THE CHARACTERISTICS OF THE PLANTAR PRESSURE CENTER DURING TAl CHI EXERCICE

The purpose of this study was to describe and quantify the plantar pressure distribution characteristics during Tai Chi (TC) exercise. Sixteen elite TC masters participated in this study. The Pedar-X insole system was used to record the plantar forces during practicing the five typical TC movements and during normal walking respectively. Results showed that in TC movements, the locations of the centre of pressure (COP) were more medial and posterior at initial contact (p < 0.05), while more medial and anterior at end contact with the ground (p < 0.05). The range of motions (ROMs) of COP were significantly wider (P < 0.05) in mediolateral direction in forward, backward, and sideways TC movements. The ROM was significantly larger (p < 0.05) in anterposterior direction in forward TC movement when compared with normal walking

BIOMECHANICAL CHARACTERISTICS OF SQUATTING WEIGHT LIFT: A CASE STUDY

The purpose of this study was to provide biomechanical data analysis of the squatting lift skill of an elite weight lifter. The performance of the athlete (X. Z.) was studied by means of 3-D fixed video testing and data analysis. Some key parameters of the body and barbell in every important phase were provided in this article. The objective was to profile a sample of biomechanics pattern of this technique with these parameters. The results of the study showed that the subject (X. Z.) performed the squatting and propping skill too long to complete catching barbell movement after the barbell reached the maximum speed. However the attempt was surprisingly successful. This proved that the strength of the lower limbs was sufficiently strong enough to complete the move

Study on defects detection of a structure undergoing dynamic load

Damages detection method of a long span beam was studied. The beam was designed to subject vibration in order to simulate service station of a real structure. The distributed dynamic strain on the beam was studied. Firstly, in order to reduce the dynamic data discriminate time, a new BOTDA method using amplitude transfer of BFS was applied. At the level of spatial resolution of 10 cm and the sampling interval of 5 cm of the BOTDA system, a sampling frequency for dynamic strain of about 13 Hz was achieved. Secondly, a cracks detection system based on distributed dynamic strain was provided. Most of the time, a real structure is undergoing dynamic load, therefore crack detection system of analyzing distributed dynamic strain was concerned. The work is unlike former research that was based on the distributed static strain analysis. Thirdly, a free vibration experiment was performed on a beam of 15 meters long in order to verify the dynamic crack detection system. In order to local the crack easily, the data from BOTDA were processed. Fourier Transform Analysis was adopted to transfer the distributed dynamic strains from time domain into frequency domain. Test results indicated that the distributed frequency amplitude analysis method provided a practical means to recognize the simulated cracks on the beam undergoing dynamic displacement

A co-design method of online learning SMC law via an input-mappping strategy

The research on sliding mode control strategy is generally based on the robust approach. The larger parameter space consideration will inevitably sacrifice part of the performance. Recently, the data-driven sliding mode control method attracts much attention and shows excellent benefits in the fact that data is introduced to compensate the controller. Nevertheless, most of the research on data-driven sliding mode control relied on identification techniques, which limits its online applications due to the special requirements of the data. In this paper, an input-mapping technique is inserted into the design framework of sliding mode control to compensate for the influence generated by the unknown dynamic of the system. The major novelty of the proposed input-mapping sliding mode control strategy lies in that the sliding mode surface and the sliding mode controller are co-designed through online learning from historical input-output data to minimize an objective function. Then, the convergence rate of the system is improved significantly based on the method designed in this work. Finally, some simulations are provided to show the effectiveness and superiority of the proposed methods