Estimation of some transducer parameters in a broadband piezoelectric transmitter by using an artificial intelligence technique

An estimation procedure to efficiently find approximate values of internal parameters in ultrasonic transducers intended for broadband operation would be a valuable tool to discover internal construction data. This information is necessary in the modelling and simulation of acoustic and electrical behaviour related to ultrasonic systems containing commercial transducers. There is not a general solution for this generic problem of parameter estimation in the case of broadband piezoelectric probes. In this paper, this general problem is briefly analysed for broadband conditions. The viability of application in this field of an artificial intelligence technique supported on the modelling of the transducer internal components is studied. A genetic algorithm (GA) procedure is presented and applied to the estimation of different parameters, related to two transducers which are working as pulsed transmitters. The efficiency of this GA technique is studied, considering the influence of the number and variation range of the estimated parameters. Estimation results are experimentally ratified.     

Phase transition and mechanical properties of tungsten nanomaterials from molecular dynamic simulation

Molecular dynamic simulation is used to systematically find out the effects of the size and shape of nanoparticles on phase transition and mechanical properties of W nanomaterials. It is revealed that the body-centered cubic (BCC) to face-centered cubic (FCC) phase transition could only happen in cubic nanoparticles of W, instead of the shapes of sphere, octahedron, and rhombic dodecahedron, and that the critical number to trigger the phase transition is 5374 atoms. Simulation also shows that the FCC nanocrystalline W should be prevented due to its much lower tensile strength than its BCC counterpart and that the octahedral and rhombic dodecahedral nanoparticles of W, rather than the cubic nanoparticles, should be preferred in terms of phase transition and mechanical properties. The derived results are discussed extensively through comparing with available observations in the literature to provide a deep understanding of W nanomaterials.     

近红外光谱法分析慈竹物理力学性质的研究

采用近红外光谱法对慈竹密度、抗弯强度和顺纹抗拉强度进行快速预测.利用反向区间偏最小二乘法(BiPIS)优选光谱区间,建立原始光谱和不同预处理(一阶微分、二阶微分、卷积平滑和归一化处理)光谱分析模型,同时应用偏最小二乘法(PLS)在全谱范围350～2 500 nm建立各光谱分析模唰,并对所建模型进行比较分析.结果表明:同...     

Feasibility of gem identification using reflectance spectra coupled with artificial intelligence

Abstract

Standard traditional gem identification requires expert supervision, while sophisticated modern methods are time-consuming and expensive. In contrast, reflectance spectroscopy coupled with artificial intelligence is economical and convenient and does not require specialist supervision. This study established an artificial neural network model that consists of standard multilayered, feed-forward, and back-propagation neural networks, and obtained reflectance spectra of a transparent gem (almandine), an opaque gem (turquoise), several almandine imitations (agate, plastic, and glass), and several treated turquoise samples (dyed, impregnated, and Zachery treated) using an Analytical Spectral Devices spectrometer. The acquired spectra were used to train and test the artificial neural network model. The results show that the model can effectively discriminate between genuine and imitation gems of different classes. However, discrimination between natural and treated gems of same class is not as effective as discrimination of gems of different classes. The results suggest that an artificial neural network based on reflectance spectroscopy could serve as a useful tool for preliminary gem identification, and the advanced identification needs further training and investigation.     

Interfacial properties of hybrid nanomaterials

A brief summary of our ongoing efforts to understand the surface properties of nanoparticles using fluorophores, namely pyrene alkanethiols, is presented. Excited state interactions were investigated by varying the length of the spacer group and the concentration of fluorophore. The flexible long alkyl chain tethering pyrene inAu-P2/Au-P3 allows free interaction between fluorophores resulting in excimer formation whereas the intermolecular interactions are limited in theAu-P 1 system due to the restriction imposed by the curvature of spherical gold nanoparticle. A gradual increase in the peak intensity ratio of III/I band of the normal fluorescence of pyrene was observed indicating that the surface of nanoparticle is more polar than the bulk solvent (toluene)     

