Time-domain Signal Processing Research Articles

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.

The surprising sample covariance matrix: Unexpected characteristics and understanding them

The Sample Covariance Matrix (SCM) is important to many problems in acoustic signal processing in both time-domain and frequency-domain processing. However, some careful analysis suggests that the SCM contains a variety of surprises. For instance, not all elements of the SCM have the same error—the error of a particular element depends on the location of the element in the matrix and is different for SCMs of real-valued processes and complex-valued processes. Moreover, when the samples of the process used to compute the SCM are correlated, the sample covariance matrix behaves differently yet again. In particular, for frequency-domain sample covariance matrices, which are common in underwater acoustic communication and sonar signal processing, the SCM obtained using a tapped delay line is a better estimate of the covariance matrix than that obtained using independent samples—a most counterintuitive result. In this talk, we present a unified analysis technique using ergodic theory that predicts a variety of unexpected characteristics of the SCM, and explain the reasons behind some of them. Given the wide variety of algorithms that rely on the SCM, understanding this behavior is crucial to designing robust and accurate algorithms.

A home sleep apnea screening device with time-domain signal processing and autonomous scoring capability.

Current solutions of sleep apnea diagnosis require the patient to undergo overnight studies at a specialized sleep laboratory. Due to such inconvenience and high cost, millions of sleep apnea patients remain undiagnosed and thus untreated. Based on a micro-electro-mechanical systems (MEMS) sensor and an effective apnea detection algorithm, we propose a low-cost single-channel apnea screening solution applicable in the comfort of patients' homes. A prototype device was designed and assembled including a MEMS sensor for measuring the patient's nasal air flows, and a time-domain signal processing IC for apnea detection and autonomous scoring. The IC chip was fabricated in standard 0.5- μm CMOS technology. The proposed device was tested for both respiratory rhythm detection and sleep apnea screening under clinical environment. Apnea-hypopnea indices (AHI) were scored to indicate severity of sleep apnea conditions. Test results suggest that the proposed device can be a valuable screening solution for the broader public with undiagnosed apnea conditions.

Smart power management algorithm in microgrid consisting of photovoltaic, diesel, and battery storage plants considering variations in sunlight, temperature, and load

Integration of utility scaled solar electricity generator into power networks can negatively affect the performance of next generation smartgrid. Rapidly changing output power of this kind is unpredictable and thus one solution is to mitigate it by short-term to mid-term electrical storage systems like battery. The main objective of this paper is to propose a power management system (PMS) which is capable of suppressing these adverse impacts on the main supply. A smart microgrid (MG) including diesel, battery storage, and solar plants has been suggested for this purpose. MG is able to supply its local load based on operator decision and decline the power oscillations caused by solar system together with variable loads. A guideline algorithm is also proposed which helps to precisely design the battery plant. A novel application of time domain signal processing approach to filter oscillating output power of the solar plant is presented as well. In this case, a power smoothing index (PSI) is formulated, which considers both load and generation, and used to dispatch the battery plant. A droop reference estimator to schedule generation is also introduced where diesel plant can share the local load with grid. A current control algorithm is designed as well which adjusts for PSI to ensure battery current magnitude is allowable. MG along with its communication platform and PMS are simulated using PSCAD software. PMS is tested under different scenarios using real load profiles and environmental data in Malaysia to verify the operational abilities of proposed MG. The results indicate that PMS can effectively control the MG satisfying both operator and demand sides.

Determination of Cellulose Crystallinity by Terahertz-Time Domain Spectroscopy

Terahertz-time domain spectroscopy (THz-TDS) has the ability to probe the crystallinity of several materials, due to the interaction of THz radiation with optical phonons in crystal lattices. In this work, THz-TDS has been used to quantify the degree of crystallinity of microcrystalline cellulose (MCC) samples. The THz spectra of cellulose present absorption features which could be directly correlated with the crystallinity index (CI) obtained by means of the well-established powder X-ray diffraction (PXRD) technique. The effect of THz time-domain signal processing was investigated, and both univariate and multivariate, based on partial least-squares (PLS), regressions were carried out with the signal in the frequency domain to correlate the THz spectra with CI. Results show that the multivariate regression models based on spectral data, collected with the sample displaced from the focal plane of the THz optics to improve representativeness and measurement repeatability, present the best performance with external validation achieving an absolute root-mean-square error of prediction (RMSEP) of 4% for CI. This result compares well with the PXRD technique.

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.

