Estimation Of Time Difference Research Articles

Retraction notice: Enhanced gray wolf optimization for estimation of time difference of arrival in WSNs

Retraction notice: Enhanced gray wolf optimization for estimation of time difference of arrival in WSNs

A 3D leakage monitoring method for pressure vessel based on region segmentation and time difference estimation

Leak monitoring and location technology is an important guarantee for the safety of pressure vessels. However, the first-time capture of sudden leakage incidents and the structure of the revolving body have brought challenges to the full range of pressure vessel monitoring and location. In this paper, based on the structural characteristics of the cylindrical pressure vessel, a 3D monitoring and location method based on region segmentation and time difference estimation is proposed, which combines regional location and time difference location to improve the location speed and accuracy of the algorithm. The adaptive threshold is adopted to capture the first moment of leakage, and the regional cross-correlation calculation is used to locate the leakage source in the area. The performance of the method is verified by liquid leakage experiment based on distributed acoustic emission sensor. The results show that the proposed method has good adaptability. It can capture leakage events and locate the leakage events at different positions and apertures in the first time, with an average location error of 2.44 cm. This study will have a new understanding of the location technology of pressure vessels and provide a reference for the health monitoring of large pressure vessels.

Enhanced gray wolf optimization for estimation of time difference of arrival in WSNs

Purpose Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios. Design/methodology/approach The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM. Findings The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods. Originality/value The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.

An Event-Based Digital Time Difference Encoder Model Implementation for Neuromorphic Systems.

Neuromorphic systems are a viable alternative to conventional systems for real-time tasks with constrained resources. Their low power consumption, compact hardware realization, and low-latency response characteristics are the key ingredients of such systems. Furthermore, the event-based signal processing approach can be exploited for reducing the computational load and avoiding data loss due to its inherently sparse representation of sensed data and adaptive sampling time. In event-based systems, the information is commonly coded by the number of spikes within a specific temporal window. However, the temporal information of event-based signals can be difficult to extract when using rate coding. In this work, we present a novel digital implementation of the model, called time difference encoder (TDE), for temporal encoding on event-based signals, which translates the time difference between two consecutive input events into a burst of output events. The number of output events along with the time between them encodes the temporal information. The proposed model has been implemented as a digital circuit with a configurable time constant, allowing it to be used in a wide range of sensing tasks that require the encoding of the time difference between events, such as optical flow-based obstacle avoidance, sound source localization, and gas source localization. This proposed bioinspired model offers an alternative to the Jeffress model for the interaural time difference estimation, which is validated in this work with a sound source lateralization proof-of-concept system. The model was simulated and implemented on a field-programmable gate array (FPGA), requiring 122 slice registers of hardware resources and less than 1 mW of power consumption.

Phase Mismatch Calibration for Dual-Channel Sliding Spotlight SAR-GMTI

This article investigates channel phase mismatch calibration during the application of displaced-phase-center antenna (DPCA) in dual-channel sliding spotlight synthetic aperture radar (SAR) for ground moving target indication (GMTI). In sliding spotlight SAR, the utilization of beam progressive sweeping in azimuth causes antenna phase centers to be misaligned from the sensor path, resulting in the phase mismatch between channels. Then, spatial channel co-registration required in the DPCA cannot be achieved directly by an azimuth time shift. In this study, a calibration method based on scanning geometry of the dual-channel sliding spotlight SAR is developed to address this issue. Moreover, the effect of the phase mismatch calibration on the estimation of azimuth time difference between the two channels is derived and analyzed in depth. The clutter suppression results processed from experimental data acquired by a C-band dual-channel SAR system (Gaofen-3) operated in sliding spotlight mode are shown for the first time to demonstrate the effective phase mismatch calibration.

Research on improved time difference estimation algorithm based on fourth-order cumulant in UHF PD location

Ultra-high frequency (UHF) detection technology is a fast-developing method for partial discharge (PD) diagnosis of electrical equipment in recent years. Extracting accurate time difference is the priority for PD location in electrical equipment using UHF technology. An improved time difference estimation algorithm based on fourth-order cumulants was first proposed in this article. It mainly included the following two steps, that is using the “correlation-shift-superposition” transformation method to process multiple samples collected from a PD source at first, and then utilizing the statistical characteristics of the fourth-order cumulant to calculate the time difference. In addition, the accuracy and stability of the improved algorithm and the other three common methods were compared. The calculation results show that the improved time difference estimation algorithm based on the fourth-order cumulant can obtain a more accurate and stable time difference than the other three methods. Improved time difference estimation algorithm based on fourth-order cumulant can approximately meet the requirements for reliable location of PD sources.

