Time-domain Data Processing Research Articles

UniChromCD for Demultiplexing Time-Resolved Charge Detection-Mass Spectrometry Data.

Charge detection mass spectrometry (CD-MS) enables characterization of large, heterogeneous analytes through the analysis of individual ion signals. Because hundreds to thousands of scans must be acquired to produce adequate ion statistics, CD-MS generally requires long analysis times. The slow acquisition speed of CD-MS complicates efforts to couple it with time-dispersive techniques, such as chromatography and ion mobility, because it is not always possible to acquire enough scans from a single sample injection to generate sufficient ion statistics. Multiplexing methods based on Hadamard and Fourier transforms offer an attractive solution to this problem by improving the duty cycle of the separation while preserving retention/drift time information. However, integrating multiplexing with CD-MS data processing is complex. Here, we present UniChromCD, a new module in the open-source UniDec package that incorporates CD-MS time-domain data processing with demultiplexing tools. Following a detailed description of the algorithm, we demonstrate its capabilities using two multiplexed CD-MS workflows: Hadamard-transform size-exclusion chromatography and Fourier-transform ion mobility. Overall, UniChromCD provides a user-friendly interface for analysis and visualization of time-resolved CD-MS data.

Automatized localization of induced geothermal seismicity using robust time-domain array processing

The surveillance of geothermal seismicity is typically conducted using seismic networks, deployed around the power plants and subject to noise conditions in often highly urbanized areas. In contrast, seismic arrays can be situated at greater distances and allow monitoring of different power plants from one central location, less affected by noise interference. However, the effectiveness of arrays to monitor geothermal reservoirs is not well investigated and the increased distance to the source coincides with a decreased accuracy of the earthquake localizations. It is therefore essential to establish robust data processing and to obtain precise estimates of the location uncertainties. Here, we use time-domain array data processing and solve for the full 3-D slowness vector using robust linear regression. The approach implements a Biweight M-estimator, which yields stable parameter estimates and is well suited for real-time applications. We compare its performance to conventional least squares regression and frequency wavenumber analysis. Additionally, we implement a statistical approach based on changepoint analysis to automatically identify P- and S-wave arrivals within the recorded waveforms. The method can be seen as a simplification of autoregressive prediction. The estimated onsets facilitate reliable calculations of epicentral distances. We assess the performance of our methodology by comparison to network localizations for 77 induced earthquakes from the Landau and Insheim deep-geothermal reservoirs, situated in Rhineland-Palatinate, Germany. Our results demonstrate that we can differentiate earthquakes originating from both reservoirs and successfully localize the majority of events within the magnitude range of ML -0.2 to ML 1.3. The discrepancy between the two localization methods is mostly less than 1 km, which falls within the statistical errors. However, a few localizations deviate significantly, which can be attributed to poor observations during the winter of 2021/2022.

Brillouin Optical Correlation Domain Analysis With Over 2.5 Million Resolution Points Based on Raman Amplification and Injection Locking

We propose and experimentally demonstrate a long-range Brillouin optical correlation domain analysis (BOCDA) system based on distributed Raman amplification and injection-locking to reach over 2.6 million resolving points. The optimization of key parameters in the Raman amplification, time domain data processing, differential measurement scheme, and injection-locking are applied to achieve a spatial resolution of 2 cm over a 50 km sensing fiber. Our result corresponds to at least twice improvement compared to former records, and the best one among distributed Brillouin sensors in terms of the number of resolving points.

Study on the Difference of Human Body Balance Stability Regulation Characteristics by Time-Frequency and Time-Domain Data Processing Methods.

