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37th IEEE International Conference on Micro Electro Mechanical Systems (MEMS)

作者： Zhen, Liyun Zhai, Yueqi Zhu, Xiantao Xu, Mengfei Li, Yizhi Liu, Jingquan Yang, Bin Shanghai Jiao Tong Univ Natl Key Lab Adv Micro & Nano Mfg Technol Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Dept Micro Nano Elect Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9798350357929

This paper reports a wearable piezoelectric pressure MEMS sensor array for multi-site conformal sensing of pulse waves. Thinned bulk lead zirconate titanate (PZT) piezoceramic films with high performance are embedded into soft materials, allowing optimal deformability and conformality. Specifically, a spin-on polymeric adhesive is adopted to transfer uniform PZT film during bonding and releasing processes. As a result, the device of single element exhibits high sensitivity with 47.45 mV/N. Furthermore, it can capture a weak pulse with the spatial and temporal distribution without cross talk among channels, which has great potential applications in the diagnosis of cardiovascular disease.

关键词： Conformal Design piezoelectric sensor array Pulse Perception Spatiotemporal Distribution

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Gain-Phase Error-Calibrated piezoelectric sensor array-Based Impact Localization on Stiffened Curved Composite Structures

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sensorS 2022年第15期22卷 5879-5879页

作者： Wang, Zhiling Zhou, Jinyu Zhong, Yongteng Li, Chaoyue Jinling Inst Technol Sch Mech & Elect Engn Nanjing 211169 Peoples R China Wenzhou Univ Coll Mech & Elect Engn Wenzhou 325035 Peoples R China

Stiffened structure-induced gain-phase errors degrade the performance of the high-resolution two-dimensional multiple signal classification (2D-MUSIC) algorithm, which makes it impossible to ensure the high accuracy of impact localization results. To eliminate the localization bias caused by these errors, a calibrated 2D-MUSIC-based impact localization method is first introduced. Firstly, time-frequency characteristics of the non-stationary impact signals are evaluated by experiment to obtain a clear first wave packet or a wave packet that purely corresponds to a single mode through continuous wavelet transform (CWT). Then, the uniform linear array covariance matrix with gain-phase errors is calibrated to be constructed as a Toeplitz structural matrix. By reconstructing covariance matrix R, 2D-MUSIC-based impact localization is calibrated for stiffened curved composite structures. Experimental research on the stiffened curved composite panel is carried out, and these impact localization results demonstrate the validity and effectiveness of the calibrated 2D-MUSIC-based method.

关键词： stiffened curved panels piezoelectric sensor array calibrated 2D-MUSIC impact localization

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Multipoint detection of structural deformation of pulsating 3D heart model using flexible organic piezoelectric-sensor array

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JAPANESE JOURNAL OF APPLIED PHYSICS 2022年第SE期61卷 SE1014页

作者： Nagayama, Yusaku Kondo, Yuya Koshiba, Yasuko Horike, Shohei Takashima, Kazuto Ishida, Kenji Kobe Univ Grad Sch Engn Dept Chem Sci & Engn Nada Ku 1-1 Rokkodai Cho Kobe Hyogo 6578501 Japan Kobe Univ Res Ctr Membrane & Film Technol Nada Ku 1-1 Rokkodai Cho Kobe Hyogo 6578501 Japan Japan Sci & Technol Agcy PRESTO Kawaguchi Saitama 3320012 Japan Kyushu Inst Technol Grad Sch Life Sci & Syst Engn Wakamatsu Ku 2-4 Hibikino Kitakyushu Fukuoka 8080196 Japan

Multipoint detection of the structural deformation of a pulsating 3D heart model was conducted using a flexible piezoelectric sensor array with a poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)] thin film sealed with biocompatible parylene C. The piezoelectric signals detected from the sensor array attached to the 3D heart model were correlated with an electrocardiogram signal. These piezoelectric signals can be converted into the compressive stress applied to the flexible sensors by the pulsating motion of the 3D heart model. The experimental results mean that the contraction force, generated by the heart muscle (i.e., myocardium), can be directly evaluated. The different output voltages depending on the location were obtained from each sensor, indicating the possibility of a real-time detection of the irregular motion of the heart and the early detection of ischemic heart disease, which leads to the loss of local contractile force in myocardial tissue.

关键词： flexible sensor piezoelectric sensor array implantable sensor multipoint detection heartbeat

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Identification of temperature variation and vibration disturbance in impedance-based structural health monitoring using piezoelectric sensor array method

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STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL 2012年第3期11卷 305-314页

作者： Bastani, Ali Amindavar, Hamidreza Shamshirsaz, Mahnaz Sepehry, Naserodin Amirkabir Univ Technol Dept Elect Engn Tehran *** Iran Amirkabir Univ Technol New Technol Res Ctr Tehran *** Iran Amirkabir Univ Technol Dept Mech Engn Tehran *** Iran

Impedance-based structural health monitoring (ISHM) using piezoelectric materials has been extensively developed to provide a structure health indicator. In practice, due to the environmental disturbances, the received signal in different surrounding conditions may be different from intact structure received signal. In the past, any difference was assumed being caused by damage even changes such as temperature effects on the received signal. In ISHM, the received signal is different from the intact structure received signal;however, there is not necessarily damage in the system. So, the validity of ISHM depends on the identification of environmental disturbances in order to extract the real results from disturbed results. In this article, a new method using sensor array and statistical metric analysis has been proposed to identify signal changes derived from damage and/or environmental change. Using this method, it is expected that the environmental variations affect similarly on output signals of different row sensors, whereas changes caused by damage will not be similar for all row and column sensors. This expectation is a general fact because there would be no sensible difference in the environmental variations from one side to other sides of the structure. To identify environmental disturbance from damage detection, an analysis is developed using statistical metrics. Experimental results show that this method is reliable to identify damage.

