Frequency Domain Signal Processing Research Articles

Active Noise Cancellation using Online Wavelet Based Control System: Numerical and Experimental Study

Reaction wheels (RWs) used for attitude control of space vehicle systems usually encounter with undesired wide band noises. These noises which significantly affect the performance of regulator controller must tune the review or review rate of RWs. According to wide frequency band of noises in RWs the common approaches of noise cancellation cannot conveniently reduce the effects of the noise. Therefore, the advanced analyzer of frequency domain signal processing such as wavelets must be used to realize the noise cancellation. In this regards, only the online application of wavelets can be practical. In this paper, an online active noise canceller based on online wavelet theory is employed to omit the effects of undesired noise. In this way, dynamic identification of a RW as well as wavelet delay compensation are used simultaneously to design an active noise cancellation system. Numerical and experimental investigations of KNTU test setup as a hard ware in the loop system show the preferences of the proposed method of online noise cancellation.

Investigation and development of a high spectral resolution coherent optical spectrum analysis system.

Focusing on high resolution optical spectroscopy, a coherent optical spectrum analysis (COSA) system is investigated in this paper. Principle is built to demonstrate the operation of COSA and its signal processing in both time and frequency domain. According to COSA principle, resolution bandwidth (RBW) filters are found to have significant influence on power accuracy and spectral resolution of the optical spectrum analysis (OSA). Much effort is paid to design RBW filters, including center frequency, bandwidth and type of filters. Two RBW filters are optimized to reduce the power uncertainty of different spectral resolution and satisfy different signal under test. Then, simulations and experiments are conducted to verify COSA principle and results show that the power uncertainty is less than 0.5% and 1.2% for high and medium spectral resolution application, respectively. Finally, experiments on the OSA of actual spectra indicate that COSA system can achieve a 6 MHz spectral resolution and has an excellent capacity in analysis of fine spectrum structures.

Condition monitoring of helical gears using automated selection of features and sensors

Abstract The selection of most sensitive sensors and signal processing methods is essential process for the design of condition monitoring and intelligent fault diagnosis and prognostic systems. Normally, sensory data includes high level of noise and irrelevant or redundant information which makes the selection of the most sensitive sensor and signal processing method a difficult task. This paper introduces a new application of the Automated Sensor and Signal Processing Approach (ASPS), for the design of condition monitoring systems for developing an effective monitoring system for gearbox fault diagnosis. The approach is based on using Taguchi’s orthogonal arrays, combined with automated selection of sensory characteristic features, to provide economically effective and optimal selection of sensors and signal processing methods with reduced experimental work. Multi-sensory signals such as acoustic emission, vibration, speed and torque are collected from the gearbox test rig under different health and operating conditions. Time and frequency domain signal processing methods are utilised to assess the suggested approach. The experiments investigate a single stage gearbox system with three level of damage in a helical gear to evaluate the proposed approach. Two different classification models are employed using neural networks to evaluate the methodology. The results have shown that the suggested approach can be applied to the design of condition monitoring systems of gearbox monitoring without the need for implementing pattern recognition tools during the design phase; where the pattern recognition can be implemented as part of decision making for diagnostics. The suggested system has a wide range of applications including industrial machinery as well as wind turbines for renewable energy applications.

Optical Beacon Sensor for Small Unmanned Aerial System State Estimation

A new optical sensor system is presented that measures a reference vector direction relative to the body frame of a small unmanned aircraft system (sUAS) at medium ranges in daylight conditions with high precision and without drift using a low‐power, nonlaser, eye‐safe optical beacon. The beacon operates as a monochromatic, time‐modulated optical source, and the airborne sensor uses both optical band‐pass filtering and frequency domain signal processing to separate the beacon signal from reflected and scattered sunlight incident on the sensor's aperture, thus providing increased sensitivity. Characterization of the prototype sensor shows that the reference‐vector direction angles can be measured with an accuracy of better than 0.5% of the field of view, resulting in 0.1° accuracy over a 30 degree range, at a measurement update rate of 200 Hz. This result is based on an operating range of 134 m using a 1 W beacon with a 9° beamwidth. The prototype system was integrated into and tested on a small UAS. Flight test results are presented comparing the prototype sensor system's output to an estimate of the reference‐vector direction produced by fusing inertial measurement and GPS information, thus demonstrating how this sensor system offers a method of validating sUAS attitude estimation systems. The sensor system may also be used to augment sUAS attitude estimation systems, or for other purposes such as in a precision sUAS landing system or for state estimation in GPS‐denied environments.

Frequency domain signal processing with axial B-dot beam angle monitor

Frequency domain signal processing with axial B-dot beam angle monitor

Two algorithms of signal processing in frequency domain

Nonrecursive algorithms for processing of nonstationary signals in frequency domain and devices implementing these algorithms are proposed. It is shown that the computational complexity of the proposed algorithms is O(N).

