87 results about "Mode mixing" patented technology

The invention provides a bearing fault classification diagnosis method based on sparse representation and an LDM (large margin distribution machine), overcomes the defects that signal decomposition is incomplete, a reconstructed signal cannot better keep features of an observed signal and the like in the conventional single-channel mechanical compound fault diagnosis method. According to the method, signal conversion from one dimension to high dimension is realized with a CEEMD (complete ensemble empirical mode decomposition) method, the decomposition completeness is guaranteed, and a mode mixing phenomenon is inhibited; meanwhile, a dimensionality reduction method based on sparse representation is introduced into a feature extracting and processing process of a blind source signal, data are subjected to sparse reconstruction through sparse representation, and data feature information is extracted from global data, so that the reconstructed signal can better keep the data features of the observed signal; further, the LDM classification method is introduced into a model fault type classification processing process of a to-be-detected bearing, and the accuracy and effectiveness of bearing fault diagnosis can be improved by aid of the generalization ability of the LDM classification method.

A signal processing method for performing hierarchical empirical mode decomposition (H-EMD) and an apparatus therefor are provided. In an embodiment, when empirical mode decomposition is performed on an input signal, an artificial assisting signal and the input signal are combined to assist the search for extrema and frequency reduction is performed in each iteration to eliminate the artificial assisting signal and make mode decomposition convergent so as to avoid mode mixing. In addition, in an embodiment, a hierarchical decomposition method is provided to decompose the input signal into a fewer number of fundamental modes. For needs in application, one of the fundamental modes can be further decomposed to produce a number of supplementary modes. In an embodiment, the H-EMD with appropriate frequency reduction can result in modes substantially independent of the form or the way of envelopes and can be applied to decompose multi-dimensional signals.

A perturbed, multimode optical fiber exhibits order-of-magnitude improved capacity attributed to mode mixing--high per-channel bit rate, and large channel number due to large available bandwidth--without the added loss which, in the past, was associated with the perturbation stream.

The invention discloses a micro-motion target characteristic extraction method based on the micro-Doppler effect. According to the micro-motion target characteristic extraction method based on the micro-Doppler effect, firstly, HHT is introduced into micro-motion target characteristic extraction, an HHT algorithm based on downsampling EMD is put forward for the problem of mode mixing of HHT characteristic extraction, noise-plus EMD is conducted on multi-set data obtained through downsampling of original signals, summation average is calculated, and therefore the problem of the pattern mode mixing in vibration target characteristic extraction of HHT is effectively solved. Noise of the original signals is restrained, signal to noise ratio is improved, the EMD arithmetic complexity of the multi-set data is reduced, arithmetic amount is greatly reduced, arithmetic speed is improved, and the better micro-Doppler characteristic extraction effect is achieved. The advantages of a traditional time-frequency analysis method and an improved HHT algorithm are combined, a micro-Doppler characteristic parameter extraction model based on improved HHT is put forward, and the resolution problem in a traditional time-frequency analysis spectrogram is improved due to the fact that a spectrogram peak value estimation method is added into the model. The micro-motion target characteristic extraction method based on the micro-Doppler effect is used as an auxiliary means for HHT characteristic extraction, and the requirement of improving accuracy and practicability of vibration target characteristic extraction is met.

The invention relates to an empirical mode decomposition-based improved harmonic analysis method. The analysis method includes the following steps that: a central processor sets a sampling period, performs real-time sampling and quantization on the signals of a power system so as to obtain original signals x [t]; empirical mode decomposition is performed on the original signals x [t], so that IMF modal components can be obtained, and HHT transform is performed on the IMF modal components, so that an instantaneous frequency graph can be obtained; frequency differences between the IMF modal components are calculated, and IMF modal components on which mode mixing begins to occur are found out; all IMF modal components before the occurrence of the mode mixing are removed from the original signals x [t]; spectrum analysis is performed on remaining signals, and frequency band filtering is performed on IMF modal components within double frequency; HHT transform is performed on the filtered IMF modal components, so that an instantaneous frequency and amplitude graph can be obtained. With the empirical mode decomposition-based improved harmonic analysis method of the invention adopted, different characteristics of the signals of the power system can be clearly differentiated from the HHT transform graphs, and an effective and rapid analysis mode can be provided for the harmonic analysis of the power system.

