Backward wave separation method in a single transmitter and multi-receiver sensor array for improved damage identification of two-dimensional structures

2017 ◽  
Vol 26 (2) ◽  
pp. 229-250 ◽  
Author(s):  
Zijian Wang ◽  
Pizhong Qiao
Keyword(s):  
Sensor Array ◽  
Damage Identification ◽  
Signal To Noise Ratio ◽  
Metal Plate ◽  
Separation Method ◽  
High Signal ◽  
Localization Accuracy ◽  
Reflected Wave ◽  
Wave Separation ◽  
Backward Wave

In this paper, a backward wave separation method is proposed. Since the first backward wave can be considered as the damage reflection, the damage reflected wave peaks are artificially amplified by appropriately shifting and summing signals collected from a series of sensing points aligned along the wave propagating direction. This shifting and summing process aims to present the damage reflected wave peaks more distinctively while offsets randomly distributed environmental interferences. Due to the high signal-to-noise ratio of the treated signal, the application of backward wave separation is able to attain baseline-free damage detection. A circular single transmitter and multi-receiver sensor array is then deployed on a metal plate to identify the crack-like damage. Signals collected by the sensor array with and without the treatment of the backward wave separation method are, respectively, imported to the delay-and-sum imaging algorithm to yield individual damage contours. The comparisons between these contours demonstrate that the backward wave separation method is able to significantly improve the damage identification performance of the sensor array with respect to the damage localization accuracy, noise immunity, and damage sensitivity. Both the finite element modeling and laser measurement are conducted to validate the effectiveness of the proposed backward wave separation method.

A compact guided-wave EMAT with pulsed electromagnet for ferromagnetic tube inspection

2020 ◽  
Vol 64 (1-4) ◽  
pp. 951-958
Author(s):  
Tianhao Liu ◽  
Yu Jin ◽  
Cuixiang Pei ◽  
Jie Han ◽  
Zhenmao Chen
Keyword(s):  
Power Plants ◽  
Signal To Noise Ratio ◽  
Small Diameter ◽  
Performance Testing ◽  
Guided Wave ◽  
High Signal ◽  
Receiver Coil ◽  
Signal To Noise ◽  
Corrosion Defects

Small-diameter tubes that are widely used in petroleum industries and power plants experience corrosion during long-term services. In this paper, a compact inserted guided-wave EMAT with a pulsed electromagnet is proposed for small-diameter tube inspection. The proposed transducer is noncontact, compact with high signal-to-noise ratio and unattractive to ferromagnetic tubes. The proposed EMAT is designed with coils-only configuration, which consists of a pulsed electromagnet and a meander pulser/receiver coil. Both the numerical simulation and experimental results validate its feasibility on generating and receiving L(0,2) mode guided wave. The parameters for driving the proposed EMAT are optimized by performance testing. Finally, feasibility on quantification evaluation for corrosion defects was verified by experiments.

Application of Novel Low Current OBIRCH Amplifier and Nanoprobing to Identify Subtle Leakages in Advanced Node Technologies

2018 ◽  
Author(s):  
Satish Kodali ◽  
Liangshan Chen ◽  
Yuting Wei ◽  
Tanya Schaeffer ◽  
Chong Khiam Oh
Keyword(s):  
Signal To Noise Ratio ◽  
Semiconductor Industry ◽  
Fault Isolation ◽  
Ring Oscillator ◽  
High Signal ◽  
The Novel ◽  
Resistance Change ◽  
Three Samples ◽  
Relative Threshold ◽  
First Time

Abstract Optical beam induced resistance change (OBIRCH) is a very well-adapted technique for static fault isolation in the semiconductor industry. Novel low current OBIRCH amplifier is used to facilitate safe test condition requirements for advanced nodes. This paper shows the differences between the earlier and novel generation OBIRCH amplifiers. Ring oscillator high standby leakage samples are analyzed using the novel generation amplifier. High signal to noise ratio at applied low bias and current levels on device under test are shown on various samples. Further, a metric to demonstrate the SNR to device performance is also discussed. OBIRCH analysis is performed on all the three samples for nanoprobing of, and physical characterization on, the leakage. The resulting spots were calibrated and classified. It is noted that the calibration metric can be successfully used for the first time to estimate the relative threshold voltage of individual transistors in advanced process nodes.

