In order to reduce energy consumption and further improve the performance of viscose yarns, this study introduced a collaborative control method to improve spun yarn performance by contacting the spinning strand with both a softening device and a pressure plate. In this study, we analyze the improving mechanism of spun yarn performance using the softening device and pressure plate. The results show that thermal insulation layer formed between the softening device and pressure plate could heat the yarns in all directions to further re-wrap out-exposed hairiness into the main body of yarns and save energy consumption. Four groups of 19.7 tex viscose yarns were spun with different collaborative apparatus (with and without the softening device or pressure plate). Four groups of viscose yarns were tested in terms of hairiness, unevenness, and tensile property. Moreover, the experimental results show that collaborative apparatus with the softening device and pressure plate could significantly improve yarn performance, including CV value, hairiness, break elongation, and breaking strength to 11.3%, 18.94, 12.9%, and 311.0 cN, respectively.

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The electrochemical noise method (ENM) has previously been employed to monitor the corrosion of steel reinforcement in concrete. The development of solid-state Ag/AgCl-based probes and dedicated monitoring technology (ProCoMeter) now offers a wider range of ENM configurations. The present study involves the laboratory investigation of three mortar samples containing steel bars and varying additions of chloride, with a view to future field application. ENM could be used to provide corrosion information on reinforcement without the need to provide direct electrical connections to the steel and without the risk or inducing or increasing corrosion. In addition to half-cell potentials, measurements were made using ENM in three different probe configurations over a total test period of 90 days. The samples were then broken open and the bars extracted and cleaned. A comparison was then made between the calculated metal thickness loss obtained from the Rn values and the actual metal thickness loss. The results showed that each configuration was able to order the results in the expected manner, with the simple single substrate (SSS) arrangement providing the best correlation with direct measurements. The study is ongoing with the intention of measurements being obtained in situ on existing reinforced concrete structures.

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Electronic yarn clearer online detected data can be used to justify whether the evenness performance of yarn meets the standard for further processing. The reliability of offline detection is limited by the sample numbers. Based on the analysis of 100 sets of yarn performances (both online and offline) and assuming that external factors are fixed, linear fitting was performed to obtain the correlation functions between online and offline data of yarn performance. Finally, the correlation functions between the online detected data, coefficient of variation value and hairiness H value and offline detected data were established. The correlations between these parameters are significant. In particular, the function-deduced confidence and prediction intervals are very useful to forecast abnormal conditions during real yarn production. The production efficiency could be significantly improved under the guiding of these correlation functions.