An Improved Adaptive Time Difference Estimation Method Based on Median Filter in Impulse Environment

Boiler tube burst is the main reason for the unplanned shutdown of thermal power plants. The time difference can be estimated and analyzed by the acoustic signal generated when the boiler tube leaks, and the time difference can be converted into a distance difference to locate the leakage point. The accuracy of positioning depends on the accuracy of the time difference estimation, and the various background noises produced by the complex production environment of the boiler and the impulse noise generated by the uncertain factors in the signal acquisition circuit have a non-negligible effect on the accuracy of the time difference estimation. Aiming at the problem that the signal does not have obvious second-order statistics in the environment of impulse noise, a Wiener weighted adaptive time difference estimation method based on median filtering is proposed. First, the median filter is used to remove the impulse points in the noise to make it obey the normal distribution and have second-order statistics; Next, select the generalized correlation method based on the Wiener weighting function of linear minimum mean square error to eliminate the influence of noise; Finally, according to the characteristics of the generalized correlation method that relies on the prior knowledge of the signal but the ability to suppress noise and the characteristics of the adaptive method that the ability to suppress noise is weak but does not rely on the prior knowledge of the signal, the two methods are combined to form a Wiener-weighted generalized correlation and its adaptive method. Simulation experiments prove that the Wiener weighted adaptive time difference estimation method based on median filtering has better estimation performance under impulsive noise than the adaptive minimum average p-norm method based on fractional low-order statistics.

Ranging technology using signals of opportunity of non-cooperative communication satellites

AbstractThe positioning technique employing the ubiquitous signals of opportunity of non-cooperative satellites does not send special navigation signals, instead it passively receives satellite signals as noise, presenting advantages of concealment and difficulty for potential attackers. Thus, this study investigates the ranging principle and model using non-cooperative communication satellites and a time difference estimation algorithm. The technology of time difference measurement under non-cooperative observation mode was determined and simulated. A test platform for time difference measurement was built to receive the signal from an unknown geostationary Earth orbit communication satellite and verify the ranging feasibility and performance. The ranging accuracy was found to be smaller than 6 m, as demonstrated by experimental data, which shows the viability of the proposed positioning technique for ranging technology.

Estimation of arrival time difference of partial discharge ultrasonic signals based on nonlinear transformation and covariant

Ultrasonic signals will be generated when high voltage equipment is partially discharged. In order to de-termine the location of partial discharge, the time difference between ultrasonic signal and sensor can be used. In this paper, Alpha stable distribution is used to model noisy ultrasonic signals collected during actual partial discharge, and a nonlinear transformation-covariant time difference estimation method is proposed. Firstly, the signal-to-noise ratio can be improved to a certain extent by preprocessing the noisy signal based on the arctangent nonlinear transformation. Then, the covariant correlation function is used to measure the similarity of the two signals arriving at the sensor, and according to the position of the peak value of the covariant correlation function, the time difference information of signal arrival is obtained. On the basis of theoretical analysis, the experimental results of computer simulation are discussed and summarized. Com-pared with generalized correlation method and covariant algorithm, the proposed method is more suitable for TDOA estimation of PD ultrasonic signals in low SNR and impulsive noise environment.

A systematic review of the impact of health information technology on nurses' time.

ObjectiveNursing time represents one of the highest costs for most health services. We conducted a systematic review of the literature on the impact of health information technology on nurses’ time.Materials and MethodsWe followed PRISMA guidelines and searched 6 large databases for relevant articles published between Jan 2004 and December 2019. Two authors reviewed the titles, abstracts, and full texts. We included articles that included a comparison group in the design, measured the time taken to carry out documentation or medication administration, documented the quantitative estimates of time differences between the 2, had nurses as subjects, and was conducted in either a care home, hospital, or community clinic.ResultsWe identified a total of 1647 articles, of which 33 met our inclusion criteria. Twenty-one studies reported the impact of 12 different health information technology (HIT) implementations on nurses’ documentation time. Weighted averages were calculated for studies that implemented barcode medication administration (BCMA) and 2 weighted averages for those that implemented EHRs, as these studies used different sampling units; both showed an increase in the time spent in documentation (+22% and +46%). However, the time spent carrying out medication administration following BCMA implementation fell by 33% (P < .05). HIT also caused a redistribution of nurses’ time which, in some cases, was spent in more “value-adding” activities, such as delivering direct patient care as well as inter-professional communication.Discussion and ConclusionsMost of the HIT systems increased nursing documentation time, although time fell for medication administration following BCMA. Many HIT systems also resulted in nurses spending more time in direct care and “value-adding” activities.