scholarly journals VS2 as saturable absorber for Q-switched pulse generation

Nanophotonics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 2569-2576 ◽  
Author(s):  
Lu Li ◽  
Lihui Pang ◽  
Qiyi Zhao ◽  
Yao Wang ◽  
Wenjun Liu
Keyword(s):  
Saturable Absorber ◽  
Nonlinear Optical ◽  
Modulation Depth ◽  
Signal To Noise Ratio ◽  
Transition Metal Dichalcogenides ◽  
Laser Cavity ◽  
Pulse Generation ◽  
High Signal ◽  
Power Pulse ◽  
Metal Dichalcogenides

AbstractTransition metal dichalcogenides have been widely utilized as nonlinear optical materials for laser pulse generation applications. Herein, we study the nonlinear optical properties of a VS2-based optical device and its application as a new saturable absorber (SA) for high-power pulse generation. Few-layer VS2 nanosheets are deposited on the tapered region of a microfiber to form an SA device, which shows a modulation depth of 40.52%. After incorporating the microfiber-VS2 SA into an Er-doped fiber laser cavity, passively Q-switched pulse trains could be obtained with repetition rates varying from 95 to 233 kHz. Under the pump power of 890 mW, the largest output power and shortest pulse duration are measured to be 43 mW and 854 ns, respectively. The high signal-to-noise ratio of 60 dB confirms the excellent stability of the Q-switching state. To the best of our knolowdge, this is the first illustration of using VS2 as an SA. Our experimental results demonstrate that VS2 nanomaterials have a large potential for nonlinear optics applications.

Probability-based diagnostic imaging with corrected weight distribution for damage detection of stiffened composite panel

2021 ◽  
pp. 147592172110339
Author(s):  
Guoqiang Liu ◽  
Binwen Wang ◽  
Li Wang ◽  
Yu Yang ◽  
Xiaguang Wang
Keyword(s):  
Distribution Function ◽  
Diagnostic Imaging ◽  
Weight Distribution ◽  
Composite Structures ◽  
Damage Identification ◽  
Guided Wave ◽  
Composite Panel ◽  
Damage Localization ◽  
Localization Accuracy ◽  
Direct Interpretation

Due to no requirement for direct interpretation of the guided wave signal, probability-based diagnostic imaging (PDI) algorithm is especially suitable for damage identification of complex composite structures. However, the weight distribution function of PDI algorithm is relatively inaccurate. It can reduce the damage localization accuracy. In order to improve the damage localization accuracy, an improved PDI algorithm is proposed. In the proposed algorithm, the weight distribution function is corrected by the acquired relative distances from defects to all actuator–sensor pairs and the reduction of the weight distribution areas. The validity of the proposed algorithm is assessed by identifying damages at different locations on a stiffened composite panel. The results show that the proposed algorithm can identify damage of a stiffened composite panel accurately.

scholarly journals Detection and localization of multiple small damages in beam

2021 ◽  
Vol 13 (1) ◽  
pp. 168781402098732
Author(s):  
Ayisha Nayyar ◽  
Ummul Baneen ◽  
Syed Abbas Zilqurnain Naqvi ◽  
Muhammad Ahsan
Keyword(s):  
Frequency Response ◽  
Natural Frequencies ◽  
Signal To Noise Ratio ◽  
Moving Average ◽  
A Priori ◽  
Damage Index ◽  
High Signal ◽  
Frequency Range ◽  
Spatial Locality ◽  
System Frequency

Localizing small damages often requires sensors be mounted in the proximity of damage to obtain high Signal-to-Noise Ratio in system frequency response to input excitation. The proximity requirement limits the applicability of existing schemes for low-severity damage detection as an estimate of damage location may not be known  a priori. In this work it is shown that spatial locality is not a fundamental impediment; multiple small damages can still be detected with high accuracy provided that the frequency range beyond the first five natural frequencies is utilized in the Frequency response functions (FRF) curvature method. The proposed method presented in this paper applies sensitivity analysis to systematically unearth frequency ranges capable of elevating damage index peak at correct damage locations. It is a baseline-free method that employs a smoothing polynomial to emulate reference curvatures for the undamaged structure. Numerical simulation of steel-beam shows that small multiple damages of severity as low as 5% can be reliably detected by including frequency range covering 5–10th natural frequencies. The efficacy of the scheme is also experimentally validated for the same beam. It is also found that a simple noise filtration scheme such as a Gaussian moving average filter can adequately remove false peaks from the damage index profile.