Estimation of multiple sound source directions using artificial robot ears

Estimating the direction of a sound source is an important technique used in various engineering fields, including intelligent robots and surveillance systems. In a household where a user’s voice and noises emitted from electric appliances originate from arbitrary directions in 3-D space, robots need to recognize the directions of multiple sound sources in order to effectively interact with the user.This paper proposes an ear-based estimation (localization) system using two artificial robot ears, each consisting of a spiral-shaped pinna and two microphones, for application in humanoid robots. Four microphones are asymmetrically placed on the left and right sides of the head. The proposed localization algorithm is based on a spatially mapped generalized cross-correlation function which is transformed from the time domain to the space domain by using a measured inter-channel time difference map. For validation of the proposed localization method, two experiments (single- and multiple-source cases) were conducted using male speech. In the case of a single source, with the exception of laterally biased sources, the localization was achieved with an error of less than 10°. In a multiple-source environment, one source was fixed at the front side and the other source changed its direction; from the experimental results, the error rates on the localization of the fixed and varying sources are 0% and 36.9% respectively within an error bound of 15°.     

Estimation of mechanical properties of a viscoelastic medium using a laser-induced microbubble interrogated by an acoustic radiation force

An approach to assess the mechanical properties of a viscoelastic medium using laser-induced microbubbles is presented. To measure mechanical properties of the medium, dynamics of a laser-induced cavitation microbubble in viscoelastic medium under acoustic radiation force was investigated. An objective lens with a 1.13 numerical aperture and an 8.0 mm working distance was designed to focus a 532 nm wavelength nanosecond pulsed laser beam and to create a microbubble at the desired location. A 3.5 MHz ultrasound transducer was used to generate acoustic radiation force to excite a laser-induced microbubble. Motion of the microbubble was tracked using a 25 MHz imaging transducer. Agreement between a theoretical model of bubble motion in a viscoelastic medium and experimental measurements was demonstrated. Young's modulii reconstructed using the laser-induced microbubble approach were compared with those measured using a direct uniaxial method over the range from 0.8 to 13 kPa. The results indicate good agreement between methods. Thus, the proposed approach can be used to assess the mechanical properties of a viscoelastic medium.     

Mechanical properties of bulk carbon nanomaterials

Bulk carbon nanomaterials, which open prospects for the development of a new generation of supercapacitors, are actively investigated for recent years, but their mechanical properties and structure remain poorly understood. In connection with this fact, the influence of the hydrostatic and uniaxial compression on mechanical properties and structure of three bulk nanomaterials consisting of (i) bent graphene flakes, (ii) short carbon nanotubes, and (iii) fullerenes C₂₄₀ are investigated by the molecular dynamics method. It is shown that the strength of the material and its stability to graphitization depend on its constituent structural units. At large degrees of deformation, the material consisting of bent graphene sheets has the highest strength, whereas at the material density lower than 2.5 g/cm³, the highest strength is observed in the nanomaterial consisting of fullerene molecules. The differences in mechanical properties of the materials under consideration are explained by their structural features.     

Tuning fractional PID controllers for a Steward platform based on frequency domain and artificial intelligence methods

In this paper, two methods to tune a fractional-order PI ^λ D ^μ controller for a mechatronic system are presented. The first method is based on a genetic algorithm to obtain the parameter values for the fractionalorder PI ^λ D ^μ controller by global optimization. The second method used to design the fractional-order PI ^λ D ^μ controller relies on an auto-tuning approach by meeting some specifications in the frequency domain. The real-time experiments are conducted using a Steward platform which consists of a table tilted by six servo-motors with a ball on the top of the table. The considered system is a 6 degrees of freedom (d.o.f.) motion platform. The feedback on the position of the ball is obtained from images acquired by a visual sensor mounted above the platform. The fractional-order controllers were implemented and the performances of the steward platform are analyzed.     

Electrochemical properties of polyaniline-modified sodium vanadate nanomaterials

Sodium vanadate nanomaterials were synthesized at different pH-values of a sodium hydroxide solution of vanadium pentoxide. Polyaniline-modified sodium vanadate nanomaterials were prepared at room temperature and at 3°C by a chemical polymerization method. The crystal structure and phase purity of the samples have been examined by powder XRD. The samples were identified as HNaV₆O₁₆⋅4H₂O and Na_1.1V₃O_7.9. The electrochemical measurements show that polyaniline-modified sodium vanadate hydrated nanomaterials provide higher current density than the sodium vanadate nanomaterials.     

