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Neural network-based helicopter gearbox health monitoring system 3

Neural network-based helicopter gearbox health monitoring sy...

引用

1993 3rd ieee-SP workshop on Neural Networks for signal processing, NNSP 1993

作者： Kazlas, P.T. Monsen, P.T. Leblanc, M.J. Sensor and Communication Electronics Division Charles Stark Draper Laboratory 555 Technology Square CambridgeMA02139 United States

ISBN: (纸本)0780309286

The results of two neural hardware implementations of a helicopter gearbox health monitoring system (HMS) are summarized. The first hybrid approach and implementation to fault diagnosis is outlined, and results are summarized using three levels of fault characterization: Fault detection (fault or no fault), classification (hear or bearing fault), and identification (fault sub-classes). Initial hardware results compare well with previously published software simulations. The second all-analog implementation exploits the ability of analog neural hardware to compute the discrete Fourier transform (DFT) as a preprocessor to a neural classifier. © 1993 ieee.

关键词： Fault detection

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Digitization of the Distribution Grid to Support e-Mobility Charging Infrastructure 3

Digitization of the Distribution Grid to Support e-Mobility ...

引用

3rd ieee International workshop on Metrology for Automotive (ieee MetroAutomotive)

作者： vom Boegel, Gerd Essingholt, Felix Bennertz, Bernhard Grenter, Thorben Fraunhofer IMS Busines Unit Ind Duisburg Germany Fraunhofer IMS Smart Sensor Syst Duisburg Germany Fraunhofer IMS Embedded Software & AI Duisburg Germany

ISBN: (纸本)9798350321876

The article addresses a subproject of the Energy ECS project [1], in which the development and realization of suitable components for condition monitoring of electrical distribution grids is carried out. By means of suitable sensor systems, communication and IT infrastructure components, relevant information on network infrastructure elements at neuralgic points is collected, aggregated and communicated. This information can be used directly for a highly dynamic grid-serving control of grid components to ensure a robust and efficient use of the distribution grid. The project makes a direct contribution to the digitization of distribution grids and thus contributes to the successful integration of decentralized generators and electromobility. The main objective of the subproject is the development and realization of energy-autonomous sensor systems for recording the status of relevant components of a low-voltage distribution network. The work to be carried out includes sensor principles as well as the field of energy harvesting or the field of sensor signal processing.

关键词： smart grid monitoring self-sufficient sensor LPWAN controlled charging infrastructure

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A Novel DOA Estimation Algorithm with Uncalibrated array

A Novel DOA Estimation Algorithm with Uncalibrated Array

引用

1996 3rd International Conference on signal processing(ICSP’96)

作者： Jia Yongkang Wu Huan Bao Zheng Institute of Electronic Engineering Xidian University

ISBN: (纸本)0780329120

A novel algorithm of DOA estimation with unknown sensor gain and phase error is presented in this *** is no need of error calibration for this *** sensors' gain and phase can be estimated after the estimation of *** application of this algorithm to linear array is also *** simulation results illustrate that this algorithm has a good performance in medium or higher SNR for array with serious gain and phase errors.

关键词： DOA A Novel DOA Estimation Algorithm with Uncalibrated array

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Parameters estimation using a random linear array and compressed sensing

Parameters estimation using a random linear array and compre...

引用

2010 3rd International Congress on Image and signal processing, CISP 2010

作者： Han, Kuoye Wang, Yanping Kou, Bo Hong, Wen National Key Laboratory of Microwave Imaging Technology Institute of Electronics Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781424465149

Existing sensor array signal processing techniques always use linear arrays sampled at Nyquist rate which demands the inter-element spacing is less than or equal to half of the system wavelength. Only in this way can algorithms such as MUSIC, Capon's beamformer estimate the direction-of-arrival (DOA) of the sources unambiguously. However, in some practical use, it seems difficult to satisfy the spatial sampling theorem. Compressed Sensing (CS) is a novel theory which enables perfect recovery of signals and data from what appear highly sub-Nyquist-rate samples on the condition that the signals or data are sparse or compressible in some domain. This implies that for spatially sparse signals, we can design a linear array with sparse property that will enable us to implement DOA estimates or even reconstruct the original signals accurately. In this paper, we proposed a parameters estimation method based on arrays with sub-Nyquist spatio-temporal sampling. We first sample the signals randomly in spatial domain, which means extracting a finite number of elements from a conventional uniform linear array. Then the signal in each channel is sampled by a random demodulator. By performing CS reconstruction algorithms, not only the DOAs can be estimated, but the original sources' waveforms will be recovered accurately. ©2010 ieee.

