Zhu, Qingyuan and Liu, Yuanhui and Hu, Huosheng and Hou, Liang and Guan, Mingjie (2017) Using wavelet denoising in automatic online efficiency estimation of a hydraulic excavator. Transactions of the Institute of Measurement and Control, 39 (8). pp. 1262-1270. DOI https://doi.org/10.1177/0142331216634428
Zhu, Qingyuan and Liu, Yuanhui and Hu, Huosheng and Hou, Liang and Guan, Mingjie (2017) Using wavelet denoising in automatic online efficiency estimation of a hydraulic excavator. Transactions of the Institute of Measurement and Control, 39 (8). pp. 1262-1270. DOI https://doi.org/10.1177/0142331216634428
Zhu, Qingyuan and Liu, Yuanhui and Hu, Huosheng and Hou, Liang and Guan, Mingjie (2017) Using wavelet denoising in automatic online efficiency estimation of a hydraulic excavator. Transactions of the Institute of Measurement and Control, 39 (8). pp. 1262-1270. DOI https://doi.org/10.1177/0142331216634428
Abstract
<jats:p> A hydraulic excavator has a number of devices attached, the operating speeds of which are important performance indicators for performance evaluation and end-of-line inspection. This paper proposes an online and low-cost detection method to estimate the operating speed based on the peak detection of the main pump outlet pressure. A pressure sensor is installed on the main pump discharge point of a hydraulic excavator to collect real-time pressure data during operation. Then the wavelet method is deployed to denoise the obtained pressure data so that two special peak points are captured as start and end points for accurately estimating the operating time and speed of excavator devices. The proposed system is used for end-of-line inspection and performance evaluation of hydraulic excavators. Experimental results from 510 groups of data show that the proposed method can achieve a high success rate of 95.1%, and a high detection efficiency that is 60% faster than manual measurement. </jats:p>
Item Type: | Article |
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Uncontrolled Keywords: | Hydraulic excavator; operating speed; performance evaluation; signal processing; wavelet denoise |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 21 Oct 2016 13:24 |
Last Modified: | 30 Oct 2024 16:59 |
URI: | http://repository.essex.ac.uk/id/eprint/17828 |