Enhanced Electro-Optic Modulation Performance in Optical Buffers by Slowing Light in Optimized Photonic Crystal Slab Structures

Slow light holds the key to advanced optical bu ering and time-domain optical signal processing technologies. Photonic crystal based optical bu ers are particularly attractive due to their nanoscale size, room temperature operation, and enhanced eld dependent nonlinear response associated with the presence of slow light. In this study, the slow light and electro-optic modulation characteristics of a line-defect Si photonic crystal slab with triangular arrangement of holes lled with an electro-optic polymer (n = 1.6) are investigated by three-dimensional plane-wave expansion and nite-di erence time-domain methods. The rst rows adjacent to the line-defect are shifted gradually in the direction of light propagation and a slow light region with a high group index below the light-line is obtained for a shifting amount between 0.22a and 0.27a. For the photonic crystal con guration with 0.22a shifted rows, under modulated voltage change, the average group index is found to be decreasing with an increase in the bandwidth. The results show that the low group velocity supports a large delay time in a small modulated voltage variation. A linear change of group index with modulated voltage is obtained and the modulation sensitivity of central wavelength is obtained as 9.45 nm/V for a delay line length of 0.5 mm. Almost the same bu er capacity and bit length are found which provides the control of delay time exibly while keeping the bu er capacity and the bit length almost unchanged.

Time Domain Bearing Diagnosis Using Kurtosis Based Filtering and Fuzzy Logic

On this paper a bearing defects diagnosis method is introduced. This diagnosis method is based on time domain signal processing first step being the kurtosis based filtering. This filtering is based on the detection of the shock pulses generated by bearing defects. The diagnosis is done using the detected defects periods which are the inputs for a fuzzy classifier that provide defect alerts for each kind of bearing localize defect

Physical Layer Design in Wireless Sensor Networks for Fading Mitigation

This paper presents the theoretical analysis, simulation results and suggests design in digital technology of a physical layer for wireless sensor networks. The proposed design is able to mitigate fading inside communication channel. To mitigate fading the chip interleaving technique is proposed. For the proposed theoretical model of physical layer, a rigorous mathematical analysis is conducted, where all signals are presented and processed in discrete time domain form which is suitable for further direct processing necessary for devices design in digital technology. Three different channels are used to investigate characteristics of the physical layer: additive white Gaussian noise channel (AWGN), AWG noise and flat fading channel and AWG noise and flat fading channel with interleaver and deinterleaver blocks in the receiver and transmitter respectively. Firstly, the mathematical model of communication system representing physical layer is developed based on the discrete time domain signal representation and processing. In the existing theory, these signals and their processing are represented in continuous time form, which is not suitable for direct implementation in digital technology. Secondly, the expressions for the probability of chip, symbol and bit error are derived. Thirdly, the communication system simulators are developed in MATLAB. The simulation results confirmed theoretical findings.

A New Approach for Chatter Prediction in Robotic Milling Based on Signal Processing in Time Domain

Robotic machining is an attractive, cost-effective, and flexible alternative for basic machining applications. Having these characteristics, industrial robots are assumed to be the next generation of machine tools. But, due to weaker structure of robotic manipulators in comparison to conventional CNC machines, robotic machining processes are more subject to unwanted detrimental vibrations. At this work, simulations are realized in Time-Domain using the linearized robot structure model as transfer function of chatter block diagram and end milling force as machining force model. This article presents a new technique for simulating and analyzing the possibility of happening chatter vibrations at different values of machining parameters considering structure and configuration of the studied robot. Results show that limit of chatter occurrence is dramatically affected by changing robotic machining configuration.

Investigation of smart multifunctional optical sensor platform and its application in optical sensor networks

In this article, a smart multifunctional optical system-on-a-chip (SOC) sensor platform is presented and its application for fiber Bragg grating (FBG) sensor interrogation in optical sensor networks is investigated. The smart SOC sensor platform consists of a superluminescent diode as a broadband source, a tunable microelectromechanical system (MEMS) based Fabry-Perot filter, photodetectors, and an integrated microcontroller for data acquisition, processing, and communication. Integrated with a wireless sensor network (WSN) module in a compact package, a smart optical sensor node is developed. The smart multifunctional sensor platform has the capability of interrogating different types of optical fiber sensors, including Fabry-Perot sensors and Bragg grating sensors. As a case study, the smart optical sensor platform is demonstrated to interrogate multiplexed FBG strain sensors. A time domain signal processing method is used to obtain the Bragg wavelength shift of two FBG strain sensors through sweeping the MEMS tunable Fabry-Perot filter. A tuning range of 46 nm and a tuning speed of 10 Hz are achieved. The smart optical sensor platform will open doors to many applications that require high performance optical WSNs.

High-speed delay tuning of slow light in pin-diode-incorporated photonic crystal waveguide

We demonstrate the high-speed electrical delay tuning of slow light pulses using Si photonic crystal waveguides. The device has an i-region-chirped pin diode, within which thermo-optic and carrier plasma effects are generated by forward bias. The former changes the delay up to 62 ps for the DC bias. The latter changes the delay for 1 Gbps pseudo random bit sequence tuning signals, which will be applicable to advanced time-domain optical signal processing.

Broadband signal processing in space and time domain using radial basis function networks.

Broadband signal processing in space and time domain using radial basis function networks.

