Active Lamb-wave-based structural health monitoring techniques have been widely studied to inspect large structures using permanently installed arrays of sensors and actuators. Most of these methods ...depend on comparing baseline signals recorded from the structure before going into service and test signals acquired during inspection. Temperature changes affect the propagation of the wave in a nonlinear and mode-dependent manner. As a result, baseline comparison methods fail when the test and baseline signals are acquired at vastly different temperatures. Approximate methods that compensate for the effects of temperature on the waves using signal stretch models have been introduced in the literature. These methods are effective when the temperature changes are small and the propagation distances are short. However, they perform poorly when these conditions are not satisfied. Consequently, there is a need for better temperature compensation algorithms than presently available. This article presents a data-driven approach that separately compensates for the effects of temperature on different mode components of the sensor signals. The performance of the temperature compensation algorithm of this article is compared with that of a commonly used baseline signal stretch (BSS) algorithm using experimental signals measured from an aluminum panel and a unidirectional composite panel. Analysis results indicate that the method of this article outperforms the BSS algorithm for large temperature differences. The usefulness of the temperature compensation algorithm is further validated by demonstrating the ability of compensated signals to accurately reconstruct anomaly maps associated with damaged composite structures.
This paper presents a likelihood-based method for automatically identifying different quadrature amplitude modulations (QAM) and phase-shift keying (PSK) modulations. This algorithm selects the ...modulation type that maximizes a log-likelihood function based on the known probability distribution associated with the phase or amplitude of the received signals for the candidate modulation types. The approach of this paper does not need prior knowledge of carrier frequency or baud rate. Comparisons of theory and simulation demonstrate good agreement in the probability of successful modulation identification under different signal-to-noise ratios (SNRs). The probability of successful identification results in the simulation results show that under additive white Gaussian noise, the system can identify BPSK, QPSK, 8PSK, and QAMs of order 16, 32, 64, 128, and 256 above 99% accuracy at 4-dB SNR when the two other competing methods available in the literatures cannot for an input signal containing 10 000 symbols and 20 samples per symbol. The simulation results also indicate that when the input signal length decreases, the system needs higher SNRs in order to get accurate identification results. Finally, simulations under different noisy environments indicate that the algorithm is robust to variations of noise environments different from the assumed model in the derivations.
Inorganic metal halide perovskite nanocrystals (NCs) are promising materials for emission-based applications; however, the inclusion of toxic lead may limit their commercial viability. This paper ...describes two cesium cupriferous iodides as nontoxic alternatives to lead containing perovskites. These nanocrystals were synthesized with tailored composition and morphology by a hot-injection colloidal route to produce hexagonal nanoplates (NPs) of blue-emitting Cs3Cu2I5 and nanorods (NRs) of yellow-emitting CsCu2I3. Phase purity was confirmed by Rietveld refinement of X-ray powder diffraction patterns and solid state 133Cs MAS NMR with both compounds exhibiting high thermal stability suitable for optoelectronic technologies. Phase mixing allows linear tuning of Commission Internationale de l’Eclairage (CIE) coordinates from (0.145, 0.055) to (0.418, 0.541) such that a 1:8 molar ratio of Cs3Cu2I5 NPs and CsCu2I3 NRs yields white emission, while the 133Cs MAS NMR demonstrates that these photophysical effects are not attributed to any changes in the Cu oxidation state.
Lamb waves are characterized by their multimodal and dispersive propagation, which often complicates analysis. This paper presents a method for separation of the mode components and reflected ...components in sensor signals in an active structural health monitoring (SHM) system. The system is trained using linear chirp signals but works for arbitrary excitation signals. The training process employs the cross-Wigner-Ville distribution (xWVD) of the excitation signal and the sensor signal to separate the temporally overlapped modes in the time-frequency domain. The mode decomposition method uses a ridge extraction algorithm to separate each signal component in the time-frequency distribution. Once the individual modes are separated in the time-frequency domain, they are reconstructed in the time domain using the inverse xWVD operation. The propagation impulse response associated with each component can be directly estimated for chirp inputs. The estimated propagation impulse response can be used to separate the modes resulting from arbitrary excitation signals as long as their frequency components fall in the range of the chirp signal. The usefulness of the mode decomposition algorithm is demonstrated on a new health monitoring system for composite structures. This system performs anomaly imaging using the first arriving mode extracted from sensor array signals acquired from the structure. The anomaly maps are computed using a sparse tomographic reconstruction algorithm. The reconstructed map can locate anomalies on the structure and estimate their boundaries. Comparisons with methods that do not employ mode decomposition and/or sparse reconstruction techniques indicate a substantially better performance for the method of this paper.
