Research on ultrasonic detection of complex surfaces

Parts of complex surface are widely used now in many fields, and their detection has caused much concern. In China many manufactories still carry on the traditional way of manual detection, which requires highly skilled personnel and efficiency is low. Some large manufactories have imported auto-detecting equipments, which require CAD data on the parts, or just divide the surface into several approximate planes for automatic detection. Phased-array system is seldom used, and the cost is high. Besides, most of the systems have not considered the automatic sensitivity compensation of parts with varying thickness. To improve the detection quality and efficiency of nondestructive test (NDT) of parts of complex surface, this paper puts forward an integrated ultrasonic NDT system characterized by: (1) Use of ultrasonic measurement and reverse of curved surface to solve the CAD data problem; (2) Use of an automatic sensitivity compensation algorithm (based on the part’s modelling information obtained in surface reverse) to fit the variety of the thickness; (3) Use of template matching and pseudo-color imaging to improve the quality of detection results. The system features integration of low cost mature technologies, and is suitable for detection of various parts of different complex surfaces in medium-and-small enterprises. The test results showed that the system can automatically detect parts of complex surface successfully, and that the inspection result is good and reliable.

Shape sensitivity analysis of flutter characteristics of a low aspect ratio supersonic wing using analytical method

Shape sensitivities of flutter characteristics can predict the moving of flutter boundary as wing shape varies. The nonlinear relationship between mass, stiffness and damping matrices of aeroelastic systems and shape variables makes the flutter characteristics vary nonlinearly as shape variables change. The computation cost of finite difference method is high and it cannot solve precisely shape sensitivities. An analytic method is developed to compute sensitivities of flutter characteristics of low aspect ratio wings to shape parameters, which include aspect ratio, taper ratio, sweep angle, and area. On the basis of the equivalent plate model and piston theory, analytic sensitivities of mass, stiffness and damping matrices with respect to various shape parameters are computed. The equivalent plate model is a continuous aeroelasticity analysis model oriented toward wing design. The flutter equation is solved by tracking the root locus of the system state space model. Lancaster's adjoint method is used to solve the eigenvalue derivatives and shape sensitivities of flutter characteristics. Linear Taylor approximation based on the analytic sensitivities is used to predict the variation of flutter speed with respect to shape variables. Comparison of these results with those from reanalysis indicates that Taylor approximation based on analytic sensitivities can precisely predict trends of flutter characteristics near the baseline configuration, but the applied neighborhood is small for sweep and area. The method can help designers make a judicious choice of wing shape parameters for preventing flutter in the preliminary design phase of aircraft.

Noise decomposition and parameter optimization method for high sensitivity fiber optic gyroscope

A novel random walk coefficient(RWC) model of the interferometric fiber optic gyroscope(IFOG) to decompose fundamental noise sources, namely the shot noise, the excess noise, the thermal noise, and the detection circuit noise, from the overall noise was developed. The coefficients of the model were extracted from the measured RWC instead of by calculating the accurate IFOG parameters, which is simpler and more accurate. The correctness and the accuracy of the model were verified by experiments. Using this model, the RWC of the experimental IFOG was predicted and the quantitative contributions of the noise sources were determined. According to the predicted results, the parameters of the IFOG were optimized. Finally, based on the model, a noise decomposition and parameter optimization method was proposed for high sensitivity IFOG design.

Modeling individual vocal differences in group-living lemurs using vocal tract morphology

Vocal individuality is widespread in social animals. Individual variation in vocalizations is a prereq- uisite for discriminating among conspecifics and may have facilitated the evolution of large complex societies. Ring-tailed lemurs Lemur catta live in relatively large social groups, have con- spicuous vocal repertoires, and their species-specific utterances can be interpreted in light of source-filter theory of vocal production. Indeed, their utterances allow individual discrimination and even recognition thanks to the resonance frequencies of the vocal tract. The purpose of this study is to determine which distinctive vocal features can be derived from the morphology of the upper vocal tract. To accomplish this, we built computational models derived from anatomical measurements collected on lemur cadavers and compared the results with the spectrographic out- put of vocalizations recorded from ex situ live individuals. Our results demonstrate that the mor- phological variation of the ring-tailed lemur vocal tract explains individual distinctiveness of their species-specific utterances. We also provide further evidence that vocal tract modeling is a power- ful tool for studying the vocal output of non-human primates.