scholarly journals Understanding PI-QUAL for prostate MRI quality: a practical primer for radiologists

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Francesco Giganti ◽  
Alex Kirkham ◽  
Veeru Kasivisvanathan ◽  
Marianthi-Vasiliki Papoutsaki ◽  
Shonit Punwani ◽  
...  
Keyword(s):  
Diffusion Weighted Imaging ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Diagnostic Quality ◽  
Prostate Mri ◽  
Prostate Imaging ◽  
Dynamic Contrast Enhanced ◽  
Diffusion Weighted ◽  
Contrast Enhanced

AbstractProstate magnetic resonance imaging (MRI) of high diagnostic quality is a key determinant for either detection or exclusion of prostate cancer. Adequate high spatial resolution on T2-weighted imaging, good diffusion-weighted imaging and dynamic contrast-enhanced sequences of high signal-to-noise ratio are the prerequisite for a high-quality MRI study of the prostate. The Prostate Imaging Quality (PI-QUAL) score was created to assess the diagnostic quality of a scan against a set of objective criteria as per Prostate Imaging-Reporting and Data System recommendations, together with criteria obtained from the image. The PI-QUAL score is a 1-to-5 scale where a score of 1 indicates that all MR sequences (T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced sequences) are below the minimum standard of diagnostic quality, a score of 3 means that the scan is of sufficient diagnostic quality, and a score of 5 implies that all three sequences are of optimal diagnostic quality. The purpose of this educational review is to provide a practical guide to assess the quality of prostate MRI using PI-QUAL and to familiarise the radiologist and all those involved in prostate MRI with this scoring system. A variety of images are also presented to demonstrate the difference between suboptimal and good prostate MR scans.

Narrow-frequency sharp-angular filters using all-dielectric cascaded meta-gratings

Nanophotonics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 3443-3450 ◽  
Author(s):  
Wei-Nan Liu ◽  
Rui Chen ◽  
Wei-Yi Shi ◽  
Ke-Bo Zeng ◽  
Fu-Li Zhao ◽  
...  
Keyword(s):  
Thin Film ◽  
Signal To Noise Ratio ◽  
Incident Angle ◽  
Design Strategy ◽  
Transmission Peak ◽  
High Signal ◽  
Waveguide Array ◽  
Signal To Noise ◽  
Center Wavelength ◽  
Noise Ratio

AbstractSelective transmission or filtering always responds to either frequency or incident angle, so as hardly to maximize signal-to-noise ratio in communication, detection and sensing. Here, we propose compact meta-filters of narrow-frequency sharp-angular transmission peak along with broad omnidirectional reflection sidebands, in all-dielectric cascaded subwavelength meta-gratings. The inherent collective resonance of waveguide-array modes and thin film approximation of meta-grating are employed as the design strategy. A unity transmission peak, locating at the incident angle of 44.4° and the center wavelength of 1550 nm, is demonstrated in a silicon meta-filter consisting of two-layer silicon rectangular meta-grating. These findings provide possibilities in cascaded meta-gratings spectroscopic design and alternative utilities for high signal-to-noise ratio applications in focus-free spatial filtering and anti-noise systems in telecommunications.

scholarly journals Mid-infrared photoacoustic gas monitoring driven by a gas-filled hollow-core fiber laser

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yazhou Wang ◽  
Yuyang Feng ◽  
Abubakar I. Adamu ◽  
Manoj K. Dasa ◽  
J. E. Antonio-Lopez ◽  
...  
Keyword(s):  
Fiber Laser ◽  
Signal To Noise Ratio ◽  
High Sensitivity ◽  
Laser Source ◽  
High Signal ◽  
Mid Infrared ◽  
Raman Fiber Laser ◽  
Custom Made ◽  
Core Fiber ◽  
Detection Technologies