A tone analyzer based on a piezoelectric polymer and organic thin film transistors

A tone analyzer is demonstrated using a distributed resonator architecture on a tensioned piezoelectric polyvinyledene diuoride (PVDF) sheet. This sheet is used as both the resonator and detection element. Two architectures are demonstrated; one uses distributed, directly addressed elements as a proof of concept, and the other integrates organic thin film transistor-based transimpedance amplifiers directly with the PVDF to convert the piezoelectric charge signal into a current signal. The PVDF sheet material is instrumented along its length, and the amplitude response at 15 sites is recorded and analyzed as a function of the frequency of excitation. The determination of the dominant component of an incoming tone is demonstrated using linear system decomposition of the time-averaged response of the sheet and is performed without any time domain analysis. This design allows for the determination of the spectral composition of a sound using the mechanical signal processing provided by the amplitude response and eliminates the need for time-domain downstream signal processing of the incoming signal.

Improved measurement of vibration amplitude in dynamic optical coherence elastography

: Optical coherence elastography employs optical coherence tomography (OCT) to measure the displacement of tissues under load and, thus, maps the resulting strain into an image, known as an elastogram. We present a new improved method to measure vibration amplitude in dynamic optical coherence elastography. The tissue vibration amplitude caused by sinusoidal loading is measured from the spread of the Doppler spectrum, which is extracted using joint spectral and time domain signal processing. At low OCT signal-to-noise ratio (SNR), the method provides more accurate vibration amplitude measurements than the currently used phase-sensitive method. For measurements performed on a mirror at OCT SNR = 5 dB, our method introduces <3% error, compared to >20% using the phase-sensitive method. We present elastograms of a tissue-mimicking phantom and excised porcine tissue that demonstrate improvements, including a 50% increase in the depth range of reliable vibration amplitude measurement.

A novel time-domain signal processing algorithm for real time ventricular fibrillation detection

This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.

Companding transform based SPM compensation in coherent optical OFDM transmission

We demonstrate a mitigation of fiber nonlinearity based on μ-law companding transform in coherent optical OFDM transmissions. High peak-to-average power ratio (PAPR) increases fiber nonlinear impairments caused by the Kerr effect in optical fiber. The μ-law companding modifies amplitude profile of OFDM signal with time domain signal processing, which reduces high PAPR of OFDM signal. The effects of companding parameter on noise enhancement and PAPR variation are presented. The impacts of companding transform on system performances are evaluated in a single polarization system as well as polarization multiplexed system. The resolution of analog-to-digital converter (ADC), dispersion map of transmission link, and launch power tolerance are also considered. The results of bit-error-rate (BER) measurements show that the μ-law companding improves OSNR margin over 5.5 dB after transmission of 1,040 km over SMF.

Some considerations for different time-domain signal processing of pulse compression radar

Radar technology has for a long time used various systems that allow detection under high-resolution conditions, while emitting at the same time low peak power. Among these systems, transmitted pulse encoding by means of biphasic codes has been used for the advanced ionospheric sounder that was developed by the AIS-INGV ionosonde. In the receiving process, suitable decoding of the signal must be accomplished. This can be achieved in both the time and the frequency domains. Focusing on the time domain, different approaches are possible. In this study, two of these approaches have been compared, using data acquired by the AIS-INGV and processed by means of software tools (mainly Mathcad©). The analysis reveals the differences under both noiseless and noisy conditions, although this does not allow the conclusive establishment as to which method is better, as each of them has benefits and drawbacks. Normal 0 14 false false false IT X-NONE X-NONE

Particles Mass Flow Rate and Concentration Measurement using Electrostatic Sensor

Abstract In many industries where flow parameters measurement is essential to control manufacturing process, the use of a reliable, cost effective and high accuracy instrument is an important issue. Appropriate measurement method and design leads to improvement of pneumatic conveyors operation and process efficiency. This paper present an instrumentation design based on passive charge detection using a single electrostatic sensor. Two different sensor electrodes are applied to show the flexibility of electrostatic sensor application. A time domain signal processing algorithm is developed to measurement of mass flow rate and concentration profile from acquired electrical charge signal. The findings is led to a low cost and high accuracy design, the experimental test results of the design shows less than ±5% error between measured parameters and reference reading acquired from the manual weighing.

Hypoexponential Power—Delay Profile and Performance of Multihop OFDM Relay Links

We study the physical-layer performance of a wideband multihop system in which a chain of amplify-and-forward relays is deployed for routing data from a source to a destination. The novelty of the system model w.r.t. prior work is in assuming frequency-selective multipath channels for all hops. We propose a new approach in which the channels are specified in terms of clustered exponentially decaying power-delay profiles (PDPs). Focusing on relays that apply time-domain signal processing, the distinctive form of the end-to-end source-destination PDP motivates us to introduce a new hypoexponential PDP and study it in detail. Then, we analyze the performance of orthogonal frequency division multiplexing (OFDM) transmission over the multihop relay link. The type of the adopted analysis is suitable mainly for investigating the typical time-domain issues of OFDM transmission such as excessive multipath delay spread, non-ideal time syncronization, and interference due to insufficient cyclic prefix duration. In particular, we derive new closed-form expressions for evaluating the signal-to-interference and noise ratio. Our analysis confirms that multihopping increases considerably the delay spread of the end-to-end PDP and makes the channel more frequency selective. This imposes significant effect on the design of receiver time synchronization and pilot structures, and on the choice of OFDM physical layer parameters.