The invention discloses an express waybill competition management system and a method based on a third-party intelligent cloud platform. The system comprises a client, a manufacturing enterprise, a third-party logistics intelligent cloud platform, a courier and an express company. The third-party logistics intelligent cloud platform comprises a waybill competition subsystem, an on-passage tracking subsystem, an express service evaluation subsystem and a service conflict detection and processing subsystem. According to the invention, based on a mode mixing waybill competition and waybill sending, the timeliness of waybill competition and answering is achieved, and service quality is ensured, so compared with the traditional waybill sending mode, efficiency and comprehensive effects of logistics services are improved; based on the artificial immunology principle, a composite viewpoint service operation management model of a service conflict processing mechanism is established; different service conflict dynamic detection and solving methods are provided for different types of service conflicts; a problem of weak management and operation ability of intelligent cloud platform services is solved; and technical support is provided for normalized service management and operation.

A cooling system that provides cooling air for an operating space of a large scale information handling system (IHS) by using an air handling unit (AHU) configured to direct cooling air through the IHS. A controller is in communication with an ambient condition interface and the AHU to cause the cooling system to (i) detect the outside ambient condition; (ii) determine whether the outside ambient condition has first condition values that support use of normal cooling mode or second condition values that requires/triggers a hybrid cooling mode; and (iii) in response to determining that the outside ambient condition has the second condition values, perform a hybrid mode mixing of the outside air with recirculated air to moderate the outside air to more efficiently cool the IHS. The cooling system is thus responsive to current/detected conditions and provides an operational mode that yields highest cooling efficiency for the existing ambient condition/s.

The invention discloses a noncontact detecting based multi-target human respiratory signal monitoring method and device. The method comprises the following steps: 1) detecting a target area through a noncontact detecting system to obtain a target signal containing a multi-target human respiratory signal; 2) separating the obtained target signal based on a window averaging-empirical mode decomposition algorithm to obtain a plurality of mode components; 3) performing spectral analysis on each obtained mode component; screening to obtain human respiratory signals based on the spectral analysis result; recognizing each screen human respiratory signal to obtain respiratory signals corresponding to different target human bodies. The device comprises a signal detecting module, a WA-EMD signal separating module and a multi-target signal recognizing module. The method and the device have the advantages that the method is simple; the multi-target human respiratory signals can be effectively separated and monitored; the mode mixing resistance is high, and the noise resistance is high; in addition, the separating accuracy and the separating efficiency are high.

The invention discloses a mechanical fault diagnosis method and system based on TJM transfer learning. According to the method, CEEMDAN decomposition is introduced. The algorithm calculation amount isreduced while the mode mixing problem is solved, and meanwhile the problems that according to a traditional machine learning method, when training and testing data distribution has a certain degree of difference, the established classification model is poor in popularization capacity, and even sometimes the classification model cannot be universally used are solved through a transfer learning method. And meanwhile, the problem of low fault diagnosis efficiency caused by data difference between different working conditions of the rotary machine is solved, and the problems that the fault stateis incomplete and the fault diagnosis cannot be correctly and completely carried out due to insufficient data acquisition quantity of the rotary machine in some working states are also solved. According to the method, the characteristic that cross-domain feature matching and instance reweighting are jointly executed in the TJM transfer learning method is utilized, the problem that the recognitionand diagnosis rate is not high due to the fact that the data difference between the source domain and the target domain is large is solved to the maximum degree, and the fault diagnosis precision is greatly improved.

An optical receiver (20) for multimode communications comprises: a mode demultiplexer (21) having an input connected to a multimode link (22) and a plurality of output lines (231-234), wherein the mode demultiplexer is adapted to couple each of the modal components of the optical signal substantially into a selected one of the output lines, a plurality of coherent optical detectors (251-254) respectively connected to the output lines to produce a set of electrical digital signals each comprising an in-phase component and a quadrature-phase component, a plurality of independently adjustable optical delay devices (241-244) arranged on the output lines to impart a selected delay to each of the corresponding modal components, and a signal processing device (26) adapted to process the digital signals to recover the independent modulations of the respective modal components by inverting a mode-mixing characteristic of the multimode link.

The invention discloses a radio frequency feed-forward amplifier and a loop self-adaptive control method. The radio frequency feed-forward amplifier comprises a carrier compensation loop, an inter-modulation compensation loop and a chip controller, wherein the carrier compensation loop comprises an amplitude modulator, a phase modulator, a first gain equalizer, a main power amplifier, a delay line and a combiner; the inter-modulation compensation loop comprises a phase regulating circuit, a gain regulating circuit, a second gain equalizer, an error power amplifier, a delay filter and a receiver; the chip controller is used for monitoring the feedback power of the carrier compensation loop and the inter-modulation compensation loop, and self-adaptively regulating the amplitude, phase position and pilot frequency of a corresponding loop. According to the radio frequency feed-forward amplifier and the loop self-adaptive control method, the chip controller is used for monitoring and controlling the two loops, so that the radio frequency feed-forward amplifier is enabled to obtain the optimal compensation effect, rate of convergence and dynamic stability, and the features such as linearity, bandwidth and mode mixing are enabled to be better.