Sequency Domain Signal Processing Using Complex Hadamard Transform

Signal processing can be performed in time domain as well as intransform domain. Frequency domain is perhaps the most widely used domain for transform domain signal processing. In this paper we analyze sequency domain (SD) signal processing as an alternate to the conventional frequency domain signal processing. We perform signal processing in sequency domain using conjugate-symmetric sequency-ordered complex Hadamard transform and compare the results with those of discrete Fourier transform. We observe that in comparison with frequency spectrum, spectral energy of sequency spectrum is spread over the entire spectrum. We performed signal and image denoising in SD and found that our designed SD filters effectively denoise the signals.

The Design of a Small GNSS Receiver with Enhanced Interference Suppression Capability for High Mobility

The applications of Global Navigation Satellite System (GNSS) receivers are becoming wider in various commercial and military systems including even small weapon systems such as artillery shells. The precision-guided munitions such as Small Diameter Bomb (SDB) of United States can be used for pinpoint strike by acquiring and tracking GNSS signals in high mobility situation. In this paper, a small GNSS receiver with embedded interference suppression capability working under high dynamic stress is developed which is applicable to the various weapon systems and can be used in other several harsh environments. It applies a kind of matched filter and multiple correlator schemes for fast signal acquisition and tracking of even weak signals and frequency domain signal processing method to eliminate the narrowband interference. To evaluate the performance of the developed GNSS receiver, the test scenario of high mobility and interference environment with the GNSS simulator and signal generator is devised. Then, the signal acquisition time, navigation accuracy, sensitivity, and interference suppression performances under high dynamic operation are evaluated. And the comparison test with the commercial GNSS receiver which has high sensitivity is made under the same test condition.

Study of Gabor Features and Heart Sound Signal Recognition by the Principal Component Analysis

Simple cells Gabor wavelet transform and human visual system in the visual stimulus response very similar. It has the good characteristics of the local space in the extraction of target and frequency domain information. Although the Gabor wavelet does not of itself constitute orthogonal basis, but in the specific parameters can form a tight frame. Gabor wavelet is sensitive to the image edge, can provide good direction and scale selection characteristics, but also insensitive to illumination changes, can provide the illumination change good adaptability. These features make Gabor wavelet is widely used in visual information understanding. The two-dimensional Gabor wavelet transform is an important tool for signal analysis and processing in frequency domain in, the coefficient of wavelet transform with the visual characteristics and good biology background, so it is widely used in image processing, pattern recognition and other fields.

Portable Roadside Sensors for Vehicle Counting, Classification, and Speed Measurement

This paper focuses on the development of a portable roadside magnetic sensor system for vehicle counting, classification, and speed measurement. The sensor system consists of wireless anisotropic magnetic devices that do not require to be embedded in the roadway-the devices are placed next to the roadway and measure traffic in the immediately adjacent lane. An algorithm based on a magnetic field model is proposed to make the system robust to the errors created by larger vehicles driving in the nonadjacent lane. These false calls cause an 8% error if uncorrected. The use of the proposed algorithm reduces this error to only 1%. Speed measurement is based on the calculation of the cross correlation between longitudinally spaced sensors. Fast computation of the cross correlation is enabled by using frequency-domain signal processing techniques. An algorithm for automatically correcting for any small misalignment of the sensors is utilized. A high-accuracy differential Global Positioning System is used as a reference to measure vehicle speeds to evaluate the accuracy of the speed measurement from the new sensor system. The results show that the maximum error of the speed estimates is less than 2.5% over the entire range of 5-27 m/s (11-60 mi/h). Vehicle classification is done based on the magnetic length and an estimate of the average vertical magnetic height of the vehicle. Vehicle length is estimated from the product of occupancy and estimated speed. The average vertical magnetic height is estimated using two magnetic sensors that are vertically spaced by 0.25 m. Finally, it is shown that the sensor system can be used to reliably count the number of right turns at an intersection, with an accuracy of 95%. The developed sensor system is compact, portable, wireless, and inexpensive. Data are presented from a large number of vehicles on a regular busy urban road in the Twin Cities, MN, USA.

Time and frequency domain analysis of wrist pulse signals for health diagnosis

Wrist pulse analysis is an approach of health diagnosis described in ancient Indian medicine. This approach is based on the analysis of three fingertip palpations observed over radial artery of both the hands. These three palpations identified as Vata, Pitta and Kapha in this approach are described by their unique characteristics. The characteristics of Vata and Pitta signals are explained by an irregularity present in the signal and the jumping or throbbing nature associated with the signal, respectively. In this paper, these wrist pulse signals are analysed in healthy and unhealthy subjects with the help of time and frequency domain signal processing techniques. Several pulse parameters are computed and their correlation is established with the corresponding pulse characteristics defined in ancient literature. These pulse parameters are also verified for their significant variations in healthy and unhealthy states of the subjects.

