Fault Identification for Shear-Type Structures Using Low-Frequency Vibration Modes

Shear-type structures are common structural forms in industrial and civil buildings,such as concrete and steel frame structures.Fault diagnosis of shear-type structures is an important topic to ensure the normal use of structures.The main drawback of existing damage assessment methods is that they require accurate structural finite element models for damage assessment.However,for many shear-type structures,it is difficult to obtain accurate FEM.In order to avoid finite elementmodeling,amodel-freemethod for diagnosing shear structure defects is developed in this paper.This method only needs to measure a few low-order vibration modes of the structure.The proposed defect diagnosis method is divided into two stages.In the first stage,the location of defects in the structure is determined based on the difference between the virtual displacements derived from the dynamic flexibility matrices before and after damage.In the second stage,damage severity is evaluated based on an improved frequency sensitivity equation.Themain innovations of this method lie in two aspects.The first innovation is the development of a virtual displacement difference method for determining the location of damage in the shear structure.The second is to improve the existing frequency sensitivity equation to calculate the damage degree without constructing the finite elementmodel.Thismethod has been verified on a numerical example of a 22-story shear frame structure and an experimental example of a three-story steel shear structure.Based on numerical analysis and experimental data validation,it is shown that this method only needs to use the low-order modes of structural vibration to diagnose the defect location and damage degree,and does not require finite element modeling.The proposed method should be a very simple and practical defect diagnosis technique in engineering practice.

Sound absorption of several various nickel foam multilayer structures at aural frequencies sensitive for human ears

Using the three-dimensional reticular nickel foam as experimental material, the sound absorption performance was investigated for several various multilayer structures in the frequency range of 2000-4000 Hz, which is aurally sensitive for human ears. The results showed that the 7.5 mm-thick foam sample, which was formed by piling of 5-layer foam plate（thickness： 1.5 mm; porosity： 96%; average pore-diameter： 0.65 mm） could exhibit an excellent sound absorption effect at 4000 Hz, with the absorption coefficient about 0.8. Constituting alternate air gap with the total thickness of about 18.5 mm can greatly improve the absorption performance at relatively low frequencies of 2000-3150 Hz, with the absorption coefficient up to about 0.5 or more. In addition, the research showed that alternate piling up the perforated plate inside the foam plates can also achieve a quite good effect of sound absorption at relatively low frequencies.

Analysis of Frequency Characteristics and Sensitivity of Compliant Mechanisms

Based on a modified pseudo-rigid-body model,the frequency characteristics and sensitivity of the large-deformation compliant mechanism are studied.Firstly,the pseudo-rigid-body model under the static and kinetic conditions is modified to enable the modified pseudo-rigid-body model to be more suitable for the dynamic analysis of the compliant mechanism.Subsequently,based on the modified pseudo-rigid-body model,the dynamic equations of the ordinary compliant four-bar mechanism are established using the analytical mechanics.Finally,in combination with the finite element analysis software ANSYS,the frequency characteristics and sensitivity of the compliant mechanism are analyzed by taking the compliant parallel-guiding mechanism and the compliant bistable mechanism as examples.From the simulation results,the dynamic characteristics of compliant mechanism are relatively sensitive to the structure size,section parameter,and characteristic parameter of material on mechanisms.The results could provide great theoretical significance and application values for the structural optimization of compliant mechanisms,the improvement of their dynamic properties and the expansion of their application range.

Robust control for active suspension system under steering condition

To minimize the auto body's posture change caused by steering and uneven road, and improve the vehicle's riding comfort and handling stability, this paper presents an H∞ robust controller of the active suspension system, which considers the effects of different steering conditions on its dynamic performance. The vehicle's vibration in the yaw, roll, pitch and vertical direction and the suspension's dynamic deflection in the steering process are taken into account for the designed H∞ robust controller, and it introduces the frequency weight function to improve the riding comfort in the specific sensitive frequency bands to human body. The proposed robust controller is testified through simulation and steering wheel angle step test. The results show that the active suspension with the designed robust controller can enhance the anti-roll capability of the vehicle, inhibit the changes of the body, and improve the riding comfort of the vehicle under steering condition. The results of this study can provide certain theoretical basis for the research and application of active suspension system.

A Necessary Condition about the Optimum Partition on a Finite Set of Samples and Its Application to Clustering Analysis

This paper presents another necessary condition about the optimum parti-tion on a finite set of samples. From this condition, a corresponding generalized sequential hao f k-means (GSHKM) clustering algorithm is built and many well-known clustering algorithms are found to be included in it. Under some assumptions the well-known MacQueen's SHKM (Sequential Hard K-Means)algorithm, FSCL (Frequency Sensitive Competitive Learning) algorithm and RPCL (Rival Penalized Competitive Learning) algorithm are derived. It is shown that FSCL in fact still belongs to the kind of GSHKM clustering algth rithm and is more suitable for producing means of K-partition of sample data,which is illustrated by numerical experiment. Meanwhile, some improvements on these algorithms are also given.