This paper reviews technologies and signal processing algorithms for decoding peripheral nerve and electrocorticogram signals to interpret human intent and control prosthetic arms. The review ...includes a discussion of human motor system physiology and physiological signals that can be used to decode motor intent, electrode technology for acquiring neural data, and signal processing methods including decoders based on Kalman filtering and least-squares regressors. Representative results from human experiments demonstrate the progress that has been made in neural decoding and its potential for developing neuroprosthetic arms that act and feel like natural arms.
This paper presents a new method for unsharp masking for contrast enhancement of images. The approach employs an adaptive filter that controls the contribution of the sharpening path in such a way ...that contrast enhancement occurs in high detail areas and little or no image sharpening occurs in smooth areas.
Significance: The performance of traditional approaches to decoding movement intent from electromyograms (EMGs) and other biological signals commonly degrade over time. Furthermore, conventional ...algorithms for training neural network based decoders may not perform well outside the domain of the state transitions observed during training. The work presented in this paper mitigates both these problems, resulting in an approach that has the potential to substantially improve the quality of life of the people with limb loss. Objective: This paper presents and evaluates the performance of four decoding methods for volitional movement intent from intramuscular EMG signals. Methods: The decoders are trained using the dataset aggregation (DAgger) algorithm, in which the training dataset is augmented during each training iteration based on the decoded estimates from previous iterations. Four competing decoding methods, namely polynomial Kalman filters (KFs), multilayer perceptron (MLP) networks, convolutional neural networks (CNN), and long short-term memory (LSTM) networks, were developed. The performances of the four decoding methods were evaluated using EMG datasets recorded from two human volunteers with transradial amputation. Short-term analyses, in which the training and cross-validation data came from the same dataset, and long-term analyses, in which the training and testing were done in different datasets, were performed. Results: Short-term analyses of the decoders demonstrated that CNN and MLP decoders performed significantly better than KF and LSTM decoders, showing an improvement of up to 60% in the normalized mean-square decoding error in cross-validation tests. Long-term analyses indicated that the CNN, MLP, and LSTM decoders performed significantly better than a KF-based decoder at most analyzed cases of temporal separations (0-150 days) between the acquisition of the training and testing datasets. Conclusion: The short-term and long-term performances of MLP- and CNN-based decoders trained with DAgger demonstrated their potential to provide more accurate and naturalistic control of prosthetic hands than alternate approaches.
Significance: A number of movement intent decoders exist in the literature that typically differ in the algorithms used and the nature of the outputs generated. Each approach comes with its own ...advantages and disadvantages. Combining the estimates of multiple algorithms may have better performance than any of the individual methods. Objective: This paper presents and evaluates a shared controller framework for prosthetic limbs based on multiple decoders of volitional movement intent. Methods: An algorithm to combine multiple estimates to control the prosthesis is developed in this paper. The capabilities of the approach are validated using a system that combines a Kalman filter-based decoder with a multilayer perceptron classifier-based decoder. The shared controller's performance is validated in online experiments where a virtual limb is controlled in real-time by amputee and intact-arm subjects. During the testing phase subjects controlled a virtual hand in real time to move digits to instructed positions using either a Kalman filter decoder, a multilayer perceptron decoder, or a linear combination of the two. Results: The shared controller results in statistically significant improvements over the component decoders. Specifically, certain degrees of shared control result in increases in the time-in-target metric and decreases in unintended movements. Conclusion: The shared controller of this paper combines the good qualities of component decoders tested in this paper. Herein, combining a Kalman filter decoder with a classifier-based decoder inherits the flexibility of the Kalman filter decoder and the limited unwanted movements from the classifier-based decoder, resulting in a system that may be able to perform the tasks of everyday life more naturally and reliably.
Digital signal processing in modern hearing aids is typically performed in a subband or transform domain that introduces analysis-synthesis delays in the forward path. Long forward-path delays are ...not desirable because the processed sound combines with the unprocessed sound that arrives at the cochlea through the vent and changes the sound quality. Nonetheless, subband domain processing for digital hearing aids is the most popular choice for hearing aids because of the associated computational simplicity. In this paper, we present an alternative digital hearing aid structure with low-delay characteristics. The central idea in the paper is a low-delay spectral gain shaping method (SGSM) that employs parallel parametric equalization (EQ) filters. The low-delay SGSM provides frequency-dependent amplification for hearing loss compensation with low forward path delays and performs dynamic signal processing such as noise suppression and dynamic range compression. Parameters of the parametric EQ filters and associated gain values are selected using a least-squares approach to obtain the desired spectral response. The low-delay structure also employs an off-the-forward-path, frequency domain adaptive filter to perform acoustic feedback cancellation. Extensive MATLAB simulations and subjective evaluations of the results indicate that the method of this paper is competent with a state-of-the-art digital hearing aid system, but exhibits much smaller forward-path delays.
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