Knock Detection Based on MAPO Analysis, AR Model and Discrete Wavelet Transform Applied to the In-Cylinder Pressure Data: Results and Comparison

2014 ◽  
Vol 8 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Daniela Siano ◽  
Maria Antonietta Panza ◽  
Danilo D'Agostino
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Ar Model ◽  
Discrete Wavelet ◽  
Cylinder Pressure ◽  
Pressure Data ◽  
Knock Detection

Knock Detection and Control in an HCCI Engine Using DWT

2011 ◽  
Author(s):  
Masoud Mashkournia ◽  
Adrian Audet ◽  
Charles Robert Koch
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Wavelet Transforms ◽  
Good Time ◽  
Discrete Wavelet ◽  
Feed Forward ◽  
Hcci Engine ◽  
Pressure Trace ◽  
Knock Detection ◽  
And Control

The novel application of the Discrete Wavelet Transform (DWT) in a real time controller is used to detect and subsequently control knock in a Homogeneous Charge Compression Ignition (HCCI) engine. Classical Fourier techniques for knock detection are discussed and compared to Wavelet Transforms. The Discrete Wavelet Transform filter bank is chosen as the best method for knock detection due to its good time-resolution and low computational requirements. The DWT method is compared with the root mean squared value of the pressure trace as the benchmark method for determining knock and the two methods are linearly correlated. Using the DWT method for knock detection and modulating fuel octane, both a Proportional Integral (PI) and PI with Feed-forward control are implemented. Both of these methods reduce knock intensity for a step increase in engine load. The combination of Feed-forward with PI feedback is found to be slightly more effective than just PI feedback control.

Improving Space Localization Properties of the Discrete Wavelet Transform

Informatica ◽  
2013 ◽  
Vol 24 (4) ◽  
pp. 657-675
Author(s):  
Jonas Valantinas ◽  
Deividas Kančelkis ◽  
Rokas Valantinas ◽  
Gintarė Viščiūtė
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Space Localization

An Adaptive Binarization Method for Cost-efficient Document Image System in Wavelet Domain

2020 ◽  
Vol 64 (3) ◽  
pp. 30401-1-30401-14 ◽  
Author(s):  
Chih-Hsien Hsia ◽  
Ting-Yu Lin ◽  
Jen-Shiun Chiang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Document Image ◽  
Background Information ◽  
Raspberry Pi ◽  
Discrete Wavelet ◽  
Image System ◽  
Low Frequencies ◽  
Cost Efficient ◽  
Binarization Method

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.

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