A Low-Complexity ECG Feature Extraction Algorithm for Mobile Healthcare Applications

This paper introduces a low-complexity algorithm for the extraction of the fiducial points from the Electrocardiogram (ECG). The application area we consider is that of remote cardiovascular monitoring, where continuous sensing and processing takes place in low-power, computationally constrained devices, thus the power consumption and complexity of the processing algorithms should remain at a minimum level. Under this context, we choose to employ the Discrete Wavelet Transform (DWT) with the Haar function being the mother wavelet, as our principal analysis method. From the modulus-maxima analysis on the DWT coefficients, an approximation of the ECG fiducial points is extracted. These initial findings are complimented with a refinement stage, based on the time-domain morphological properties of the ECG, which alleviates the decreased temporal resolution of the DWT. The resulting algorithm is a hybrid scheme of time and frequency domain signal processing. Feature extraction results from 27 ECG signals from QTDB, were tested against manual annotations and used to compare our approach against the state-of-the art ECG delineators. In addition, 450 signals from the 15-lead PTBDB are used to evaluate the obtained performance against the CSE tolerance limits. Our findings indicate that all but one CSE limits are satisfied. This level of performance combined with a complexity analysis, where the upper bound of the proposed algorithm, in terms of arithmetic operations, is calculated as 2:423N + 214 additions and 1:093N + 12 multiplications for N 861 or 2:553N + 102 additions and 1:093N +10 multiplications for N > 861 (N being the number of input samples), reveals that the proposed method achieves an ideal trade-off between computational complexity and performance, a key requirement in remote CVD monitoring systems.

Bilateral collicular interaction: Modulation of auditory signal processing in frequency domain

In the ascending auditory pathway, the inferior colliculus (IC) receives and integrates excitatory and inhibitory inputs from a variety of lower auditory nuclei, intrinsic projections within the IC, contralateral IC through the commissure of the IC and the auditory cortex. All these connections make the IC a major center for subcortical temporal and spectral integration of auditory information. In this study, we examine bilateral collicular interaction in the modulation of frequency-domain signal processing of mice using electrophysiological recording and focal electrical stimulation. Focal electrical stimulation of neurons in one IC produces widespread inhibition and focused facilitation of responses of neurons in the other IC. This bilateral collicular interaction decreases the response magnitude and lengthens the response latency of inhibited IC neurons but produces an opposite effect on the response of facilitated IC neurons. In the frequency domain, the focal electrical stimulation of one IC sharpens or expands the frequency tuning curves (FTCs) of neurons in the other IC to improve frequency sensitivity and the frequency response range. The focal electrical stimulation also produces a shift in the best frequency (BF) of modulated IC (ICMdu) neurons toward that of electrically stimulated IC (ICES) neurons. The degree of bilateral collicular interaction is dependent upon the difference in the BF between the ICES neurons and ICMdu neurons. These data suggest that bilateral collicular interaction is a part of dynamic acoustic signal processing that adjusts and improves signal processing as well as reorganizes collicular representation of signal parameters according to the acoustic experience.

Distributed antenna network for gigabit wireless access

For gigabit wireless data services, there are three important technical issues to be addressed: limited bandwidth, severe frequency-selective fading, and limited transmit power. A distributed antenna network (DAN) is a promising solution to the above three technical issues. In DAN, each mobile user is served by using multiple distributed antennas close to it. In this paper, recent advances in various distributed multi-input/multi-output (MIMO) techniques combined with single-carrier (SC) frequency-domain signal processing are presented for DAN. Particular attention is paid to SC frequency-domain MIMO diversity, relay, beamforming, and multiplexing jointly used with frequency-domain equalization (FDE) to significantly improve the signal transmission performance.

Distributed Sensing at Centimeter-Scale Spatial Resolution by BOFDA: Measurements and Signal Processing

In this paper, we demonstrate high spatial (≈3 cm) and spectral (≈30 MHz) resolution Brillouin sensing by use of Brillouin optical frequency-domain analysis (BOFDA) and signal processing. An iterative method is employed to correct the acquired data from spurious effects associated to acoustic wave modulation and relevant in the high spatial resolution regime. Experimental tests demonstrate that the proposed algorithm allows to reconstruct the Brillouin shift profile with the full spatial resolution allowed by the system bandwidth.