In all, 16 subjects were tested, including 8 from the Chinese national team who had won the world championships of freestyle skiing aerials, with 10+ years of training (age: 23 ± 23.1 years, Height: 176 ± 2.1 cm, and weight: 69 ± 3.5 kg), and 8 ordinary graduate students of Shenyang Institute of Physical Education (age: 22.6 ± 4.6 years, Height: 179 ± 3.3 cm, and weight: 73 ± 4.1 kg). When performing the tasks, the research subjects were required to stand on the steady support surface (with eyes closed and legs closed) for 30 s in each testing. The displacement data of the anteroposterior (AP) direction and the mediolateral (ML) direction of their centre of pressure (COP) were recorded. Then, WT and OSI were calculated. Two dissimilar methods were compared to analyse the characteristics of balance ability. (1) The athletes' WT values in the AP direction and the ML direction were concentrated in the interval of 22~30 s and 0-8 s, respectively, while the ordinary graduate students' WT values in the AP direction and the ML direction were concentrated in the interval of 10~25 s and 0-7 s, respectively; (2) the WT values of the regular graduate students in the AP direction and the ML direction were higher than those of the athletes (p < 0.01); and (3) the OSI value in the AP direction of the athletes was higher than of the ordinary graduate students, while the OSI value in the ML direction of the athletes was lower than that of regular graduate students. Compared to the OSI, WT can analyse the characteristics of balance control ability more effectively. The COP displacement frequencies of the athletes and ordinary graduate students were concentrated in the low-frequency bands. The athletes had superior adjustment ability in an imbalanced state and could adjust to the best position without effort. In addition, the athletes had a stronger adaptive ability. In comparison, the ordinary graduate students had comparatively poor adaptive ability and weak adjustment ability in the imbalanced state, so it was difficult for them to attain the best angle after adjustment.

A Multi-Frequency Tomographic Inverse Scattering Using Beam Basis Functions.

We present an overview of a beam-based approach to ultra-wide band (UWB) tomographic inverse scattering, where beam-waves are used for local data-processing and local imaging, as an alternative to the conventional plane-wave and Green’s function approaches. Specifically, the method utilizes a phase–space set of iso-diffracting beam-waves that emerge from a discrete set of points and directions in the source domain. It is shown that with a proper choice of parameters, this set constitutes a frame (an overcomplete generalization of a basis), termed “beam frame”, over the entire propagation domain. An important feature of these beam frames is that they need to be calculated once and then used for all frequencies, hence the method can be implemented either in the multi-frequency domain (FD), or directly in the time domain (TD). The algorithm consists of two phases: in the processing phase, the scattering data is transformed to the beam domain using windowed phase–space transformations, while in the imaging phase, the beams are backpropagated to the target domain to form the image. The beam-domain data is not only localized and compressed, but it is also physically related to the local Radon transform (RT) of the scatterer via a local Snell’s reflection of the beam-waves. This expresses the imaging as an inverse local RT that can be applied to any local domain of interest (DoI). In previous publications, the emphasis has been set on TD data processing using a special class of localized space–time beam-waves (wave-packets). The goal of the present paper is to present the imaging scheme in the UWB FD, utilizing simpler Fourier-based data-processing tools in the space and time domains.

Terahertz waves for contactless control and imaging in aeronautics industry

The usability of terahertz systems for specific inspection tasks and imaging in the aeronautics industry is assessed. Especially, we demonstrate the suitability of Frequency-modulated continuous-wave (FMCW) radars for health monitoring and see-through imaging. Additionally, terahertz time-domain data processing is performed for multi-layered paint structure characterization. FMCW radar principles are introduced. Available systems are described along with their benefits and limitations. Defect detection capabilities and progresses towards airplane covering see-through imaging are illustrated through FMCW experimental results on real samples. The suitability of FMCW radars as an advanced contactless non-destructive testing (NDT) tool for the aeronautics industry and maintenance services is demonstrated. A second application, based on terahertz time domain techniques, targets the characterisation of multi-layered painting structures through the assessment of dielectric properties and individual thickness of each layer deposited. Beside the review of extraction methods, the introduced new algorithm allows to derive a parametric transfer function, thus denoting the main contributions which give rise to the recorded terahertz electromagnetic field. Such a development pushes further the understanding and characterization of stratified structures by means of terahertz radiations and represents an indispensable tool to efficiently localise any deviation to the nominal painting stack in terms of thickness or dielectric properties.

50 km-Range Brillouin Optical Correlation Domain Analysis With First-Order Backward Distributed Raman Amplification

We demonstrate the enlargement of sensing range of Brillouin optical correlation domain analysis (BOCDA) system by introducing the first-order distributed Raman amplification. The time-domain data processing is adopted for the BOCDA system utilizing a gated Brillouin pump, and the Raman amplification is applied to compensate for the depletion of Brillouin pump induced by Rayleigh scattering and Brillouin interaction. The Raman pump is injected in the opposite direction to the propagation of Brillouin pump, where the pumping scheme is optimized by simulations. A differential measurement scheme is additionally introduced for improving spatial resolution and dynamic range. In experiments, we measure the strain distribution along a 52.1 km sensing fiber with 7 cm spatial resolution, where the number of resolving points of measurement is more than 744 000.