Intelligent Ultrasonic Flow Measurement Using Linear Array Transducer With Recurrent Neural Networks

To realize high-quality transit-time ultrasonic flow measurements, accurate and precise estimates of the transit-time difference are essential. In this study, we propose deep learning-based neural network (NN) models to measure the transit-time difference in an ultrasonic flowmeter using a linear array transducer. Three approaches to compute the transit-time difference are presented: the cross-correlation with phase zero-crossing (XCorr), fully connected NN, and recurrent neural network (RNN) with long short-term memory (LSTM). The training data for the NN were generated by simulating target time differences by utilizing the experimental data acquired in the pipe system. To evaluate the performance of the proposed methods, linear regression, the Bland–Altman plot, and the root mean squared error (RMSE) were analyzed using testing data from the experiment. The results of this study show that the RNN-based approach yielded improved performance with an accuracy of up to 94% and a 33.48% reduction in the RMSE, compared to the XCorr method. In addition to the time difference estimation, our proposed RNN-based model can replace the entire flow rate estimation process, including interpolation, velocity correction, and zero-flow calibration. This study demonstrates the feasibility of an intelligent ultrasonic flowmeter employing the RNN-based model with potential in industrial applications.

Synchronization and Estimation of Gravity‐Induced Time Difference for Quantum Clocks

AbstractIt has recently been reported that, under an operational definition of time, quantum clocks would get entangled through gravitational effects. Here, an alternative scenario is studied: The clocks have different masses and energy gaps, which would produce time differences via gravitational interaction. The proposal of quantum clock synchronization (QCS) for the gravity‐induced time difference is discussed. It is illustrated how the stability of measurement probability in the QCS proposal is influenced by the gravitational interaction induced by the clocks themselves. It is found that the precision of clock synchronization depends on the energy gaps of the clocks and the improvement of precision in quantum metrology is in fact an indicator of entanglement generation. The quantum enhanced estimation of time difference is also presented and it is found that the quantum Fisher information is very sensitive to the distance between the clocks.

Design and Development of Embedded Sound Source Localization System

The system is based on ARM as the core of the embedded platform, using STM32F103 chip, comprehensively designing adjustable gain microphone, AD7606 eight channel synchronous acquisition chip,W5300 Ethernet chip, Qt upper computer and so on to complete a multi-channel sound source localization system integrating acquisition, storage, upload, analysis and display of sound signals. The system use STM32F103 chip to control the core and source localization algorithm based on time delay estimation of arrival time difference with small computation, accurate localization and good real-time performance. Through the design and fabrication of microphone array, the acquisition and pre-processing function of sound signal is accomplished by using eight-channel synchronous acquisition module. The data is transmitted to the upper computer by using Ethernet module, and the upper computer performs algorithm processing and display. The system is simple in structure, small in size and easy to use. The test results show that the system can not only acquire complete sound data and high waveform reduction, but also display real-time sound source waveform in the upper computer. The positioning result is ideal, high accuracy, good real-time, and has certain practical value.

Arrival Time Difference Estimation of Ultrasonic Signals from Partial Discharge in Electric Power Equipments

Partial discharge of power equipment is one of the common faults in power systems. How to quickly and accurately determine the location of partial discharge is a problem that needs to be solved in practice. The signal arrival time difference estimation technique in signal processing is one of the effective methods to solve this problem. When the power equipment is partially discharged, an ultrasonic signal is generated. Therefore, the local discharge can be positioned according to the ultrasonic signal, however, the traditional signal arrival time difference estimation methods are not ideal for the actual low signal-to-noise ratio and narrow-band ultrasonic signals. In this paper, an improved correlation coefficient waveform comparison time difference estimation algorithm based on complete ensemble empirical mode decomposition with adaptive noise（CEEMDAN）, threshold denoising is proposed, referred to as CEEMDAN-TDE. Firstly, according to the characteristics of the actual ultrasonic signals, the double-exponential decay oscillation model is used to model the partial discharge ultrasonic signals, and Gaussian white noises are added as the interference signals. secondly, the CEEMDAN threshold denoising is used to improve the signal-to-noise ratio of the partial discharge signals; thirdly, the cross-correlation coefficient is calculated, then the arrival time difference can be obtained by comparing the waveforms of the correlation coefficients, and the partial discharge location information is known. The computer simulations of the CEEMDAN-TDE method, and the generalized correlation method, LMS method, and correlation coefficient waveform comparison method estimation are performed. Experimental results show that the estimating performance in arrival time difference of proposed method, CEEMDAN-TDE, is better than the other three methods’ under low SNR and narrowband. The CEEMDAN-TDE method has the hopeful more application in practice.

