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Ultra‑High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

Nano-Micro Letters 2025年第2期17卷 432-446页

作者： Hao Yin Yanting Li Zhiying Tian Qichao Li Chenhui Jiang Enfu Liang Yiping Guo State Key Laboratory of Metal Matrix Composites School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China Beijing Vacuum Electronics Research Institute Beijing 100015People’s Republic of China Fundamental Science On Vibration Shock and Noise LaboratoryState Key Laboratory of Mechanical System and VibrationSchool of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing ***,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also ***,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic *** as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse *** ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate ***,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%*** structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.

关键词： Flexible piezoelectric filaments Anisotropic Ultra-high sensitivity Structural health detection texture recognition

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People recognition via Tongue Print Using Deep and Machine Learning

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Journal of Artificial Intelligence and Technology 2023年第3期3卷 119-125页

作者： Ahmed Shallal Obaid Mohammed Y.Kamil Basaad Hadi Hamza College of Science Mustansiriyah UniversityBaghdadIraq

The tongue is a unique organ that is well protected inside the mouth and not affected by external factors;it is also difficult to *** biometric systems are widely used for authentication and recognition,such as fingerprints,faces,iris,sound,and *** biometrics represent a challenge and an obstacle as they can be falsified,duplicates can be made(e.g.,iris,face,fingers,and signature),or they are expensive and rarely used(e.g.,DNA).The increased security measures called for modern biometrics that is more secure,less expensive,and cannot be *** a result,the goal of this paper is to create a system for distinguishing people based on their tongue *** will contribute to solving many forensic issues and increasing electronic security because it has features suitable for identification and biometrically distinguishing between *** this paper,the tongue is located based on the fixed window size *** tongue localization,feature extraction using the VGG-16 model,and a classification system that uses both transfer learning and machine learning as VGG-16,XGBoost,KNN,and random forest classifiers,extracted features are then trained for personal *** dataset consisted of 1085 tongue images of 138 people with a test ratio of 20%,and the results achieved an accuracy of 92%.The process of distinguishing people through tongue prints has proven to be effective and accurate.

关键词： pattern recognition ROI texture recognition tongue VGG-16

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