PCNN based image processing and feature extraction of dual-bypass gas metal arc weld pool

In manual welding process, skilled welders can adjust the welding parameters to ensure the weld quality through their observation of the weld pool surface. In order to acquire useful information of the weld pool for control of the welding process and realizing the automatic welding, the measurement system of DB-GMA W process was established and the weld pool image was obtained by passive vision. Then, three image processing algorithms, Sobel, Canny, and pulse coupled neural network （PCNN） were detailed and applied to extracting the edge of the DB-GMA weld pool. In addition, a scheme was proposed for calculating the length, maximum width and superficial area of the weld pool under different welding conditions. The compared results show that the PCNN algorithm can be used for extracting the edge of the weld pool and the obtained information is more useful and accurate. The calculated results coincide with the actual measurement well, which demonstrates that the proposed algorithm is effective, its imaging processing time is required only 20 ms, which can completely meet the requirement of real-time control.     

光催化氧化降解高盐废水中EDTA的研究

研究了UV/H2O2/TiO2光催化体系对高盐氛围中EDTA的去除效果,通过比较不同组合方法、催化剂的投加量、过氧化氢含量、废水pH、氯化钠浓度、硫酸钠浓度以及污染物初始浓度对该反应效率的影响.结果 表明,在EDTA二钠浓度为500 mg/L,初始pH为4,硫酸钠浓度为30 g/L的溶液,加入8mL/L 30％的H2O...