Both bentonite and CaCO3 are cheap and abundant superior regional non-metal ores in Guangxi province, so it is very meaningful to jointly exploit bentonite and CaCO3 for real applications. In this study, bentonite modified with CaCO3 (CCB) was prepared and its adsorption performance of Congo Red (CR) and Methylene Blue (MB) was evaluated by investigating the adsorption influencing effects of initial pH, SDBS and phosphate. Adsorption isotherms and adsorption kinetics models were also fitted to analysis the corresponding kinetic characteristics of CCB. The results show that CCB exhibited superior adsorption performance with the respective > 90% MB and CR removal within the initial pH range 2 ~ 10. To a certain extent, MB removal efficiencies by CCB can be increased with the addition of SDBS. On the other hand, CR adsorption on CCB was inhibited slightly in presence of SDBS. But as a whole, removal efficiencies of MB and CR by CCB were kept constant when SDBS co-existed. MB and CR adsorption on CCB decreased to some extent because of competitive adsorption effect when phosphate co-existed. It also demonstrated that CCB can remove phosphate at the same time with dyes. Adsorption models including adsorption isotherms adsorption kinetics indicated that MB and CR adsorption on CCB was a monolayer process, and the adsorption rate depended on both adsorbent and adsorbate. In summary, CCB is a promising adsorbent for dyes removal with many advantages such as simple preparation technology, excellent adsorption performance for anionic and cationic dyes, broad fitting pH range and SDBS resistance. Besides, it can remove dyes together with phosphate at the same time. Therefore, this study is very useful for the dyeing wastewater treatment and exploiting the resources of bentonite and CaCO3.

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Due to the fish scale surface of the weld seam, the guided wave dispersion is intensified, resulting in serious mode aliasing problem of the detected signal. It is difficult to analyze defect echo signal and locate defect accurately. To solve this problem, a new method of ultrasonic guided wave detection is proposed for weld defects based on matching pursuit and density peak clustering. First, according to the characteristics of the guided wave echo signal, a matching pursuit algorithm based on Morlet wavelet dictionary is established. The time-frequency analysis and parameter analysis of the obtained wavelet atoms are carried out to realize the modal separation and identification of the guided wave signal. Then, the similarity weight is introduced into the density peak algorithm to cluster the atoms obtained by sparse decomposition. The obtained clustering center is used to locate the weld defect. The validity of the method is proved by simulation and experiment. Finally, the experimental results show that the positioning error is 0.261% when the proposed method is used to detect the weld defects of 3-mm wide steel plate.

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