Ultrasonic echo signal modeling and identification for minor defects in metallic materials

2015 ◽  
Vol 23 (9) ◽  
pp. 2635-2644
Author(s):  
杨辰龙 YANG Chen-long ◽  
陈越超 CHEN Yue-chao ◽  
叶钱 YE Qian ◽  
郑慧峰 ZHENG Hui-feng
Keyword(s):  
Metallic Materials ◽  
Echo Signal ◽  
Signal Modeling ◽  
Ultrasonic Echo

scholarly journals Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 269 ◽  
Author(s):  
Wei Zhang ◽  
Zhipeng Li ◽  
Xuyang Gao ◽  
Yanjun Li ◽  
Yibing Shi
Keyword(s):  
Wavelet Transform ◽  
Wind Speed ◽  
Arrival Time ◽  
Time Window ◽  
Signal To Noise Ratio ◽  
Information Criteria ◽  
Echo Signal ◽  
Time Frequency ◽  
Ultrasonic Echo ◽  
Ultrasonic Anemometer

The time-difference method is a common one for measuring wind speed ultrasonically, and its core is the precise arrival-time determination of the ultrasonic echo signal. However, because of background noise and different types of ultrasonic sensors, it is difficult to measure the arrival time of the echo signal accurately in practice. In this paper, a method based on the wavelet transform (WT) and Bayesian information criteria (BIC) is proposed for determining the arrival time of the echo signal. First, the time-frequency distribution of the echo signal is obtained by using the determined WT and rough arrival time. After setting up a time window around the rough arrival time point, the BIC function is calculated in the time window, and the arrival time is determined by using the BIC function. The proposed method is tested in a wind tunnel with an ultrasonic anemometer. The experimental results show that, even in the low-signal-to-noise-ratio area, the deviation between mostly measured values and preset standard values is mostly within 5 μs, and the standard deviation of measured wind speed is within 0.2 m/s.

THE ULTRASONIC THREE-DIMENSIONAL FILTER FOR THE QUANTITATIVE DIAGNOSIS OF LIVER FIBROSIS

2009 ◽  
Vol 09 (04) ◽  
pp. 579-588 ◽  
Author(s):  
TADASHI YAMAGUCHI ◽  
HIROYUKI HACHIYA
Keyword(s):  
Liver Fibrosis ◽  
Gold Standard ◽  
Sampling Error ◽  
Three Dimensional ◽  
Percutaneous Liver Biopsy ◽  
Fiber Structure ◽  
Echo Signal ◽  
Quantitative Diagnosis ◽  
Ultrasonic Echo ◽  
Structure Extraction

At present, percutaneous liver biopsy is the gold standard in assessing liver fibrosis such as hepatitis and cirrhosis, but there could be sampling error, and specimens might not represent the state of the whole liver accurately because only about 0.002% of the organ is sampled. In this research, we propose the three-dimensional fiber structure extraction echo filter to realize a quantitative ultrasonic diagnosis. The filter is designed based on a statistical theory, and it is possible to reduce the noise contained in a back scattered ultrasonic echo signal, and to visualize the structure of a fiber.

Research on Feature Extraction for Ultrasonic Echo Signal Based on EEMD Approach

2013 ◽  
Vol 321-324 ◽  
pp. 1311-1316 ◽  
Author(s):  
Jian Ming Yu ◽  
Ze Zhang
Keyword(s):  
Empirical Mode Decomposition ◽  
Ensemble Empirical Mode Decomposition ◽  
Thin Plates ◽  
Echo Signal ◽  
Stationary Characteristic ◽  
Bonding Quality ◽  
Time Frequency ◽  
Mode Decomposition ◽  
Ultrasonic Echo

The bonding quality of composite materials have a critical influence on the quality of the product in modern industry, while the current technology can only make judgments on bonding and de-bonding instead of quantitative evaluation of different de-bonding degrees. We present HHT method to extract features of echo signals used for quantitative recognition of bonding quality of thin plates. For the non-stationary characteristic of the ultrasonic echo signal, empirical mode decomposition(EMD) and ensemble empirical mode decomposition(EEMD) are put forward to decompose the signal and calculate its energy torque. The HHT method highlights the time-frequency performance of echo signals effectively. The simulated signals verify that EEMD has more excellent decomposition performance than EMD, that is, EEMD diminishes the mode mixing to some extent generated from EMD decomposition.

