10 results about "FastICA" patented technology

The invention discloses an automatic detection method for dynamic balance parameters of an automobile hub, and the method comprises the steps: employing a piezoelectric ceramic array self-sensing main shaft technology, enabling detection reference establishment and signal collection to be integrated in a main shaft body, and carrying out the fusion of a hub installation process and a detection reference establishment process; synchronous acquisition of multi-dimensional vibration signals is carried out; an original mixed signal is decomposed into modal components in a self-adaptive mode, and environmental vibration interference is eliminated; a FastICA-RLS hybrid algorithm is adopted to separate an independent source signal from the preliminarily purified signal, and non-stationary interference is tracked and compensated in real time; constructing a flexible rotor model based on modal parameter identification, and calculating an unbalance amount; self-adaptive Kalman filtering error compensation and prediction are carried out, and the amount of unbalance after compensation is output; and an optimal counterweight scheme is automatically calculated based on the compensated unbalance amount, and visual display and guidance are performed through a human-computer interface, so that the detection precision and the detection efficiency are improved.

The invention discloses a graph signal blind source separation method in a white noise environment, and belongs to the technical field of signal processing. Aiming at the problem that the traditional blind source separation performance is reduced due to additive white noise, the invention provides a joint optimization scheme combining blind compression nonlinear noise suppression and image smoothing regularization. Firstly, a blind compression function is applied to a noisy observation image signal for preprocessing; secondly, carrying out mean value removal and whitening processing on the compressed signal; then, constructing a graph Laplacian matrix as a smoothing operator, establishing a joint diagonalization objective function fusing graph autocorrelation, a FastICA item and a graph smoothing regular item, and adopting a Givens rotation algorithm to iteratively optimize and solve a separation matrix; and finally, reconstructing a source signal through multiplication of the separation matrix and the whitening data. According to the method, noise interference is effectively suppressed through blind compression, signal structure consistency is maintained by using graph smoothing prior, and separation robustness, precision and convergence stability in a strong noise environment are remarkably improved.

The application particularly relates to a radar main lobe interference suppression method based on direction constraint, which realizes suppression of interference and separation of target echo in a main lobe suppression type interference scene by embedding array manifold vectors into FastICA fixed point iteration and applying direction constraint to the separation vectors after each update so that the separation vectors are always focused on a target angle subspace.

The application discloses a kind of sensor fault detection method and device of structural health monitoring system, it is related to structural health monitoring technical field, comprising: obtaining the nonlinear structure monitoring data of sensor system collected by structural health monitoring system, nonlinear structure monitoring data is handled using improved geometric PNL hybrid model, obtain linear to-be-separated mixed signal, using FastICA model to process to-be-separated mixed signal, obtain multiple independent elements, determine the separation matrix of improved geometric post-nonlinear independent component analysis model according to multiple independent elements, using the processing of improved geometric post-nonlinear independent component analysis to real-time collection nonlinear structure monitoring data, determine whether sensor system exists fault and the sensor of fault occurrence.The method can still complete linearization processing to sensor mixed signal under the condition that prior knowledge is unknown, compared with simple linear ICA analysis algorithm, it is more suitable for complex nonlinear structure.

The invention relates to the technical field of power system equipment fault diagnosis, in particular to a transformer substation GIS equipment partial discharge fault type identification method considering environmental interference compensation. The method comprises the steps of multi-source multi-mode signal acquisition, hybrid interference decoupling and preprocessing, physical information fusion dynamic interference compensation, fusion feature extraction, interpretable feature optimization and fault identification, and cloud edge collaborative closed-loop update full-process optimization, multi-mode signals are synchronously acquired through FPGA + edge nodes, and through preprocessing such as improved FastICA decoupling and db4 wavelet denoising, the cloud edge collaborative closed-loop update is obtained. The method comprises the following steps: constructing a fusion feature vector, carrying out dynamic compensation by using a random forest model, extracting 16-dimensional traditional features and 8-dimensional deep learning features, carrying out fusion, carrying out SHAP value analysis and genetic algorithm optimization, inputting into a transfer learning-PSO-ELM model for identification, and carrying out cloud edge collaboration to realize model updating. And the compensation signal distortion degree, the fault identification accuracy, the small sample generalization ability and the continuous operation accuracy are greatly improved.