Trace-Level Persistent Organic Pollutant Analysis with Gas-Chromatography Orbitrap Mass Spectrometry-Enhanced Performance by Complementary Acquisition and Processing of Time-Domain Data.

The range of commercial techniques for high-resolution gas-chromatography-mass spectrometry (GC-MS) has been recently extended with the introduction of GC Orbitrap Fourier transform mass spectrometry (FTMS). We report on progress with quantitation performance in the analysis of persistent organic pollutants (POP), by averaging of time-domain signals (transients), from a number of GC-FTMS experiment replicates. Compared to a standard GC-FTMS measurement (a single GC-FTMS experiment replicate, mass spectra representation in reduced profile mode), for the 10 GC-FTMS technical replicates of ultratrace POP analysis, sensitivity improvement of up to 1 order of magnitude is demonstrated. The accumulation method was implemented with an external high-performance data acquisition system and dedicated data processing software to acquire the time-domain data for each GC-FTMS replicate and to average the acquired GC-FTMS data sets. Concomitantly, the increased flexibility in ion signal detection allowed the attainment of ultrahigh-mass resolution (UHR), approaching R = 700 000 at m/z = 200.

Healthcare Informatics and Monitoring System based on Fog Computing

Wireless sensor networks and internet of things are widely used in healthcare industry. In today’s scenario wearable sensors become very popular devices to monitor patients at high risk. Patients who are suffering from long lasting sickness visits hospital at multiple time for their regular check-up. Treatment from this kind of system increases the expenditure in overall for the patients. However, with recent technological innovation such as cloud and fog computing, with minimal expense on storage and computing facilities these problems are overcome. In this paper, we provide an analysis of fog computing role over cloud computing to monitor patient’s health to provide context aware services without delay to the end user when it required to patient and medical practitioner. Three layer architecture is proposed for real time domain data storage, processing and communication. This increase the capability of cloud computing with the integration to fog computing for current and future use application.

Linearly Configured Brillouin Optical Correlation Domain Analysis System Incorporating Time-Domain Data Processing

We propose a linearly configured Brillouin optical correlation domain analysis system incorporated with time domain data processing, where a fiber under test (FUT) is accessed from single end and multiple sensing points are simultaneously interrogated to extend the measurement range. In our scheme, correlation peaks (CPs) are sequentially generated by the interaction between a pump pulse outgoing from the system and a probe wave reflected from the end of an FUT, where the time-domain data processing is applied to obtain the Brillouin gain spectrum of each CP. In experiments, we demonstrate simultaneous acquisition of Brillouin gain spectra at 982 CPs with a spatial resolution of less than 5 cm and a sensing range extended from 10.3 m to 10.15 km. We also show that the amplitude of frequency modulation (Δf), which has been limited to the Brillouin frequency of an FUT in linear-configured BOCDA systems, can be enlarged without definite limitation by the time-domain data processing. In the experimental confirmation Δf of 15.6 GHz, about 1.5 times of the Brillouin frequency of FUT, is successfully applied to simultaneous analysis of 98 CPs by the time-domain data processing.

JOINT INTERPRETATION OF AIRBORNE ELECTROMAGNETIC DATA IN THE TIME DOMAIN AND FREQUENCY DOMAIN

Тhe advantage of combine processing of frequency domain and time domain data provided by the EQUATOR system is discussed. The heliborne complex has a towed transmitter, and, raised above it on the same cable a towed receiver. The excitation signal contains both pulsed and harmonic components. In fact, there are two independent transmitters operate in the system: one of them is a normal pulsed domain transmitter, with a half-sinusoidal pulse and a small "cut" on the falling edge, and the other one is a classical frequency domain transmitter at several specially selected frequencies. The received signal is first processed to a direct Fourier transform with high Q-factor detection at all significant frequencies. After that, in the spectral region, operations of converting the spectra of two sounding signals to a single spectrum of an ideal transmitter are performed. Than we do an inverse Fourier transform and return to the time domain. The detection of spectral components is done at a frequency band of several Hz, the receiver has the ability to perfectly suppress all sorts of extra-band noise. The detection bandwidth is several dozen times less the frequency interval between the harmonics, it turns out thatto achieve the same measurement quality of ground response without using out-of-band suppression you need several dozen times higher moment of airborne transmitting system. The data obtained from the model of a homogeneous half-space, a two-layered model, and a model of a horizontally layered medium is considered. A time-domain data makes it easier to detect a conductor in a relative insulator at greater depths. The data in the frequency domain gives more detailed information about subsurface. These conclusions are illustrated by the example of processing the survey data of the Republic of Rwanda in 2017. The simultaneous inversion of data in frequency domain and time domain can significantly improve the quality of interpretation.