关键词： piezoelectric sensor array health monitoring environmental effects temperature vibration

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Application of principal component analysis and discriminant analysis using latent structure regression to the identification of highly volatile organic compounds in gas mixtures based on piezoelectric quartz microweighing parameters

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JOURNAL OF ANALYTICAL CHEMISTRY 2013年第7期68卷 652-661页

作者： Kuchmenko, T. A. Pogrebnaya, D. A. Shuba, A. A. Voronezh State Univ Engn Technol Fac Ecol & Chem Technol Voronezh 394000 Russia

The applicability of the new parameters of piezoelectric quartz microweighing and principal component and discriminant analysis with the use of latent structure regression to the treatment of the output data of an array of piezoelectric sensors in the identification of individual highly volatile compounds in model three-component gas mixtures is discussed. The parameters proposed and the methods of chemometrics were used in the treatment of the multidimensional data of an electronic nose for detecting individual aromaforming compounds and evaluating changes in the aroma of food systems with functional additives.

关键词： piezoelectric sensor array food systems identification parameters organic compounds regression analysis discriminant analysis standard reference method principal component analysis

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A piezoelectric quartz crystal sensor array self assembled calixarene bilayers for detection of volatile organic amine in gas

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TALANTA 2002年第6期57卷 1181-1188页

作者： Wang, C He, XW Chen, LX Nankai Univ Dept Chem Tianjin 300071 Peoples R China

P-tert-butylcalix[n]arenes (n = 4, 6, 8, abbreviated as CA[4], CA[6], CA[8], respectively) were immobilized on the An surface of the piezoelectric quartz crystal by the reaction between CA[n] and the acid chloride terminated mercaptoacetic acid (MAA) self assembled monolayers to form MAA/CA[n] bilayers. The sensing films were not only immobilized easily and reproducibly, but also used to improve the reversibility of the sensor signal. The response characteristics show the response of CA to organic amine attributes to specific interaction between CA[n] (host) and organic amines (guest). The frequency shifts of n-butylamine and iso-butylamine are much larger than tert-butylamine and diethylamine because of shape-selection and hydrogen bonding. Compared to CA[6] and CA[4], CA[8] has highest sensitivity to organic amine due to having more flexibility to accommodate guest molecules. A sensor array with three-layer back-propagation neural network was applied to detect the binary mixture of n-butylamine in the range of 7.14-142 mul l(-1) and iso-butylamine in the range of 7.14-57 mul l(-1). The optimum values of learning rate (0.15) and momentum term (0.8) were determined by experiment. The best epoch of training was 1098. The root mean square error of prediction was 1.69 (mul l(-1)) for n-butylamine, and 1.42 (mul l(-1)) for iso-butylamine. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： organic amine calixarenes self-assembly artificial neural network piezoelectric sensor array

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Application of an artificial neural network (ANN) and piezoelectric chemical sensor array for identification of volatile organic compounds

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TALANTA 1997年第12期44卷 2237-2245页

作者： Barko, G Hlavay, J UNIV VESZPREM DEPT EARTH & ENVIRONM SCIH-8201 VESZPREMHUNGARY

A piezoelectric chemical sensor array was developed using four quartz crystals. Gas chromatographic stationary phases were used as sensing materials and the array was connected to an artificial neural network (ANN). The application of the ANN method proved to be particularly advantageous if the measured property (mass, concentration, etc.) should not be connected exactly to the signal of the transducers of the piezoelectric sensor. The optimum structure of neural network was determined by a trial and error method. Different structures were tried with several neurons in the hidden layer and the total error was calculated. The optimum values of primary weight factors, learning rate (eta = 0.15), momentum term (mu = 0.9), and the sigmoid parameter (beta = 1) were determined. Finally, three hidden neurons and 900 training cycles were applied. After the teaching process the network was used for identification of taught analytes (acetone, benzene, chloroform, pentane). Mixtures of organic compounds were also analysed and the ANN method proved to be a reliable way of differentiating the sensing materials and identifying the volatile compounds. (C) 1997 Elsevier Science B.V.

关键词： piezoelectric sensor array artificial neural network identification of organic compounds

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Application of principal component analysis for the characterisation of a piezoelectric sensors array

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ANALYTICA CHIMICA ACTA 1998年第1-3期367卷 135-143页

作者： Barkó, G Hlavay, J Univ Veszprem Dept Earth & Environm Sci H-8201 Veszprem Hungary

A piezoelectric sensor array was developed using four quartz crystals. For sensing materials gas chromatographic stationary phases were used. Factor analysis was performed and the weight of the factors was applied to characterise the selectivity of the sensing materials. The identification of some organic vapours was carried out by the sensor array. Principal component analysis was used and the signals were transformed into feature space. It was found that the transformed values of chloroform, acetone and cyclohexane were well separated. The data for the aromatic hydrocarbons were situated near the pixels of methanol and pentane. Organic materials can be identified in a mixture if the calculated factors are different. Interference has been found between benzene and toluene due to their similar factors. The selectivity of the chemical sensor array can be greatly improved using more sensing elements in one array and sensing compounds with very different chemical features. (C) 1998 Elsevier Science B.V.

关键词： piezoelectric sensor array factor analysis identification of organic compounds

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