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An Innovative Rail Pressure Sensor signal processing algorithm to Determine the Start of Injection and End of Injection of Diesel Engines With Common Rail Injection Systems

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IEEE ACCESS 2018年 6卷 64674-64687页

作者： Kang, Qinmiao Li, Yong Xie, Zhifeng Liu, Yongquan Zhou, Ming Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China Chinese Aeronaut Estab Inst 606 Shenyang 110015 Liaoning Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

This paper proposes an innovative rail pressure sensor signal processing algorithm to determine the start of injection and end of injection for single or multiple injections of diesel engines with a common rail injection system (CRIS). The importance of fuel injection timing (FIT) and fuel injection volume (FIV) in the CRIS is discussed, as well as the current progress of research in this field. The working principle of a solenoid valve injector is also described, pressure wave propagation is analyzed, and the characteristics of pressure waves are studied by simulation and experiments. The proposed algorithm has high reliability and flexibility and can be adjusted in real time according to engine operating status. The algorithm can effectively avoid the defects and shortcomings of traditional engine matching calibration, enhance the control precision of the FIT and FIV, improve the consistency and stability of fuel injection, and is expected to promote the performance of engine on fuel economy and pollutant emissions. The hardware implementation of this algorithm in practical ECU is also presented.

关键词： signal processing algorithm rail pressure sensor start of injection end of injection diesel engine CRIS

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Practical signal processing algorithm for wide-area surveillance-GMTI mode

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IET RADAR SONAR AND NAVIGATION 2015年第8期9卷 991-998页

作者： Yan, He Zhu, Daiyin Wang, Robert Mao, Xinhua Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing Jiangsu Peoples R China Chinese Acad Sci Inst Elect Space Microwave Remote Sensing Syst Dept Beijing Peoples R China

On the basis of the real data acquired with an X-band airborne wide-area surveillance (WAS)-GMTI radar, a practical signal processing algorithm for WAS-GMTI mode is proposed, and it is simple and effective for real-time processing. The key feature of the new algorithm is that the spatial steering vector and fixed channel error are estimated according to the result of the Doppler centroid estimation. This is due to the fact that the angle corresponding to the Doppler centroid is just the antenna look direction. In this study, the detailed description of the algorithm is presented with four steps: pre-processing, clutter suppression, constant false alarm rate detection and parameter estimation. Besides, to observe the effect of the proposed algorithm, the real data processing results are shown after each step. Finally, moving target positioning results of five successive scan periods is presented to demonstrate the effectiveness of the new algorithm.

关键词： search radar radar signal processing channel estimation radar antennas parameter estimation radar clutter interference suppression radar detection signal processing algorithm X-band wide-area surveillance-GMTI radar mode WAS spatial steering vector fixed channel error estimation Doppler centroid estimation antenna look direction clutter suppression constant false alarm rate detection parameter estimation real data processing moving target positioning successive scan periods ground moving target detection mode

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High Precision signal processing algorithm for White Light Interferometry

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SENSORS 2008年第12期8卷 7609-7635页

作者： Kim, Jeonggon Harrison Hansei Univ Informat & Commun Engn Dept Gunpo City Kyunggi Do South Korea

A new signal processing algorithm for absolute temperature measurement using white light interferometry has been proposed and investigated theoretically. The proposed algorithm determines the phase delay of an interferometer with very high precision (<< one fringe) by identifying the zero order fringe peak of cross-correlation of two fringe scans of white light interferometer. The algorithm features cross-correlation of interferometer fringe scans, hypothesis testing and fine tuning. The hypothesis test looks for a zero order fringe peak candidate about which the cross-correlation is symmetric minimizing the uncertainty of mis-identification. Fine tuning provides the proposed algorithm with high precision sub-sample resolution phase delay estimation capability. The shot noise limited performance of the proposed algorithm has been analyzed using computer simulations. Root-mean-square (RMS) phase error of the estimated zero order fringe peak has been calculated for the changes of three different parameters (SNR, fringe scan sample rate, coherence length of light source). Computer simulations showed that the proposed signal processing algorithm identified the zero order fringe peak with a miss rate of 3 x 10(-4) at 31 dB SNR and the extrapolated miss rate at 35 dB was 3 x 10(-8). Also, at 35 dB SNR, RMS phase error less than 10(-3) fringe was obtained. The proposed signal processing algorithm uses a software approach that is potentially inexpensive, simple and fast.

