Analysis of Factors Affecting the Accuracy of Moving Force Identification

In this study, the influence of the static component in the total force and the effective frequency bandwidth on the accuracy of force identification has been investigated. The acceleration and bending moment responses at different locations of a simply supported beam under different moving forces are numerically measured. The fast Fourier transformation is also introduced to analyze the frequency-domain component of the dynamic responses of the beam. Simulation results show that the dynamic characteristics of the vehicle, such as the frequency of dynamic vehicle load, have significant effect on the proportion of static component in the total vehicle load; the higher the proportion of static component in the total force, the higher the identification accuracy. In addition, the wider the effective frequency bandwidth, the higher the identification accuracy. The numerical results also show that both the proportion of static component in the total force and the effective frequency bandwidth vary with the type and location of measurement. To more accurately identify the moving force, it is necessary to analyze first the static component and frequency characteristics of the measured responses and to select appropriate type and location of measurement.

Bridge Damage Detection Using Quasi-Static Component of Moving Vehicle-Induced Dynamic Response

The critical signal component extracted from the bridge response caused by a moving vehicle is normally used to construct damage index for damage detection. The dynamic response of bridges subjected to moving vehicle includes several components, among which the quasi-static component reflects the inherent characteristics of the bridge. In view of this, this paper presents a bridge damage detection method based on quasi-static component of the moving vehicle-induced dynamic response. First, damage-induced changes of the natural-frequency component, moving-frequency component and quasi-static component responses are investigated via a simply-supported beam bridge. The quasi-static component response is proved to be less sensitive to the moving velocity of the load and more suitable for damage detection. Subsequently, a quasi-static component response extraction method is proposed based on analytical mode decomposition (AMD) and moving average filter (MAF). The extracted quasi-static component response is further employed to localize and quantify damages. Finally, numerical simulations are conducted to examine the feasibility, accuracy and advantages of the proposed damage detection method. The results indicated that the proposed method performs well in different damage scenarios and is insensitive to the moving velocity of the load and road roughness.

Methods for Detection of Bioimpedance Variations in Resource Constrained Environments

Changes in a certain parameter are often a few magnitudes smaller than the base value of the parameter, specifying significant requirements for the dynamic range and noise levels of the measurement system. In case of electrical bioimpedance acquisition, the variations can be 1000 times smaller than the entire measured value. Synchronous or lock-in measurement of these variations is discussed in the current paper, and novel measurement solutions are presented. Proposed methods are simple and robust when compared to other applicable solutions. A common feature shared by all members of the group of the proposed solutions is differentiation. It is achieved by calculating the differences between synchronously acquired consecutive samples, with lock-in integration and analog differentiation. All these methods enable inherent separation of variations from the static component of the signal. The variable component of the bioimpedance can, thus, be acquired using the full available dynamic range of the apparatus for its detection. Additive disturbing signals and omnipresent wideband noise are considered and the method for their reduction is proposed.