Određivanje pozicije akustičkih izvora korišćenjem spektralne analize višeg reda za određivanje vremena nailaska signala

The localization of various acoustic sources in a battlefield (such as weapon rounds, mortars, rockets, mines, improvised explosive devices, vehicle-borne improvised explosive devices and airborne vehicles) nowadays has a significant history. In acoustic source localization systems of multiple sensors, networked and placed at known positions are used to detect signals emitted from the source and perform localization of the source. Time of arrival estimation of the gun fire shock waves at large distances is significant when the purpose is the gun localization. At large distances shock wave signal is significantly deformed and therefore it is relatively difficult to accurately estimate the time of arrival. In this paper methods for TOA estimation are proposed, which are based on cumulants of the acoustic signal which originate from distant gunfire events. Localization of acoustic sources is performed in two steps by time difference estimation of acoustic signal arrival and using Discrete Probability Density method for positioning. Numerous field experiments have been conducted in order to verify performance of the proposed approach.

ADMM-Based TDOA Estimation

Accurate estimation of time difference of arrival (TDOA) between sensors is a fundamental problem in various applications of sensor networks. In this letter, a novel algorithm is proposed to estimate TDOAs based on low-rank essence of a TDOA matrix, whose entry $(i,j)$ denotes TDOA value between sensors $i$ and $j$ with respect to a common reference source. To enhance the robustness of the proposed algorithm, we further introduce the Gram matrix of the TDOA matrix, resulting in a semidefinite programming estimation problem. An efficient alternating direction method of multipliers is developed to improve the scalability of the proposed algorithm. Simulation results validate the performance of the proposed algorithm.

Spectral Kurtosis를 이용한 프로펠러 날개끝 보텍스 소음의 발생위치추정

One primary concern for marine propeller design is the incipient tip vortex cavitation. The present study elaborates its hyperbolic localization, which is subjected to an estimation of time difference of arrival between measured acoustic signals. The generalized cross-correlation with phase transform, a conventional algorithm for time delay estimation, tends to be susceptible to the noise outside the frequency band of signal. In order to suppress these effects, we propose a weighting function, resembling the rectangular window in frequency domain. By further noting that the signal arisen by the tip vortex cavitation can be fall into the cyclostationary type, the spectral kurtosis is employed to design the optimum band of the frequency weights. Finally, the method is verified by experimental measurements in the water tunnel.

GCC-PHAT time difference estimation algorithm based on binary frequency weight with suppressing wind noise

GCC-PHAT time difference estimation algorithm based on binary frequency weight with suppressing wind noise

A new method for estimation of time parameters of standard and non-standard switching impulse voltages

In this paper, a new method for estimation of time parameters of standard and non-standard switching impulse voltages is presented. Method is based on estimation of time difference between true and virtual origin of the switching impulse waveform. An analytical expression was derived for calculation of time to peak, which is more accurate than the expression given in IEC 60060-1. The presented method was verified with mathematically generated double-exponential waveforms and waveforms given in IEC 61083-2 with time to peak values within the range 20–300 µs and time to half values within the range 1000–4000 µs. An experimental verification of the proposed method was successfully demonstrated by comparison with an approved impulse voltage measuring system.

Leak Detection and Location of Water Pipes Using Vibration Sensors and Modified ML Prefilter.

This paper proposes a new leak detection and location method based on vibration sensors and generalised cross-correlation techniques. Considering the estimation errors of the power spectral densities (PSDs) and the cross-spectral density (CSD), the proposed method employs a modified maximum-likelihood (ML) prefilter with a regularisation factor. We derive a theoretical variance of the time difference estimation error through summation in the discrete-frequency domain, and find the optimal regularisation factor that minimises the theoretical variance in practical water pipe channels. The proposed method is compared with conventional correlation-based techniques via numerical simulations using a water pipe channel model, and it is shown through field measurement that the proposed modified ML prefilter outperforms conventional prefilters for the generalised cross-correlation. In addition, we provide a formula to calculate the leak location using the time difference estimate when different types of pipes are connected.