Brillouin Optical Correlation Domain Analysis Enhanced by Time-Domain Data Processing for Concurrent Interrogation of Multiple Sensing Points

We propose and experimentally demonstrate a Brillouin optical correlation domain analysis system adopting time-domain data processing and differential measurement for simultaneous interrogation of multiple sensing points. Continuous probe and pulsed pump waves are simultaneously frequency-modulated by a MHz-order sinusoidal RF wave so that multiple correlation peaks are sequentially generated according to the propagation of the pump along a fiber under test (FUT). The Brillouin gain spectrum of each correlation peak is obtained and interrogated by moving window averaging of the probe wave with a span of the period of the RF modulation, leading to the simultaneous monitoring of the multiple sensing points. In experiments, 148 correlation peaks are concurrently interrogated with a spatial resolution less than 3 cm along a 1530 m FUT.

Non-invasive and non-ionizing depth resolved infra-red imaging for detection and evaluation of breast cancer: a numerical study

Among various breast cancer screening modalities (x-ray mammography, magnetic resonance, ultrasound, optical, positron emission mammography, molecular breast, breast specific gamma, guided radiofrequency biopsy and electrical impedance imaging) recently proposed infrared thermography proved to be an emerging screening technique due to its inherent capabilities (such as non-contact, non-harmful, full field imaging) for early detection of breast cancer. It is highly desirable to diagnose the cancer at an early stage for proper treatment. This present work highlights an emissivity insensitive highly depth resolved infrared imaging technique and associated analysis for early detection of the tumours present inside the breast at different depths simulated using a three-dimensional finite element model. In order to make this study more realizable an additive white Gaussian noise is incorporated in the generated simulated data. Further, the noisy data is analysed using time domain data processing technique to obtain the respective phase information. This letters presents the results obtained results for both normal breast as well as for the breast having four tumours located at different depths. In order to compare the detection capabilities of the proposed scheme quantitatively signal to noise ratio is taken as a figure of merit.

A polyphase filter for many-core architectures

In this article we discuss our implementation of a polyphase filter for real-time data processing in radio astronomy. The polyphase filter is a standard tool in digital signal processing and as such a well established algorithm. We describe in detail our implementation of the polyphase filter algorithm and its behaviour on three generations of NVIDIA GPU cards (Fermi, Kepler, Maxwell), on the Intel Xeon CPU and Xeon Phi (Knights Corner) platforms. All of our implementations aim to exploit the potential for data reuse that the algorithm offers. Our GPU implementations explore two different methods for achieving this, the first makes use of L1/Texture cache, the second uses shared memory. We discuss the usability of each of our implementations along with their behaviours. We measure performance in execution time, which is a critical factor for real-time systems, we also present results in terms of bandwidth (GB/s), compute (GFLOP/s/s) and type conversions (GTc/s). We include a presentation of our results in terms of the sample rate which can be processed in real-time by a chosen platform, which more intuitively describes the expected performance in a signal processing setting. Our findings show that, for the GPUs considered, the performance of our polyphase filter when using lower precision input data is limited by type conversions rather than device bandwidth. We compare these results to an implementation on the Xeon Phi. We show that our Xeon Phi implementation has a performance that is 1.5× to 1.92× greater than our CPU implementation, however is not insufficient to compete with the performance of GPUs. We conclude with a comparison of our best performing code to two other implementations of the polyphase filter, showing that our implementation is faster in nearly all cases. This work forms part of the Astro-Accelerate project, a many-core accelerated real-time data processing library for digital signal processing of time-domain radio astronomy data.