关键词： Phase delay estimation white light interferometry signal processing algorithm fine tuning

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Design of a signal processing algorithm for error-minimized optical triangulation displacement sensors

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MEASUREMENT SCIENCE AND TECHNOLOGY 2001年第10期12卷 1683-1688页

作者： Kim, KC Oh, SB Kim, SH Kwak, YK Korea Adv Inst Sci & Technol Dept Engn Mech Yusong Gu Taejon South Korea

Optical triangulation displacement sensors are widely used for their non-contact measurement characteristic, sub-micrometre order resolution, simple structure and long operation range. However. errors originating from surface inclination, speckle effect, light source fluctuation and detector noise restrict the wider use. In order to minimize these errors. a structure for an optical triangulation displacement sensor, which is composed of an incoherent source and a linear CCD (charge coupled device), has been proposed. However. using a linear CCD causes several problems in signal processing. Because CCDs consist of spatially discrete pixels, it is impossible to detect the peak position movement within a pixel. This is an inherently severe problem of CCDs. Therefore, a new approach is needed. In this paper, we propose an adequate signal processing algorithm to overcome the limited resolution problem of a CCD for the proposed sensor structure. The signal processing algorithm is composed of a pre-processing algorithm and a modified cross correlation algorithm. With the help of the proposed algorithm, the limited resolution problem of the CCD can be solved.

关键词： correlation algorithm displacement measurement optical sensor optical triangulation signal processing algorithm linear CCD

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Design and development of an Internet-of-Things enabled wearable ExG measuring system with a novel signal processing algorithm for electrocardiogram

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IET CIRCUITS DEVICES & SYSTEMS 2019年第6期13卷 903-907页

作者： Das, Devarshi Mrinal Vidwans, Amogh Srivastava, Abhishek Ahmad, Meraj Vaishnav, Saujal Dewan, Sourya Baghini, Maryam Shojaei Indian Inst Technol IIT Ropar Dept Elect Engn Rupnagar Punjab India Indian Inst Technol IIT Bombay Dept Elect Engn Mumbai Maharashtra India

In this article, the design and development aspects of a compact bio-potential measuring system, named ExGSense, is presented. Two versions of the prototype have been developed;first one can measure 3 + 1 V leads in time-multiplexed fashion, while the other can measure 3 + 1 V leads simultaneously. This article also presents an efficient algorithm for filtering electrocardiogram signals which is required to attenuate the effect of motion artefacts which are inevitable in wearable systems. Further, a user-friendly interface for PC and smartphone has also been developed. By the virtue of an ultra-low noise instrumentation amplifier and the programmability of gain and bandwidth of the bio-signal measuring system, a number of other bio-potential signals like EMG, EOG and EEG have been successfully recorded using disposable, off-the-shelf wet Ag/AgCl electrodes.

关键词： electromyography medical signal processing biomedical electrodes electrocardiography electroencephalography electro-oculography instrumentation amplifiers filtering theory Internet of Things human computer interaction Internet-of-Things wearable ExG measuring system signal processing algorithm development aspects compact bio-potential measuring system time-multiplexed fashion motion artefacts user-friendly interface bio-signal measuring system bio-potential signals ultralow noise instrumentation amplifier ExGSense electrocardiogram signal filtering smartphone EMG EOG EEG disposable off-the-shelf wet Ag-AgCl electrodes Ag-AgCl

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Study and Implementation of a signal processing algorithm for Doppler Ultrasound Fetal Heart signals 14

Study and Implementation of a Signal Processing Algorithm fo...

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14th IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Liu, Chuqi Ji, Chenpeng Lin, Xiaoqiang Yao, Jian Huang, Hai Zhejiang Univ Coll Biomed Engn & Instrument Sci Hangzhou Peoples R China Medzone Inst Biomed Mat & Devices Hangzhou Peoples R China

ISBN: (纸本)9781538694909

The Doppler ultrasound fetal heart signals are work and complex, while the background noise is strong. It results in many problems for household integrated Doppler fetal heart monitors. such as low sensitivity, small measuring area, low accuracy of fetal heart rates, and self-excited howling. A fetal heart signal processing algorithm is proposed in this paper, which includes the adaptive demising method based on spectral subtraction and the non-linear self-excitation suppression processing algorithm. The measuring results in a Doppler ultrasound fetal heart simulator and pregnant women show that the good denoising effect can been achieved and the signal-to-noise of the signals can been greatly enhanced by the proposed algorithm. Also, the sensitivity of fetal heart measurement is improved and the self-excited howling is eliminated effectively.

关键词： Doppler ultrasound signal processing algorithm adaptive denoising self-excited suppression

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A Guide to signal processing algorithms for Nanopore Sensors

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ACS SENSORS 2021年第10期6卷 3536-3555页

作者： Wen, Chenyu Dematties, Dario Zhang, Shi-Li Uppsala Univ Dept Elect Engn Div Solid State Elect SE-75103 Uppsala Sweden Mendoza Technol Sci Ctr Inst Ciencias Humanas Sociales & Ambientales CONICET RA-5500 Mendoza M Argentina

Nanopore technology holds great promise for a wide range of applications such as biomedical sensing, chemical detection, desalination, and energy conversion. For sensing performed in electrolytes in particular, abundant information about the translocating analytes is hidden in the fluctuating monitoring ionic current contributed from interactions between the analytes and the nanopore. Such ionic currents are inevitably affected by noise;hence, signal processing is an inseparable component of sensing in order to identify the hidden features in the signals and to analyze them. This Guide starts from untangling the signal processing flow and categorizing the various algorithms developed to extracting the useful information. By sorting the algorithms under Machine Learning (ML)-based versus non-ML-based, their underlying architectures and properties are systematically evaluated. For each category, the development tactics and features of the algorithms with implementation examples are discussed by referring to their common signal processing flow graphically summarized in a chart and by highlighting their key issues tabulated for clear comparison. How to get started with building up an ML-based algorithm is subsequently presented. The specific properties of the ML-based algorithms are then discussed in terms of learning strategy, performance evaluation, experimental repeatability and reliability, data preparation, and data utilization strategy. This Guide is concluded by outlining strategies and considerations for prospect algorithms.

