Vehicle engine classification using normalized tone-pitch indexing and neural computing on short remote vibration sensing data

Wei, Jie; Liu, Chi-Him; Zhu, Zhigang; Cain, Lindsay R.; Velten, Vincent J.

doi:10.1016/j.eswa.2018.07.073

Cited by 9 publications

(3 citation statements)

References 16 publications

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“…As the core technology of artificial intelligence, the importance of artificial neural networks has gradually emerged, and has been widely used in many fields such as chemistry and chemical engineering [2][3][4], and it is worthy of in-depth study. This article mainly introduces the application status and research progress of artificial neural networks in the chemical field of extraction.…”

Section: Review Articlementioning

confidence: 99%

Optimization of Extraction Process Based on Neural Network

Sun

Chen

2022

AJOCS

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Liquid-liquid extraction is a chemical unit operation that utilizes the difference in solubility or distribution ratio of target components in two immiscible solvents to achieve separation, extraction or purification. There are many factors that affect the extraction efficiency, and it is difficult to quickly optimize the process using traditional methods. Artificial neural network is a system structure composed of multiple artificial neuron models, with functions such as self-learning, associative storage and fault tolerance. It can be used for optimization or control of multi-variable complex systems, and has been successfully applied to the extraction process of various products. optimization. This paper discusses the basic situation of artificial neural network, and analyzes the research progress of extraction process optimization based on neural network.

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Section: Review Articlementioning

confidence: 99%

Optimization of Extraction Process Based on Neural Network

Sun

Chen

2022

AJOCS

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“…In recent years, outside the field of diagnosis and fault detection, advanced approaches using machine learning and neural networks have been applied for various classifications of vehicles. Some of them use sound and vibration signals as information for general recognition of passbys for traffic planning, military and homeland security applications, [17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Unsupervised Learning Approach for Classification of Vehicle Fuel Type Using Psychoacoustic Features

Milivojčević,

Ćirič,

Prezelj

et al. 2023

Preprint

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“…Convolutional neural network (CNN), one of the most successful network architecture in deep learning method, has been applied with great success to learn features from raw data and adopted as the dominant approach for almost all recognition and detection tasks [19][20][21][22][23][24]. is paper develops a CNN model to learn features directly from the raw acceleration signals and tests the performance of feature learning from combined time-frequency data.…”

Section: Introductionmentioning

confidence: 99%

An Application of Time-Frequency-Based Analysis Method for Identifying Bolt Anchorage System

Zheng

Zhang

Gao

et al. 2021

Mathematical Problems in Engineering

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A rock bolt refers to a reinforcing bar used commonly in geotechnical engineering. Also, defect identification of bolt anchorage system determines the safe operation of the reinforced structures. In the present paper, to accurately extract defect information, a CNN model based on time-frequency analysis is proposed, covering both time-domain and frequency-domain information. The effect of the number of convolution kernels on the defect identification results is discussed. By laboratory experiments, the performances of STFT-based CNN with those of time-domain input or frequency-domain input-based 1D CNN are compared, and the results demonstrate that the proposed method showed enhanced performance in identification accuracy.

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Vehicle engine classification using normalized tone-pitch indexing and neural computing on short remote vibration sensing data

Cited by 9 publications

References 16 publications

Optimization of Extraction Process Based on Neural Network

Optimization of Extraction Process Based on Neural Network

Analysis of Unsupervised Learning Approach for Classification of Vehicle Fuel Type Using Psychoacoustic Features

An Application of Time-Frequency-Based Analysis Method for Identifying Bolt Anchorage System

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