The optimization of fire robot axle in axle size based on dynamic strength and material cost
The axle of robot always afford complex load in a high dynamic vibration, the statics strength cannot take enough safety factor, and a larger safety factor would waste the material cost. In this paper, a new optimization function which takes consideration to the dynamic strength and material cost is derived. The dynamic strength has been discussed, a dynamic simulation modle based on FEA has also been bulid, the simulation results showed the boundary conditions of the optimization, the relationship between dynamic strength and axle size which was highly nonlinear, was simplized as a approximated sine function. The material cost factor is simplified to the mess of the axle. And all the factors in the optimization plently funtion were normalized, and the 3D graphic of the funtion has been draw, the extremum point of the optimization function, which was the most appropriate sizes of the axle, was found by the Matlab.
An Application of MATLAB in Optimization Design of Parallel Robot Mechanism's Physical Dimension
To problems on optimization design of parallel robot mechanism's physical dimension, a method using MATLAB and its optimization toolbox instead of that the traditional programming is put forward. With its simple programming and easily modify ,the method can solve optimal value and has extensive prospects in application in this field.
SVD-based optimal filtering for noise reduction in dual microphone hearing aids: a real time implementation and perceptual evaluation
In this paper, the first real-time implementation and perceptual evaluation of a singular value decomposition (SVD)-based optimal filtering technique for noise reduction in a dual microphone behind-the-ear (BTE) hearing aid is presented. This evaluation was carried out for a speech weighted noise and multitalker babble, for single and multiple jammer sound source scenarios. Two basic microphone configurations in the hearing aid were used. The SVD-based optimal filtering technique was compared against an adaptive beamformer, which is known to give significant improvements in speech intelligibility in noisy environment. The optimal filtering technique works without assumptions about a speaker position, unlike the two-stage adaptive beamformer. However this strategy needs a robust voice activity detector (VAD). A method to improve the performance of the VAD was presented and evaluated physically. By connecting the VAD to the output of the noise reduction algorithms, a good discrimination between the speech-and-noise periods and the noise-only periods of the signals was obtained. The perceptual experiments demonstrated that the SVD-based optimal filtering technique could perform as well as the adaptive beamformer in a single noise source scenario, i.e., the ideal scenario for the latter technique, and could outperform the adaptive beamformer in multiple noise source scenarios.