A multifunctional integrated silicon tactile imager with arrays of strain and temperature sensors on single crystal silicon diaphragm

In this study, a silicon multifunctional tactile imager with the simultaneous detection abilities of ‘3D surface shape’ and ‘temperature distribution’ of touching object has been realized with silicon LSI/MEMS technology. The pixel circuit array including a piezoresistor and a temperature sensor is integrated on elastic surface of pneumatically swollen silicon diaphragm. Also, elasticity detection of touching object has been simultaneously realized with signal processing in frequency domain. Prototype tactile imagers with a 3.1 mm × 3.1 mm sensor diaphragm integrating 420-μm pitch multifunctional sensor pixel array have been fabricated. In the evaluation experiments, the shape of a 1.5 mmϕ soft tube was successfully detected. Also, simultaneous measurement of surface shape and temperature distribution was performed using a heated metal pipe. The detectable lower-limit of vibration in this tactile imager was below 1.0 μm with signal bandwidth more than 2 kHz. Using the ability of vibration detection, the three kinds of materials with different elasticity (0.59–7.04 mN/μm) were successfully distinguished with the tactile imager. The highly sensitive and multifunctional tactile imager with versatile detection ability has been realized by sophisticated integration ability of silicon-MEMS technology.

Eulerian laser Doppler vibrometry: Online blade damage identification on a multi-blade test rotor

Laser Doppler vibrometry enables the telemetry-free measurement of online turbomachinery blade vibration. Specifically, the Eulerian or fixed reference frame implementation of laser vibrometry provides a practical solution to the condition monitoring of rotating blades. The short data samples that are characteristic of this measurement approach do however negate the use of traditional frequency domain signal processing techniques. It is therefore necessary to employ techniques such as time domain analysis and non-harmonic Fourier analysis to obtain useful information from the blade vibration signatures. The latter analysis technique allows the calculation of phase angle trends which can be used as indicators of blade health deterioration, as has been shown in previous work for a single-blade rotor. This article presents the results from tests conducted on a five-blade axial-flow test rotor at different rotor speeds and measurement positions. With the aid of artificial neural networks, it is demonstrated that the parameters obtained from non-harmonic Fourier analysis and time domain signal processing on Eulerian laser Doppler vibrometry signals can successfully be used to identify and quantify blade damage from among healthy blades. It is also shown that the natural frequencies of individual blades can be approximated from the Eulerian signatures recorded during rotor run-up and run-down.

Remote Monitoring of Industrial Systems Health

A low cost platform is proposed for remote monitoring the health status of an industrial system. The key elements of this platform are: a measurement system, a communication system and a data processing system responsible for analyzing data and estimating the status of the equipments placed in remote locations. Wired and wireless sensors are developed for collecting vibration, acceleration, current and temperature values that characterize the operation of remote industrial equipment. A “plug and play„ software application is implemented for allowing remote computers to share this sensor data using OPC technology. Using Matlab as an OPC client, time-domain and frequency-domain signal processing techniques are used in order to determine the signatures associated with faults of the remote equipments.

A TR-UWB Downconversion Autocorrelation Receiver for Wireless Body Area Network

Low power UWB receiver architecture is proposed for a Wireless Body Area Network (WBAN). This receiving technology is a synergy of existing downconversion-based narrowband rejection mechanism in RF front end and signal processing in frequency domain. Frequency components of converted and filtered UWB pulses are separated into real and imaginary parts, independently correlated and effectively combined to achieve an improved output Signal to noise ratio (SNR). An extensive mathematical analysis has been performed to formulate the close-form expressions for SNRs in order to compare system performances toward favorable BER under BPSK modulation scheme. Analysis shows that optimal rotation of coordination plays an important role for the enhancement of receiving SNR which is further confirmed by computer simulation. A wide range of link level simulation (LLS) urges that the proposed system is more power efficient in higher-order modulation (HOM) schemes. Transmitted Reference (TR) scheme has been considered as the basis for wideband communication.

Frequency-domain photothermoacoustics: Alternative imaging modality of biological tissues

Frequency-domain photothermoacoustic (FD-PTA) imaging of biological tissues is presented and compared with the conventional time-domain methodology. We demonstrate that tissue imaging can be performed with high axial resolution without the necessity to employ short-pulse and high peak-power laser systems to generate acoustic transients. The presented analysis shows that depth information in the FD-PTA method can be recovered by using linear frequency-modulated (chirped) optical excitation and frequency-domain signal processing algorithms. The signal-to-noise ratio can be increased significantly using correlation processing, which can compensate for the small amplitude of acoustic waves typical to the periodic excitation mode. Additionally, narrow-band signal demodulation enables depth-specific and confocal tissue imaging using the optically induced photothermoacoustic effect. Application of the FD-PTA is demonstrated in experiments with turbid phantoms and ex vivo tissue specimens.