Microstructure characterization and magnetic properties of nanomaterials

The microstructure and superparamagnetic properties of two systems of magnetic nano-particles are reviewed. A new type of magnetic core-shell Ni—Ce nanocomposite particle (15–50 nm) has been prepared. Typical HREM images and FFT patterns of HREM images showed that many planar defects (nanotwins and stacking faults) exist in the large Ni core zone (10–45 nm). The shell layers (3–5 nm) consist of an innermost Ni—Ce alloy and an outermost NiO oxide. FFT patterns from different regions of typical HREM images show well defined spots characteristic of core-shell nanocomposite materials. Magnetization measurements as a function of magnetic field and temperature showed that superparamagnetic behaviour is exhibited above the average block temperature (T_B = 170 K). This superpara-magnetic relaxation was found to be modified by interparticle interactions that depend on the applied field and size distribution. In addition, antiferromagnetic order occurred with a Neél temperature T_N of about 11 K. A spin-flip transition was observed below T_N at a certain applied field. Novel carbon encapsulated Ni nanoparticles assemblies have been synthesized by modified arc-discharge under a methane atmosphere. The presence of carbon encapsulation is confirmed by HR-TEM lattice imaging, and nanodiffraction. The intimate and contiguous carbon fringe around these Ni nanoparticles is good evidence for complete encapsulation by carbon shell layers. Superparamagnetic property studies show that the blocking temperature T_B is around 115K at 0.1 T applied field. Above T_B, the magnetization M(H,T) can be described by the classical Langevin function L using the relation M/M_s(T = 0) = coth (μH/kT) — kT/μH. The particle size can be inferred from the Langevin fit (particle moment μ), which is a little larger than the HR-TEM observation. It is suggested that these assemblies of carbon encapsulated Ni nanoparticles have typical single-domain, field-dependent superparamagnetic relaxation properties, and this typical superparamagnetic behaviour is consistent with the Stoner—Wohlfarth theory of single-domain particles.     

Simulating the mechanical response of amorphous solids using atomistic methods

The study of elasticity, plasticity and failure in non-crystalline solids has greatly benefitted from the application of atomic scale simulation. This “colloquium paper" reviews the ways in which a variety of computational approaches have been used to elucidate the atomic scale phenomena that control the mechanics of amorphous solids. The constitutive theories that have been developed for describing mechanical response are briefly reviewed, as well as the prospects for testing the assumptions of these theories using simulation. We list what we believe to be the most pressing open questions for substantiating these theoretical approaches, and ultimately for understanding and predicting the mechanical responses of amorphous solids.     

An application of artificial neural intelligence for personal dose assessment using a multi-area OSL dosimetry system

Significant advances have been made in recent years to improve measurement technology and performance of phosphor materials in the fields of optically stimulated luminescence (OSL) dosimetry. Pulsed and continuous wave OSL studies recently carried out on alpha-Al2O3:C have shown that the material seems to be the most promising for routine application of OSL for dosimetric purposes. The main objective of the study is to propose a new personal dosimetry system using alpha-Al2O3:C by taking advantage of its optical properties and energy dependencies. In the process of the study, a new dose assessment algorithm was developed using artificial neural networks in hopes of achieving a higher degree of accuracy and precision in personal OSL dosimetry system. The original hypothesis of this work is that the spectral information of X- and gamma-ray fields may be obtained by the analysis of the response of a multi-element system. In this study, a feedforward neural network using the error back-propagation method with Bayesian optimization was applied for the response unfolding procedure. The validation of the proposed algorithm was investigated by unfolding the 10 measured responses of alpha-Al2O3:C for arbitrarily mixed photon fields which range from 20 to 662 keV.     

Determine mechanical properties of particulate composite using ultrasound spectroscopy

It is known that microscopic spherulite growth plays an important role in macroscopical properties such as elastic moduli of some semicrystalline polymers. Ultrasonic spectroscopy can be used to quantitatively determine the role of spherulites. As a first approximation, spherulitic polymers are modeled as a material with spherical inclusions in an amorphous matrix. This two-phase composite model is then physically realized by embedding glass micro-spheres in an epoxy. The dynamic mechanical properties of these composites are experimentally determined by measuring their acoustic properties such as phase velocity and attenuation. Acoustic scattering theories are then applied to this model to test their predictive capabilities for the real composite's mechanical properties.     