Disclose a multiscale retinex and FASTICA combined infrared thermal image processing method, including the following steps: laser infrared thermal imaging; FASTICA image processing; multiscale Retinex image noise reduction; signal-to-noise ratio calculation.The FASTICA infrared thermal image processing method based on Retinex can enhance the infrared thermal image to display the key information of the image, and the effect of laser infrared nondestructive testing has obvious visual improvement, and other types of image optimization processing can also be carried out by this method.

The present application relates to the technical field of machining process parameter optimization, and particularly relates to a surface quality dynamic optimization method for camshaft non-circular contour high-speed grinding; the method comprises the following steps: collecting multi-source mixed signals in the camshaft non-circular contour high-speed grinding process; separating out source signal components corresponding to the grinding process state by using a signal processing method based on WPD-EWT-FastICA; selecting a high-correlation feature set with high correlation with the grinding process state by using ReliefF; dividing state labels; training a recognition model based on CNN-LSTM-Attention; acquiring real-time multi-source mixed signals during processing, and outputting real-time grinding process states; triggering a dynamic response mechanism, updating a multi-objective optimization function, and acquiring an optimal process parameter combination; the method can adaptively adjust the optimal process parameter combination in real time, and dynamically optimize surface roughness, residual stress and material removal rate.

The invention relates to an acoustic feature enhancement method and device based on blind source separation and two-stage filtering and a medium, and the method comprises the steps: carrying out the FastICA blind source separation of a collected acoustic signal, and obtaining a plurality of separated sub-signals; the amplitude and the phase of each obtained sub-signal are corrected; the corrected sub-signals are screened through the energy ratio, and effective source signals are obtained; and filtering the effective source signal by adopting a self-adaptive two-stage filtering mode to obtain a target source signal. According to the invention, the target source signal can be effectively separated, the background noise is reduced, and the acoustic characteristics are obviously enhanced, thereby improving the effectiveness of acoustic fault recognition.

This invention belongs to the field of online detection technology for metal impurities in food, and particularly relates to an intelligent sensing-based online detection method and system for metal impurities in food. It simultaneously transmits and receives multiple discrete frequency band electromagnetic signals, generating a multi-dimensional original signal matrix by leveraging the differences in their responses to metals, food, packaging, and the environment. Based on the fusion application of an improved FastICA blind source separation algorithm and wavelet packet transform, a multi-frequency feature-blind source separation dual-layer model is constructed. The effectiveness of signal separation is verified using a multi-scenario standard signal feature library and cosine similarity matching. After feature extraction and combined dimensionality reduction processing, the output is fused through a hybrid model of traditional machine learning and lightweight deep learning. The D-S evidence theory is introduced and combined with real-time parameters from the production line to dynamically adjust the decision rules.

This invention discloses a single-channel mixed signal demodulation method based on oversampling. First, the mixed signal of BPSK and 16QAM signals received in a PCMA communication system is processed to construct a multi-channel blind source separation model. The signal from the multi-channel blind source separation model is then centered and whitened to reduce the computational cost of FastICA. Then, FastICA is used to extract independent components. Finally, based on the obtained independent components, a phase-locked loop is used to extract baseband information to obtain the baseband signal. This invention effectively solves the problem of high bit error rate after separating and demodulating mixed signals in a single-channel environment. This invention utilizes the orthogonality of carriers, which further improves the demodulation performance of single-channel mixed signals when the sampling factor is increased. Compared with time-domain filtering methods, frequency-domain notch filtering methods, empirical mode decomposition methods, and wavelet decomposition methods, this method has better demodulation performance and a lower bit error rate.