The invention relates to a high-pressure diaphragm pump check valve fault diagnosis method based on vibration signal analysis, and belongs to the field of mechanical fault diagnosis and signal processing. The high-pressure diaphragm pump check valve fault diagnosis method based on the vibration signal analysis comprises the following steps that firstly, VMD decomposition is carried out on a vibration signal of a check valve of a high-pressure diaphragm pump, and the number K of decomposition modes is determined through a center frequency to obtain K IMF components with physical significance; the MPE of the IMF components is then calculated to form a multi-scale complexity measure feature vector; and finally, a high-dimensional feature matrix is input into a classifier established by a support vector machine optimized based on a genetic algorithm to identify a working state of the check valve of the high-pressure diaphragm pump. According to the high-pressure diaphragm pump check valvefault diagnosis method based on the vibration signal analysis, the vibration signal of the check valve is denoised and decomposed into the IMF components without mode-mixing through a VMD algorithm, the multi-scale arrangement entropy of each IMF component is calculated to collect fault characteristic information distributed on multiple scales, the correct rate of fault identification of the checkvalve is improved, and higher practicability and engineering significance are achieved.

Methods and apparatus for coherent polarization mode dispersion generation are provided. A generator can include at least four birefringent stages. The birefringent stages are in optical series, and each includes a differential group delay (“DGD”) element. The intermediate stages' DGD elements are harmonic. Also, these intermediate stages each include a phase-shifting element. The generator can also include a polarization mode-mixing apparatus and a variable phase-shifting apparatus. The mode-mixing apparatus is capable of inducing polarization mode-mixing between at least one pair of adjacent stages to generate DGD and second order PMD independently at at least one optical frequency. The variable phase-shifting apparatus can include a phase-shifting controller coupled to each of said phase-shifting elements. A graphical user interface for PMD emulation, a PMD compensator for reducing PMD impairment, and calibration methods are also provided.

The invention discloses a denoising method based on hybrid EMD (Empirical Mode Decomposition), and belongs to the technical field of digital signal processing. According to the denoising method disclosed by the invention, EEMD (Ensemble Empirical Mode Decomposition) and MEMD (Multivariate Empirical Mode Decomposition) algorithms are combined, and aiming at a masking signal frequency used in the MEMD algorithm, parameter optimization is carried out, so that mode mixing can be more effectively eliminated, and a denoising effect is better; and according to the denoising method, targeted optimization is further carried on an additive noise amplitude in the EEMD, filtering thresholds of noise related IMF (Spurious modes) and filtering thresholds of noise IMF, so that an integral denoising effect is further improved. Compared with the prior art, the method disclosed by the invention can more effectively eliminate mode mixing, and has a better denoising effect.

The invention discloses a control system health state analysis method based on combined noise reduction and empirical mode decomposition (EMD). A combined noise reduction method combining median filtering, interscale dependency, and threshold value and threshold value function wavelet threshold value improvement is introduced, so that the control system state signals including pulse noises and Gaussian random noises can be effectively suppressed; and for the signals after nose reduction, a method combining end extension, ensemble empirical mode decomposition (EEMD), and correlation coefficient threshold value comparison is proposed, so that the problems of end effects and mode mixing during the signal feature extraction only by EMD in the prior art can be effectively solved. The method includes performing staging process on common state signals easy to be acquired by a control system; analyzing the energy entropy obtained through calculation to obtain effective state feature information at the end; comparing the state feature information with the energy entropy at the initial normal state and rapidly determining the health state of the control system in real time; and providing accurate criterion for fault diagnosis, on-condition maintenance, and fault tolerance control of the control system. The method is applicable to the feature extraction and health state real-time detection of high-precision control system noised state signals.

A polarization mode dispersion generator for generating polarization mode dispersion (“PMD”) spectra is provided. The generator includes a plurality of birefringent stages, each stage including a differential group delay (“DGD”) element and a phase-shifting element. The generator is capable of inducing an amount of polarization mode-mixing between at least one adjacent pair of stages. The shape of a PMD spectrum can be preserved while frequency shifting the spectrum in either direction. Alternatively, the shape of the PMD spectrum can be changed without frequency shifting.