低维纳米材料热电性能测试方法研究

通过近几十年的研究,人们对于块体及薄膜材料的热电性能已经有了较全面的认识,热电优值ZT的提高取得了飞速的进展,比如碲化铋相关材料、硒化亚铜相关材料、硒化锡相关材料的最大ZT值都突破了2.但是,这些体材料的热电优值距离大规模实用仍然有较大的差距.通过理论计算得知,当块体热电材料被制作成低维纳米结构材料时,比如二维纳米薄膜、一维纳米线,热电性能会得到显著的改善,具有微纳米结构材料的热电性能研究引起了科研人员的极大兴趣.当块体硅被制作成硅纳米线时,热电优值改善了将近100倍.然而,微纳米材料的热电参数测量极具挑战,因为块体材料的热电参数测量方法和测试平台已经不再适用于低维材料,需要开发出新的测量方法和测试平台用来研究低维材料的热导率、电导率和塞贝克系数.本文综述了几种用于精确测量微纳米材料热电参数的微机电结构,包括双悬空岛、单悬空岛、悬空四探针结构,详细介绍了每一种微机电结构的制备方法、测量原理以及对微纳米材料热电性能测试表征的实例.     

功能纳米材料的可控制备及性能研究

功能纳米材料以其独特的结构和优异的性能在催化、能源、传感等领域具有广泛的应用前景.通过控制其制备和组装过程,可以有效地调节其性能.文章介绍了作者所在实验室在新型纳米材料合成方面的研究进展,深入探索了纳米晶体、生物络合高分子和生物分子-无机杂化纳米结构的可控性制备过程,对金属-半胱氨酸生物络合高分子的自组装与超结构手性进行了系统的研究和探讨.另外,文章作者还发现了无机杂化纳米结构的可逆光开关荧光效应,该效应在光信息记录方面具有潜在的应用价值.     

功能纳米材料的可控制备及性能研究

功能纳米材料以其独特的结构和优异的性能在催化、能源、传感等领域具有广泛的应用前景.通过控制其制备和组装过程,可以有效地调节其性能.文章介绍了作者所在实验室在新型纳米材料合成方面的研究进展,深入探索了纳米晶体、生物络合高分子和生物分子-无机杂化纳米结构的可控性制备过程,对金属-半胱氨酸生物络合高分子的自组装与超结构手性进行了系统的研究和探讨.另外,文章作者还发现了无机杂化纳米结构的可逆光开关荧光效应,该效应在光信息记录方面具有潜在的应用价值.     

Functional Fe–Pd nanomaterials synthesized by template-assisted methods

In this work, we highlight our recent progress in the synthesis and characterization of functional nanomaterials based on Fe–Pd ferromagnetic alloys by means of template-assisted deposition techniques employing highly ordered nanoporous alumina membranes, such as ordered arrays of nanowires and antidots thin films. Special attention is paid on their basic magnetic properties, such as coercivity, remanence and magnetic anisotropy, and their dependence on the microstructure and morphological parameters of the ordered arrays.     

Estimation and interpolation of underwater low frequency ambient noise spectrum using artificial neural networks

In this work, estimation of ambient noise spectrum influenced by wind speed and wave height carried out for the frequency range of 500 Hz to 5 kHz using Feed forward Neural Network (FNN) is presented. Ocean ambient noise measurements were made in the shallow waters of Bay of Bengal using a portable data acquisition system with a high sensitivity hydrophone at a depth of 5 m from the surface.100 sets of data covering a rage of wind speeds from 2.5 m/s to 8.5 m/s with approximately 15 sets of data falling within 1 m/s over the range of wind speed were used for training the FNN. The parameter wave height which contributes to the noise producing mechanism is also used for training along with wind speed. The results revealed that the proposed method is useful in the estimation and interpolation of underwater noise spectrum level and hence in simulation for the considered frequency range. These were confirmed by calculating the Mean Squared Error (MSE) between the experimental data and the simulation. As the measurements of the underwater ambient noise level are very difficult in remote oceanic regions, where conditions are often inhospitable, these studies seem to be relevant.