• Title/Summary/Keyword: road roughness detection

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IRI estimation using analysis of dynamic tire pressure and axle acceleration

  • Zhao, Yubo;McDaniel, J. Gregory;Wang, Ming L.
    • Smart Structures and Systems
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    • v.19 no.2
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    • pp.151-161
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    • 2017
  • A new method is developed to estimate road profile in order to estimate IRI based on the ASTM standard. This method utilizes an accelerometer and a Dynamic Tire Pressure Sensor (DTPS) to estimate road roughness. The accelerometer measures the vertical axle acceleration. The DTPS, which is mounted on the tire's valve stem, measures dynamic pressure inside the tire while driving. Calibrated transfer functions are used to estimate road profile using the signals from the two sensors. A field test was conducted on roads with different quality conditions in the city of Brockton, MA. The IRI values estimated with this new method match the actual road conditions measured with Pavement Condition Index (PCI) based on the ASTM standard, images taken from an onboard camera and passengers' perceptions. IRI has negative correlation with PCI in general since they have overlapping features. Compared to the current method of IRI measurement, the advantage of this method is that a) the cost is reduced; b) more space is saved; c) more time is saved; and d) mounting the two sensors are universally compatible to most cars and vans. Therefore, this method has the potential to provide continuous and global monitoring the health of roadways.

The detection of IC engine's Mutiple misfire using Walsh transform (월쉬변환을 이용한 IC엔진의 다중실화검출)

  • 김종부;이태표어정수임국현
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.235-238
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    • 1998
  • This paper presents the detection of internal combustion engine's multiple misfire. The primary cause of air pollution by vehicles is imperfect conbustion of fuel. The CARB(California Air Resources Board) have imposed regulations for the detection of misfiring in automotive engines. The OBD-II regulations requir that misfire should be monitored by the diagnostic system, and that the goal of OBD-II is to alert the driver to the presence of a malfunction of the emission control system. Present invention based upon measurements of engine roughness as derived from crankshaft angular velocity measurements with special signal processing method. Crankshaft angular velocity signals are processed by walsh-fourier transform. Experimental work confims that it's possible to apply walsh-fourier transform for the detection of multiple misfires in no-load idle and road testing.

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Extraction of quasi-static component from vehicle-induced dynamic response using improved variational mode decomposition

  • Zhiwei Chen;Long Zhao;Yigui Zhou;Wen-Yu He;Wei-Xin Ren
    • Smart Structures and Systems
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    • v.31 no.2
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    • pp.155-169
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    • 2023
  • The quasi-static component of the moving vehicle-induced dynamic response is promising in damage detection as it is sensitive to bridge damage but insensitive to environmental changes. However, accurate extraction of quasi-static component from the dynamic response is challenging especially when the vehicle velocity is high. This paper proposes an adaptive quasi-static component extraction method based on the modified variational mode decomposition (VMD) algorithm. Firstly the analytical solutions of the frequency components caused by road surface roughness, high-frequency dynamic components controlled by bridge natural frequency and quasi-static components in the vehicle-induced bridge response are derived. Then a modified VMD algorithm based on particle swarm algorithm (PSO) and mutual information entropy (MIE) criterion is proposed to adaptively extract the quasi-static components from the vehicle-induced bridge dynamic response. Numerical simulations and real bridge tests are conducted to demonstrate the feasibility of the proposed extraction method. The results indicate that the improved VMD algorithm could extract the quasi-static component of the vehicle-induced bridge dynamic response with high accuracy in the presence of the road surface roughness and measurement noise.

Detection of Misfire in Car Engines using Walsh Discrete Fourier Transform (WDFT를 이용한 자동차 엔진의 실화검출)

  • 김종부;이태표;오정수;임국현
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.1
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    • pp.67-74
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    • 1998
  • The primary cause of air pollution by vehicles is imperfect combustion of fuel. One of the most usual causes of this imperfect combustion is the misfire in IC engins. The U.S. EPA(Environment Protection Agency) and the CARB(California air Resources Board) have imposed regulations for the detection of misfiring in automotive engines. The OBD-II regulations require that misfire should be monitored by the engine diagnostic system, and that the goal of OBD-II is to alert the driver to the presence of a malfunction of the emission control system. Several solutions to the misfire detection problem have been proposed for the detection of misfires. However, the performance of these methods in the presence of misfire is not altogether clear. This paper presents a precise method and system for internal combustion engine misfire. Present invention based upon measurements of engine roughness as derived from crankshaft angular velocity measurements with special signal processing method. Crankshaft angular velocity signals are processed by WDPT, so that the more reliable misfire detection than the time domain analysis. Experimental work confirms that it is possible to apply the WDFT for the detection of misfires in no-load idle and road testing.

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