关键词： Compressed sensing

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Optimal sensor placement for damage detection

Optimal sensor placement for damage detection

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3rd European workshop on Structural Health Monitoring 2006

作者： Krawczuk, M. Kudela, R. Ostachowicz, W. Palacz, M. Zak, A. Polish Academy of Sciences IFFM Fiszera 14 80-231 Gdansk Poland Technical University of Gdansk Faculty of Electrical and Control Engineering Narutowicza 11/12 80-952 Gdansk Poland Gdynia Maritime University Faculty of Navigation Al. Zjednoczenia 3 81-345 Gdynia Poland

ISBN: (纸本)1932078630

In this study a damage identification approach has been developed for an aluminium plate with damage. A real time diagnostic system has been established Propagating Lamb waves have been introduced. The proposed technique uses distributed piezoelectric transducers to generate and monitor the wave changes due to damage occurrence. In presented approach the sensors have been deployed in arrays. Two different configurations have been tested. With proposed methodologies the sensor information has been combined with adequate signal processing in order to obtain a reliable damage location indication. Therefore a minimal number of sensors needed for proper damage location estimation has been established. The number of sensors needed is strongly connected with the proposed shape of sensor array.

关键词： Damage detection

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Beam Learning

Beam Learning

引用

ieee International Conference on Communications (ICC) / Wireless Communications Symposium / 3rd workshop on Optical Wireless Communications (OWC)

作者： Amuru, SaiDhiraj Samsung R&D Inst Bangalore Karnataka India

ISBN: (纸本)9781467389990

Beamforming is the key enabler for wireless communications in the mmWave bands. 802. 11 ad and WiGig are wireless technologies that currently use the 60GHz unlicensed mmWave spectrum via beamforming techniques. Given the widespread study and potential deployments of LTE in the 5GHz unlicensed band, it is likely that 5G systems will be considered for potential deployments in the 60GHz unlicensed spectrum (apart from other unlicensed bands). Therefore, 5G systems must coexist with 802. 11 ad and WiGig in this spectrum. The first step to achieve this co-existence is to find the directions in which the nodes using these incumbent technologies are communicating and eliminate those directions to avoid interference. In this paper, we use multi-armed bandits-based algorithms to blindly detect the beam directions (both along azimuth and elevation i.e., 3D-beamforming) used for communication by the incumbents. Numerical results show the superior performance of these algorithms over techniques that are commonly employed in such blind settings.

关键词： array signal processing signal processing algorithms Antenna arrays 5G mobile communication signal to noise ratio NIST ieee 802.11 Standard

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Selective signal Sample Forwarding for Receive Diversity in Energy-Constrained sensor Networks

Selective Signal Sample Forwarding for Receive Diversity in ...

引用

ieee International Conference on Communications (ICC) / Wireless Communications Symposium / 3rd workshop on Optical Wireless Communications (OWC)

作者： Nabeel, Muhammad Bloessl, Bastian Dressler, Falko Univ Paderborn Heinz Nixdorf Inst Paderborn Germany Univ Paderborn Dept Comp Sci Paderborn Germany

ISBN: (纸本)9781467389990

Receive diversity increases the reliability and robustness of ultra-low powerWireless sensor Networks (WSNs) by using spatially separated antennas without modifying the physical layer. We consider a distributed ground network in the wild to track bats in their natural habitat. The bats are equipped with a sensor node of only 2 g that limits the energy budget available for communication. In this work, we exploit the distributed nature of the ground network to employ diversity combining, i.e., we use the ground nodes as a geographically distributed multi-antenna array. However, this causes several research challenges given the limited bandwidth between nodes and the need for accurate synchronization to combine signal copies constructively at a central node. Sending all signal samples from all ground nodes to the central node is prohibitive due to the required data rates in the network. As a novel concept, we propose a system that only forwards selected signal samples belonging to a packet with high probability. We study the performance in simulations as well as in a testbed using a Software Defined Radio (SDR) prototype implementation. Our results clearly indicate a substantial performance gain while keeping the data rate in the ground network in a feasible range.

