upwards, the potential energy of water is increased on the condition that no conventional energy is consumed, a useful energy cycle in the nature is achieved, that is, negentropy is achieved on the basis of the thermodynamic entropy increasing direction, and finally, frequent occurrence of natural disasters on the earth is reduced.