Three-dimensional Objects Recognition by Ultrasonic Echo-Signal

1999 ◽  
Vol 31 (11) ◽  
pp. 86-94
Author(s):  
Roman Kuc ◽  
Nikolay P. Lepekha ◽  
Nikolay Fedorovich Kirichenko
Keyword(s):  
Three Dimensional ◽  
Echo Signal ◽  
Three Dimensional Objects ◽  
Ultrasonic Echo

scholarly journals Identification of Denatured Biological Tissues Based on Time-Frequency Entropy and Refined Composite Multi-Scale Weighted Permutation Entropy during HIFU Treatment

Entropy ◽  
2019 ◽  
Vol 21 (7) ◽  
pp. 666 ◽  
Author(s):  
Bei Liu ◽  
Shengyou Qian ◽  
Weipeng Hu
Keyword(s):  
Biological Tissues ◽  
High Intensity Focused Ultrasound ◽  
Permutation Entropy ◽  
Hifu Treatment ◽  
Echo Signal ◽  
Frequency Spectra ◽  
Time Frequency ◽  
Normal Tissues ◽  
Multi Scale ◽  
Ultrasonic Echo

Identification of denatured biological tissue is crucial to high intensity focused ultrasound (HIFU) treatment. It is not easy for intercepting ultrasonic scattered echo signals from HIFU treatment region. Therefore, this paper employed time-frequency entropy based on generalized S-transform (GST) to intercept ultrasonic echo signals. First, the time-frequency spectra of ultrasonic echo signal is obtained by GST, which is concentrated around the real instantaneous frequency of the signal. Then the time-frequency entropy is calculated based on time-frequency spectra. The experimental results indicate that the time-frequency entropy of ultrasonic echo signal will be abnormally high when ultrasonic signal travels across the boundary between normal region and treatment region in tissues. Ultrasonic scattered echo signals from treatment region can be intercepted by time-frequency entropy. In addition, the refined composite multi-scale weighted permutation entropy (RCMWPE) is proposed to evaluate the complexity of nonlinear time series. Comparing with multi-scale permutation entropy (MPE) and multi-scale weighted permutation entropy (MWPE), RCMWPE not only measures complexity of signal including amplitude information, but also improves the stability and reliability of multi-scale entropy. The RCMWPE and MPE are applied to 300 cases of actual ultrasonic scattered echo signals (including 150 cases in normal status and 150 cases in denatured status). It is found that the RCMWPE and MPE values of denatured tissues are higher than those of the normal tissues. Both RCMWPE and MPE can be used to distinguish normal tissues and denatured tissues. However, there are fewer feature points in the overlap region between RCMWPE of denatured tissues and normal tissues compared with MPE. The intra-class distance and the inter-class distance of RCMWPE are less and greater respectively than MPE. The difference between denatured tissues and normal tissues is more obvious when RCMWPE is used as the characteristic parameter. The results of this study will be helpful to guide doctors to obtain more accurate assessment of treatment effect during HIFU treatment.

De-Noising Using Wavelet Packet for Ultrasonic Testing Signal of Small Diameter Steel Pipe with Thick Wall

2013 ◽  
Vol 798-799 ◽  
pp. 398-401
Author(s):  
Yong Qiao Wei ◽  
Li Hou ◽  
Feng Lan Jia ◽  
Shao Jiang Wang ◽  
Hua Jun Xiao
Keyword(s):  
Wavelet Packet ◽  
Small Diameter ◽  
Wavelet Packet Transform ◽  
Steel Pipe ◽  
Thick Wall ◽  
Echo Signal ◽  
Ultrasonic Echo ◽  
Testing Signal ◽  
Reduction Effect

In the ultrasonic detection of small-diameter steel pipe with thick wall, the quality of ultrasonic echo signals is the foundation for the pipeline flaw identification and feature extraction. In this paper,a de-noising method of wavelet packet based on threshold is proposed for the limitation of soft and hard thresholds. The ultrasonic wave pipeline detection signal contaminated by noise is de-noised by this method. Moreover, the contrastive analysis is performed among the wavelet packet transform based on adjusted threshold, original ultrasonic echo signal and the wavelet packet transform based on default threshold. Experiment results show that the noise reduction effect of the wavelet packet based on the adjusted threshold is obvious and the SNR of signals is also improved.

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