Continuous-wave mud generator is widely adopted for real-time downhole data transmission of deep wells in the oil industry. There have been many studies on rotor structure optimization of continuous rotary valve tools but few studies on the different optimization mechanisms of oscillating shear valve tools. In this paper, a theoretical model of pressure wave generation for oscillating shear valve tools was presented, and the reason for the non-sinusoidal waveform was analyzed theoretically for the first time. A series of rotor rotation strategies were proposed to improve the sinusoidal properties of pressure waves without changing the mechanical structure of the rotor. Finally, CFD with different parameters was conducted to verify the feasibility of the optimization scheme. The numerical results give the recommended range of parameters under different control schemes. In addition, the relationship between throttle pressure drop and pressure wave waveform is found through comparison with previous research of the team, which provides a new research idea for the optimization of the pressure wave in the future.

Since light propagation in a multimode fiber (MMF) exhibits visually random and complex scattering patterns due to external interference, this study numerically models temperature and curvature through the finite element method in order to understand the complex interactions between the inputs and outputs of an optical fiber under conditions of temperature and curvature interference. The systematic analysis of the fiber’s refractive index and bending loss characteristics determined its critical bending radius to be 15 mm. The temperature speckle atlas is plotted to reflect varying bending radii. An optimal end-to-end residual neural network model capable of automatically extracting highly similar scattering features is proposed and validated for the purpose of identifying temperature and curvature scattering maps of MMFs. The viability of the proposed scheme is tested through numerical simulations and experiments, the results of which demonstrate the effectiveness and robustness of the optimized network model.