AbstractDevelopment of novel mid-infrared (MIR) lasers could ultimately boost emerging detection technologies towards innovative spectroscopic and imaging solutions. Photoacoustic (PA) modality has been heralded for years as one of the most powerful detection tools enabling high signal-to-noise ratio analysis. Here, we demonstrate a novel, compact and sensitive MIR-PA system for carbon dioxide (CO2) monitoring at its strongest absorption band by combining a gas-filled fiber laser and PA technology. Specifically, the PA signals were excited by a custom-made hydrogen (H2) based MIR Raman fiber laser source with a pulse energy of ⁓ 18 μJ, quantum efficiency of ⁓ 80% and peak power of ⁓ 3.9 kW. A CO2 detection limit of 605 ppbv was attained from the Allan deviation. This work constitutes an alternative method for advanced high-sensitivity gas detection.

scholarly journals A Self-Powered and Highly Accurate Vibration Sensor Based on Bouncing-Ball Triboelectric Nanogenerator for Intelligent Ship Machinery Monitoring

Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 218
Author(s):  
Taili Du ◽  
Xusheng Zuo ◽  
Fangyang Dong ◽  
Shunqi Li ◽  
Anaeli Elibariki Mtui ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Work Conditions ◽  
Copper Electrode ◽  
Vibration Sensor ◽  
High Signal ◽  
Triboelectric Nanogenerator ◽  
Vibration Exciter ◽  
Bouncing Ball ◽  
3D Printed ◽  
Self Powered

With the development of intelligent ship, types of advanced sensors are in great demand for monitoring the work conditions of ship machinery. In the present work, a self-powered and highly accurate vibration sensor based on bouncing-ball triboelectric nanogenerator (BB-TENG) is proposed and investigated. The BB-TENG sensor consists of two copper electrode layers and one 3D-printed frame filled with polytetrafluoroethylene (PTFE) balls. When the sensor is installed on a vibration exciter, the PTFE balls will continuously bounce between the two electrodes, generating a periodically fluctuating electrical signals whose frequency can be easily measured through fast Fourier transform. Experiments have demonstrated that the BB-TENG sensor has a high signal-to-noise ratio of 34.5 dB with mean error less than 0.05% at the vibration frequency of 10 Hz to 50 Hz which covers the most vibration range of the machinery on ship. In addition, the BB-TENG can power 30 LEDs and a temperature sensor by converting vibration energy into electricity. Therefore, the BB-TENG sensor can be utilized as a self-powered and highly accurate vibration sensor for condition monitoring of intelligent ship machinery.

scholarly journals Damage Identification of Long-Span Bridges Using the Hybrid of Convolutional Neural Network and Long Short-Term Memory Network

Algorithms ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 180
Author(s):  
Lei Fu ◽  
Qizhi Tang ◽  
Peng Gao ◽  
Jingzhou Xin ◽  
Jianting Zhou
Keyword(s):  
Short Term Memory ◽  
Damage Identification ◽  
Identification Accuracy ◽  
Damage Localization ◽  
Short Term ◽  
Term Memory ◽  
Localization Accuracy ◽  
Long Span Bridges ◽  
Long Span ◽  
Long Short Term Memory

The shallow features extracted by the traditional artificial intelligence algorithm-based damage identification methods pose low sensitivity and ignore the timing characteristics of vibration signals. Thus, this study uses the high-dimensional feature extraction advantages of convolutional neural networks (CNNs) and the time series modeling capability of long short-term memory networks (LSTM) to identify damage to long-span bridges. Firstly, the features extracted by CNN and LSTM are fused as the input of the fully connected layer to train the CNN-LSTM model. After that, the trained CNN-LSTM model is employed for damage identification. Finally, a numerical example of a large-span suspension bridge was carried out to investigate the effectiveness of the proposed method. Furthermore, the performance of CNN-LSTM and CNN under different noise levels was compared to test the feasibility of application in practical engineering. The results demonstrate the following: (1) the combination of CNN and LSTM is satisfactory with 94% of the damage localization accuracy and only 8.0% of the average relative identification error (ARIE) of damage severity identification; (2) in comparison to the CNN, the CNN-LSTM results in superior identification accuracy; the damage localization accuracy is improved by 8.13%, while the decrement of ARIE of damage severity identification is 5.20%; and (3) the proposed method is capable of resisting the influence of environmental noise and acquires an acceptable recognition effect for multi-location damage; in a database with a lower signal-to-noise ratio of 3.33, the damage localization accuracy of the CNN-LSTM model is 67.06%, and the ARIE of the damage severity identification is 31%. This work provides an innovative idea for damage identification of long-span bridges and is conducive to promote follow-up studies regarding structural condition evaluation.

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