Adaptive frequency domain identification for ANC systems using non-stationary signals

The problem of identification of secondary path in active noise control applications is dealt with fundamentally using time-domain adaptive filters. The use of adaptive frequency domain subband identification as an alternative has some significant advantages which are overlooked in such applications. In this paper two different delayless subband adaptive algorithms for identification of an unknown secondary path in an ANC framework are utilized and compared. Despite of reduced computational complexity and increase convergence rate this approach allows us to use non-stationary audio signals as the excitation input to avoid injection of annoying white noise. For this purpose two non-stationary music and speech signals are used for identification. The performances of the algorithms are measured in terms of minimum mean square error and convergence speed. The results are also compared to a fullband algorithm for the same scenario. The proposed delayless algorithms have a closed loop structure with DFT filterbanks as the analysis filter. To eliminate the delay in the signal path two different weights transformation schemes are compared

A single antenna ambient noise cancellation method for in-situ radiated EMI measurements in the time-domain

This paper presents a single antenna ambient noise cancellation method for in-situ radiated emissions measurements performed using an entirely time-domain approach and the sliding window Empirical Mode Decomposition. The method requires a pair of successive measurements, an initial one for characterizing the ambient noise and a final one for the EMI measurement in the presence of ambient noise. The method assumes the spectral content of the ambient noise is stable between both measurements. The measured time-domain EMI is decomposed into a finite set of intrinsic mode functions. Some modes contain the ambient noise signals while other modes contain the actual components of the EMI. A brute-force search algorithm determines which mode, or combination of modes, maximize the absolute difference between the magnitude of their spectrum and the ambient noise levels for every frequency bin in the measurement bandwidth. Experimental results show the effectiveness of this method for attenuating several ambient noise signals in the 30 MHz – 1 GHz band.Postprint (published version

Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory

A comparative study of the effectiveness of vibration and acoustic emission in diagnosing a defective bearing in a planetry gearbox

Whilst vibration analysis of planetary gearbox faults is relatively well established, the application of Acoustic Emission (AE) to this field is still in its infancy. For planetary-type gearboxes it is more challenging to diagnose bearing faults due to the dynamically changing transmission paths which contribute to masking the vibration signature of interest. The present study is aimed to reduce the effect of background noise whilst extracting the fault feature from AE and vibration signatures. This has been achieved through developing of internal AE sensor for helicopter transmission system. In addition, series of signal processing procedure has been developed to improved detection of incipient damage. Three signal processing techniques including an adaptive filter, spectral kurtosis and envelope analysis, were applied to AE and vibration data acquired from a simplified planetary gearbox test rig with a seeded bearing defect. The results show that AE identified the defect earlier than vibration analysis irrespective of the tortuous transmission pat

Radio Frequency Interference Mitigation

Radio astronomy observational facilities are under constant upgradation and development to achieve better capabilities including increasing the time and frequency resolutions of the recorded data, and increasing the receiving and recording bandwidth. As only a limited spectrum resource has been allocated to radio astronomy by the International Telecommunication Union, this results in the radio observational instrumentation being inevitably exposed to undesirable radio frequency interference (RFI) signals which originate mainly from terrestrial human activity and are becoming stronger with time. RFIs degrade the quality of astronomical data and even lead to data loss. The impact of RFIs on scientific outcome is becoming progressively difficult to manage. In this article, we motivate the requirement for RFI mitigation, and review the RFI characteristics, mitigation techniques and strategies. Mitigation strategies adopted at some representative observatories, telescopes and arrays are also introduced. We also discuss and present advantages and shortcomings of the four classes of RFI mitigation strategies, applicable at the connected causal stages: preventive, pre-detection, pre-correlation and post-correlation. The proper identification and flagging of RFI is key to the reduction of data loss and improvement in data quality, and is also the ultimate goal of developing RFI mitigation techniques. This can be achieved through a strategy involving a combination of the discussed techniques in stages. Recent advances in high speed digital signal processing and high performance computing allow for performing RFI excision of large data volumes generated from large telescopes or arrays in both real time and offline modes, aiding the proposed strategy.Comment: 26 pages, 10 figures, Chinese version accepted for publication in Acta Astronomica Sinica; English version to appear in Chinese Astronomy and Astrophysic