Wet Welding Platform Design based on Ultrasonic Sensor
The research platform for underwater wet welding is designed and high frequency ultrasonic sensor is put into use, The research platform comprises four independently movable shafts which names as X, Y, Z and A axis, The four axes are driven by servo motor and stepping motor, The features of both servo motor and stepping motor are analyzed at first, and then the relationship between the moving speed and controlling precision among different shaft is discussed, control program is given out based on ADT8940A1 PCI four-shaft bus control card after the shafts running parameters have determined, With the help of high-frequency underwater ultrasonic sensor, high-precision ranging experiments are carried out on the base of a hybrid digital signal process method combined band filter and Wavelet transform (WT), satisfied results are achieved in distance detection experiments with related coefficients method, results will be used in seaming tracking later.
Improving Stability of Welding Model with ME-ELM
Welding shape is important in evaluating welding quality, but accurate predictive model is hard to achieve, because welding is a complex nonlinear process, and the sampled data are inevitably contaminated. Extreme learning machine (ELM) is used to construct a single-hidden layer feedforward network (SLFN) in our study, for improving stability of welding model, M-estimation is combined with ELM and a new algorithm named ME-ELM is developed; researches indicate that it works more effective than BP and other variants of ELM in reducing influence, furthermore, it can improve the model’s anti-disturbance and robustness performance even if the data are seriously contaminated. Real TIG welding models are constructed with ME-ELM, by comparing with BP, multiple nonlinear regression (MNR), and linear regression (LR), conclusions can be gotten that ME-ELM can resist the interference effectively and has the highest accuracy in predicting the welding shape.
Experimental investigation of the geotechnical properties and microstructure of lime-stabilized saline soils under freeze-thaw cycling
Abstract The Song-Nen Plain in northeastern China holds one of the three largest expanses of soda saline-alkali soil in the world. Due to its disadvantageous geotechnical properties, the saline soil in this area is unable to meet the needs of construction projects. This study evaluates the stabilizing effect of adding lime to such soils. Specifically, it investigates how the physicochemical and mechanical properties and microstructure of soda saline-alkali soil are altered by lime and how these changes are affected by both freeze-thaw cycling and the duration of curing. The results reveal that adding lime to saline soil transforms clay particles into sand and silt particles and causes the pore size distribution (PSD) to become bimodal, with small-pore and macropore populations. An increase in lime content leads to an increase in the unconfined compressive strength (UCS) but a gradual decrease in both the cation exchange capacity (CEC) and plastic index. Freeze-thaw cycles break up coarse particles and aggregate finer particles, increasing the diameter of macropores and decreasing the USC; however, the effect on specimens with >9% lime is negligible. It is further shown that the geotechnical properties of the soil change immediately after the addition of lime, indicating that the cation exchange reaction takes place very quickly. Furthermore, the pozzolanic reaction leads to an increase in the percentage of sand-sized particles and a decrease in porosity after 28 days of curing. Overall, these results indicate that it is feasible to use lime to improve the engineering properties of soda saline-alkali soil in this area.