Detecting the backfill pipeline blockage and leakage through an LSTM-based deep learning model

Detecting a pipeline's abnormal status,which is typically a blockage and leakage accident,is important for the continuity and safety of mine backfill.The pipeline system for gravity-transport high-density backfill(GHB)is complex.Specifically designed,efficient,and accurate abnormal pipeline detection methods for GHB are rare.This work presents a long short-term memory-based deep learning(LSTM-DL)model for GHB pipeline blockage and leakage diagnosis.First,an industrial pipeline monitoring system was introduced using pressure and flow sensors.Second,blockage and leakage field experiments were designed to solve the problem of negative sample deficiency.The pipeline's statistical characteristics with different working statuses were analyzed to show their complexity.Third,the architecture of the LSTM-DL model was elaborated on and evaluated.Finally,the LSTM-DL model was compared with state-of-the-art(SOTA)learning algorithms.The results show that the backfilling cycle comprises multiple working phases and is intermittent.Although pressure and flow signals fluctuate stably in a normal cycle,their values are diverse in different cycles.Plugging causes a sudden change in interval signal features;leakage results in long variation duration and a wide fluctuation range.Among the SOTA models,the LSTM-DL model has the highest detection accuracy of98.31%for all states and the lowest misjudgment or false positive rate of 3.21%for blockage and leakage states.The proposed model can accurately recognize various pipeline statuses of complex GHB systems.

The biomimetic catalytic synthesis of acetal compounds using β-cyclodextrin as catalyst

Based on the principle of biomimetic catalysis, β-cyclodextrin was applied to the acetalation reaction as a facile and efficient catalyst, and the synthesis was environmentally friendly with atomic economy. The influencing factors of the acetalation reaction e.g. the reaction time, the volume of water-carrying agent,the molar ratio of catalyst to benzaldehyde and the molar ratio of glycol to benzaldehyde had been studied.The yield of benzaldehyde glycol acetal would reach a maximum of 81.3% under the conditions approached.Six of other acetals were also synthesized. Moreover, a plausible reaction mechanism for the formation of acetal had been proposed.