Bearing diagnosis using proximity probe and accelerometer

Employing multiple sensors that generate different physical parameters from the measured system to monitor its health increases the diagnosis reliability. In the present work, bearing diagnosis capabilities of proximity probes are explored by exploiting its advantages and alleviating its shortcomings using appropriate signal processing of the raw time domain data. A Time Synchronous Averaging based method is proposed for processing of the data acquired by proximity probes and its benefit is illustrated on test bearings. Simultaneous synchronous data is acquired with the help of proximity probes and accelerometer during a life test as the defect is naturally induced and progressed with time. The proximity probe is shown to perform better diagnosis for inner race defect compared to accelerometer due to a direct transmission path for this defect. The use of proximity probe can effectively supplement the information from accelerometer and improve the accuracy of bearing diagnosis.

Acceleration Data Acquisition and Analysis Method of Shaking Table Test

Shaking table test is an important means of simulated earthquake in laboratory, slope shaking table test data provide a scientific basis for analysis of dynamic stability and instability mechanism of slopes. Sine vibration table test data processing is different from general frequency domain analysis method, need real-time data processing in time domain. Taking the sine sweep test conditions, which is one of the conditions in "Earthquake landslide and slope prevention and control technology research on shaking table test", as an example. Describes the layout of sensors in shaking table test and the reasons; Sine sweep test load and aim; and listed the steps and methods of the sine sweep test in data processing; Through the processing and analysis of test data identified the vibration frequency of model and shaking table system is 30Hz, damping ratio is 2.06%; Analysis and calculation of the different sections of the slope and position of the amplification coefficient. A methodological guidance for shaking table test and dynamic response analysis of the slope is provided.

Crack detection in structures using deviation from normal distribution of measured vibration responses

Cracks are one of the common defects in structural components that may ultimately lead to failure of structures if not detected. Generally, most of the vibration based crack detection methods transform measured vibration responses from time-domain into frequency-domain using Fourier or wavelet transform for damage detection. However, it would be more convenient if the vibration responses could be analysed in their original time-domain. Therefore, a practical method based on probability distribution function is proposed which performs all the data processing in time-domain for the purpose of crack detection in beam-like structures. The application of the proposed method to both numerical and experimental examples and their results are presented.

Comparison of Deterministic and Stochastic Method in Operational Modal Analysis in Application for Civil Engineering Structures

Applying Operational Modal Analysis (OMA) one can extract modal properties of structure (eigenfrequencies, eigenforms and modal damping) on the basis of vibration measurement only - without excitation measurement, what is very complicated in case of big structures. This great advantage of OMA makes this method more common for civil engineering application. The two main techniques are used in OMA, one uses data processing in time domain, the second in frequency domain. The paper presents the comparison of these two method in application OMA for engineering structures.

Refined sea state analysis from an array of four identical directional buoys deployed off the Northern Cornish coast (UK)

This paper presents an analysis of sea states carried out from extended wave measurements realized near the Wave Hub wave energy test facility in Cornwall (UK). The space directional information is derived from the spectro-directional processing of time-domain data provided by an array of four independent SEAWATCH Mini II displacement buoys separated by an approximate average distance of 500m. It is observed that, even though the size of the array is small compared to the local wave trains’ length, the estimation of the directional spectra – using maximum entropy and likelihood methods – may sometimes exhibit certain space variability over the array. It was also observed that the tidal currents variations produced a significant influence upon the wave directional estimation and wave spectral parameters. Spectro-directional partitioning and wave system tracking were subsequently applied and this emphasized the influence of tide variations upon the individual swells and wind-seas as measured by the buoys. This paper, therefore, also illustrates the relevance of applying partitioning and tracking procedures for the identification of wave systems in oceanographic and wave energy studies.

Practical Methods for Noise Removal: Applications to Spikes, Nonstationary Quasi-Periodic Noise, and Baseline Drift

A new approach to signal processing of analytical time-domain data is presented. It consists in identifying the types of noise, characterizing them, and subsequently subtracting them from the otherwise unprocessed data set. The algorithms have been successfully applied to three classes of noise commonly found in analytical signals: spikes, ripples, and baseline drift. Traditional filters have been used as an intermediary step to detect and remove spikes in the signal with 96.8% success. Adaptive ensemble average subtraction has been developed to remove nonstationary ripples that have similar time scales as the signal of interest. This method increased the signal-to-noise ratio by up to 250% and led to minimal distortion of the signal, unlike conventional Fourier filters. Finally the removal of baseline drift has been achieved by subtraction of a mathematical model for the baseline. These three methods are generic, computationally fast, and applicable to a wide range of analytical techniques. Full Matlab codes and examples are included as Supporting Information.