Analysis of Engine States and Automobile Features Based on Time-Dependent Spectral Characteristics

Yumi TAKIZAWA; Shinichi SATO; Keisuke ODA; Atsushi FUKASAWA

Analysis of Engine States and Automobile Features Based on Time-Dependent Spectral Characteristics

Yumi TAKIZAWA, Shinichi SATO, Keisuke ODA, Atsushi FUKASAWA

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This paper describes a nonstationary spectral analysis method and its application to prognosis and diagnosis of automobiles. An instantaneous frequency spectrum is considered first at a single point of time based on the instantaneous representation of autocorrelation. The spectral distortion is then considered on two-dimensional spectrum, and the filtering is introduced into the instantaneous autocorrelations. By the above procedure, the Instantaneous Covariance method (ICOV), the Instantaneous Maximum Entropy Method (IMEM), and the Wigner method are shown and they are unified. The IMEM is used for the time-dependent spectral estimation of vibration and acoustic sound signals of automobiles. A multi-dimensional (M-D) space is composed based on the variables which are obtained by the IMEM. The M-D space is transformed into a simple two-dimensional (2-D) plane by a projection matrix chosen by the experiments. The proposed method is confirmed useful to analyze nonstationary signals, and it is expected to implement automatic supervising, prognosis and diagnosis for a traffic system.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E75-A No.11 pp.1524-1532

Publication Date: 1992/11/25

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Type of Manuscript: Special Section PAPER (Special Section on Acoustic System Modeling and Signal Processing)

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Yumi TAKIZAWA, Shinichi SATO, Keisuke ODA, Atsushi FUKASAWA, "Analysis of Engine States and Automobile Features Based on Time-Dependent Spectral Characteristics" in IEICE TRANSACTIONS on Fundamentals, vol. E75-A, no. 11, pp. 1524-1532, November 1992, doi: .
Abstract: This paper describes a nonstationary spectral analysis method and its application to prognosis and diagnosis of automobiles. An instantaneous frequency spectrum is considered first at a single point of time based on the instantaneous representation of autocorrelation. The spectral distortion is then considered on two-dimensional spectrum, and the filtering is introduced into the instantaneous autocorrelations. By the above procedure, the Instantaneous Covariance method (ICOV), the Instantaneous Maximum Entropy Method (IMEM), and the Wigner method are shown and they are unified. The IMEM is used for the time-dependent spectral estimation of vibration and acoustic sound signals of automobiles. A multi-dimensional (M-D) space is composed based on the variables which are obtained by the IMEM. The M-D space is transformed into a simple two-dimensional (2-D) plane by a projection matrix chosen by the experiments. The proposed method is confirmed useful to analyze nonstationary signals, and it is expected to implement automatic supervising, prognosis and diagnosis for a traffic system.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e75-a_11_1524/_p

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@ARTICLE{e75-a_11_1524,
author={Yumi TAKIZAWA, Shinichi SATO, Keisuke ODA, Atsushi FUKASAWA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Analysis of Engine States and Automobile Features Based on Time-Dependent Spectral Characteristics},
year={1992},
volume={E75-A},
number={11},
pages={1524-1532},
abstract={This paper describes a nonstationary spectral analysis method and its application to prognosis and diagnosis of automobiles. An instantaneous frequency spectrum is considered first at a single point of time based on the instantaneous representation of autocorrelation. The spectral distortion is then considered on two-dimensional spectrum, and the filtering is introduced into the instantaneous autocorrelations. By the above procedure, the Instantaneous Covariance method (ICOV), the Instantaneous Maximum Entropy Method (IMEM), and the Wigner method are shown and they are unified. The IMEM is used for the time-dependent spectral estimation of vibration and acoustic sound signals of automobiles. A multi-dimensional (M-D) space is composed based on the variables which are obtained by the IMEM. The M-D space is transformed into a simple two-dimensional (2-D) plane by a projection matrix chosen by the experiments. The proposed method is confirmed useful to analyze nonstationary signals, and it is expected to implement automatic supervising, prognosis and diagnosis for a traffic system.},
keywords={},
doi={},
ISSN={},
month={November},}

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TY - JOUR
TI - Analysis of Engine States and Automobile Features Based on Time-Dependent Spectral Characteristics
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1524
EP - 1532
AU - Yumi TAKIZAWA
AU - Shinichi SATO
AU - Keisuke ODA
AU - Atsushi FUKASAWA
PY - 1992
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E75-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 1992
AB - This paper describes a nonstationary spectral analysis method and its application to prognosis and diagnosis of automobiles. An instantaneous frequency spectrum is considered first at a single point of time based on the instantaneous representation of autocorrelation. The spectral distortion is then considered on two-dimensional spectrum, and the filtering is introduced into the instantaneous autocorrelations. By the above procedure, the Instantaneous Covariance method (ICOV), the Instantaneous Maximum Entropy Method (IMEM), and the Wigner method are shown and they are unified. The IMEM is used for the time-dependent spectral estimation of vibration and acoustic sound signals of automobiles. A multi-dimensional (M-D) space is composed based on the variables which are obtained by the IMEM. The M-D space is transformed into a simple two-dimensional (2-D) plane by a projection matrix chosen by the experiments. The proposed method is confirmed useful to analyze nonstationary signals, and it is expected to implement automatic supervising, prognosis and diagnosis for a traffic system.
ER -