关键词： nanopore sensing signal processing algorithm pulse-like signal spike recognition feature extraction analyte identification machine learning neural network

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A Survey of signal processing algorithms for Estimating Power System Modal Parameters

A Survey of Signal Processing Algorithms for Estimating Powe...

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54th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Min, Daham Yoo, Jaeyeong Heo, Jeonghyeok Hur, Kyeon Yonsei Univ Sch Elect & Elect Engn Seoul 120749 South Korea

ISBN: (纸本)9781612848570

Smart Grid is expected to provide a reliable power supply with fewer and briefer outages, cleaner power, and self-healing power systems, through advanced Power Quality (PQ) monitoring, analysis and diagnosis of the PQ measurements and identification of the root causes, and timely automated controls. It is important to understand that signal processing has been an integral part of advancing and expanding the horizons of this PQ research significantly. The capabilities and applications of signal processing for PQ are continually evolving due to the advanced PQ monitoring devices. Thus, this paper is to present a survey on the proven and emerging signal applications for enhancing PQ, focusing on algorithms for estimating system modal parameters because resonant frequencies and their damping information are critical signatures in evaluating the PQ. In particular, we discuss the need for investigating time-varying and nonlinear characteristics of the modal parameters due to dynamic changes in system operating conditions, and introduce promising signal processing techniques for this purpose.

关键词： Equations Monitoring PQ measurements damping damping information fault tolerance nonlinear characteristics power quality monitoring power supply quality power supply reliability power system identification power system measurement power system modal parameter estimation power system reliability resonant frequency self-healing power system signal processing signal processing algorithm smart grid smart power grids time-varying characteristics

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A self-sensing technology of active magnetic bearings using a phase modulation algorithm based on a high frequency voltage injection method

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2008年第9期22卷 1757-1764页

作者： Park, Young Ho Han, Dong Chul Park, In Hwang Ahn, Hyeong Joon Jang, Dong Young Seoul Natl Univ Sch Mech & Aerosp Engn Seoul 151742 South Korea BK21 Sch Creat Engn Design Next Generat Mech & Ae Seoul 151742 South Korea Soongsil Univ Dept Mech Engn Seoul 156743 South Korea Seoul Natl Univ Technol Seoul 139743 South Korea

Conventional AMB(active magnetic bearings) systems consist of electromagnetic coils, position sensors, power amplifiers and a feedback controller. This hardware configuration can lead to a structural complexity, problems of space limitations for the installation, and position control difficulties due to the non-collocation of actuators and sensors. In this paper, a self-sensing mechanism is proposed to resolve Such limitations of the general AMB system. The proposed self-sensing scheme uses a phase difference of the injected current of two opposite electromagnetic actuators while an object is levitating between the actuators. The relationship between the phase difference of injected currents and the position of a levitated object was theoretically derived and linearized. In order to realize the proposed self-sensing scheme, a signal processing algorithm was developed. The frequency response of the estimator was measured to verify, the performance of the proposed self-sensing scheme. In addition, a magnetic levitation and a disturbance rejection response were experimentally obtained to verify the feasibility of the proposed self-sensing mechanism. Experimental results showed that the developed self-sensing technique has similar performance as a practical gap sensor.

关键词： active magnetic bearing self-sensing phase modulation position sensor feedback controller pulse width modulation(PWM) signal processing algorithm position estimator

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Bias Compensation When Identifying Static Nonlinear Functions Using Averaged Measurements

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2014年第7期63卷 1855-1862页

作者： Carbone, Paolo Vandersteen, Gerd Vrije Univ Brussels Dept Elect B-1050 Brussels Belgium

When estimating the input-output characteristic of a static nonlinear function, input-referred noise may induce estimation bias, if model identification based on simple averages of input and output measurement data is performed. This paper considers estimation of static nonlinearities based on polynomial functions and input-output averaged data. It first illustrates how the estimation bias originates and then it describes a procedure to compensate its effects. Both simulation and experimental results are shown. Experiments are carried out to estimate the voltage-to-voltage characteristic of a diode-based electrical circuit. Practical considerations are made regarding the minimum number of samples needed to perform compensation effectively.

关键词： Error compensation estimation error nonlinear systems signal processing algorithm system identification

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