关键词： Diversity reception Receivers Diversity methods Mobile nodes Bandwidth Synchronization

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On-chip Pixel Reconstruction using Simple CNN for Sparsely Read CMOS Image sensor 3

On-chip Pixel Reconstruction using Simple CNN for Sparsely R...

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ieee 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)

作者： Kisku, Wilfred Kaur, Amandeep Mishra, Deepak Indian Inst Technol Dept Elect Engn Jodhpur Rajasthan India Indian Inst Technol Dept Comp Sci & Engn Jodhpur Rajasthan India

ISBN: (纸本)9781665419130

CMOS image sensors have gained popularity due to low power consumption, high speed and their ability to scale to smaller sizes. These factors can further be improved by either improving the circuitry of the imager or by enhancing the processing capabilities of the entire imaging system through on-chip processing of the pixel information. One such improvement is to read only a small fraction of the pixel array information and reconstruct the original information from it. The on-chip prediction of the unread pixels to reconstruct the acquired image is still an open problem. Here we propose a solution to the problem which relies on on-chip implementation of simple convolutional neural network (CNN) for pixel prediction and image reconstruction. The system strives to selectively read only a minimal number of pixels (10% to 15%), while skipping the rest. This attributes to a considerable saving on power and checks the issue of latency at the ADC. This selective process in reading of only few pixels generates a sparse image signal. The proposed network is trained to reconstruct the estimation of the actual image from the sparse set. The hardware accelerator that incorporates the CNN model also considers hardware limitations and constraints such as power consumption and latency. The PSNR achieved for the SiDCNet variant with SqueezeNet achieves for test images is similar to 30 dB for 85% of pixels skipped, and the quantized model does not lose much in PSNR.

关键词： Deep Learning Convolutional Neural Networks Compressed Sensing System On-Chip Image sensors

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BSS for improved interference estimation for Blind speech signal Extraction with two microphones

BSS for improved interference estimation for Blind speech si...

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ieee International workshop on Computational Advances in Multi-sensor Adaptive processing (CAMSAP)

作者： Yuanhang Zheng Klaus Reindl Walter Kellermann Multimedia Communications and Signal Processing University of Erlangen Nuremberg Erlangen Germany

ISBN: (纸本)9781424451791;9781424451807

Blind source extraction (BSE) as desirable for acoustic cocktail party scenarios requires estimates for the target or interfering signals. Conventional single-channel approaches for obtaining the interference estimate rely on noise and interference estimates during absence of the target signal. For multichannel approaches using multiple microphone signals, a separation of simultaneously active target and interference signals becomes possible if the positions of the target and interfering sources are known. We propose a new method which exploits directional BSS (blind source separation with a geometric constraint) to estimate the interfering speech sources and diffuse background noise jointly and blindly. Herewith we can effectively deal with the underdetermined BSS scenario (more point sources than sensors) in reverberant environments and can even allow for additional babble noise in the background.

关键词： Interference Microphones Source separation Speech enhancement Background noise sensor arrays MIMO signal processing Blind source separation array signal processing

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Image processing techniques for high speed camera-based free-field optical communication

Image processing techniques for high speed camera-based free...

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3rd ieee International Conference on signal and Image processing Applications (ICSIPA)

作者： Nava, Gabriel Pablo Kamamoto, Yutaka Sato, Takashi G. Shiraki, Yoshifumi Harada, Noboru Moriya, Takehiro NTT Corp NTT Commun Sci Labs Atsugi Kanagawa 2430198 Japan

ISBN: (纸本)9781479902699;9781479902675

Optical communication through light-emitting diodes (LEDs) and video cameras is rapidly gaining attention due to the increasing pervassiveness of those devices, and because of its potential data capacity. However, the communication quality is greatly compromised by the low resolution of the imaging sensor which produces blurred images of the LEDs at long distances. On the other hand, the images recorded at high frame rates possess particular features that can be used to improve the reception. This paper suggests image processing techniques to detect and decode the optical signals of an array of LEDs. For the case of blurred images, detection of the LED's is reinforced by a k-means clustering algorithm based on distance measurements derived from the linear correlation among pixel intensities along the time dimension. Experiments with a prototype show that the proposed algorithms can improve the bit error rate (BER) of the decoded signal. Furthermore, partial implementation on a General Purpose Graphics processing Unit (GPGPU) is also addressed, and processing times are demonstrated.

关键词： error statistics graphics processing units image processing light emitting diodes optical communication optical signal detection pattern clustering video cameras

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