In this paper, we present a new numerical method for calculating pump power in designing multi-wavelength pumped Raman amplifiers, by using some optimal searching method, we establish a complete computing model to optimize the pump wavelength and power allocation with flat net gain and broad bandwidth. In order to increase precision and degrade computing time a new predictor-corrector linear multistep method is proposed instead of one-step method, which was adopted in traditional designing to calculate power integral for signals and pumps propagating through the fiber. Further more, we adopt the Quasi-Newton iteration method to adjust the pump power efficiently without any manual adjustment. The optimal results show that by using our method, iteration process will be convergent rapidly and relative gain flatness below 5% can be achieved over 100nm bandwidth without any gain equalization devices. The whole optimal method costs within 10 minutes in a common computer.
An experimental setup was established by using a high stability, narrow line bandwidth fiber laser with a fiber optic amplifier, polarization maintaining fiber coupler with split ratio of 50:50 and 95:5 respectively, a fiber optic sensing coil with high birefringence large nonlinear polarization maintaining fiber, and uniform fiber Bragg grating that was used at output port for filtering the excess pumping component. Based on this experimental setup, the threshold power of the pumping laser was deduced, and the relationship of the spectra and intensity between pumping laser component and stokes component with frequency downshift was obtained experimentally.
Combining the active digitizing technique with the passive stereo vision, a novel method is proposed to acquire the 3D data from two 2D images. Based on the principle of stereo vision, and assisting the active dense structure light projecting, the system overcomes the problem of data points matching between two stereo images, which is the most important difficulty occurring in stereo vision. An algorithm based on wavelet transform is proposed here to auto-get the threshold for image segment and extract the grid points. The system described here is mainly applied to digitize the 3D objects in time. Comparing with the general digitizers, it performs the translation from 2D images to 3D data completely, and gets over some shortcomings, such as slow image acquiring and data processing speed, depending on mechanical moving, painting on the object before digitizing, and so on. The system is the same with the non-contact and fast measurement and modeling for the 3D object with freedom surface, and can be employed widely in the fields of Reverse Engineering and CAD/CAM. Experiment proves the efficiency of the new use of shape from stereo vision (SFSV) in engineering.