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We prepared a sludge-based fire-preventive and extinguishing composite gel for coal mines using sludge, HPAM, water glass, and sodium bicarbonate as the main raw materials. Orthogonal test was used to analyze the effects of each component and its level on the performance of gel to determine the optimal ratio of gel and then tested its fire-preventive and extinguishing characteristics. Finally, the gelling mechanisms of the gel are discussed. The composite gel prepared at the optimal level showed that the gelling time can be maintained at about 55 s, the water retention can reach up to 58.6% in 12 h at 100 °C. The gel has a dense microstructure and uniform pores, and has the best inhibition rate of coal spontaneous combustion. As compared with other materials, the coal piled with gel did not reignite. TGA showed that the gel hinders oxidation and complete combustion of coal. The in-situ infrared analysis confirmed that the coal sample treated with gel has a low content of aliphatic hydrocarbon and hydroxyl group. Infrared spectroscopy analysis indicated that the sludge in the gel plays the role of filler. The organic-inorganic composite network structure formed by the sludge and the gel not only prevents the system from water loss and coal oxidation but also absorbs a large amount of sludge and realizes the resource utilization of sludge. Therefore, the preparation of composite gel reduces the secondary pollution of sludge and lowers the cost of the material, making it an economical and environmentally friendly fire-preventive and extinguishing material.

Accurate extraction of natural frequencies of the Polyester Filament Yarn (PFY) vibration can effectively estimate PFY tension. However, due to the special working operating conditions of spinning equipment, the collected PFY vibration signals always contain strong noise components, which severely affect the analysis and processing of those signals. Stochastic resonance has received extensive attention and research in enhancing and extracting feature signals. In this paper, a time-delayed feedback bistable stochastic resonance (TFBSR) system is proposed and the feasibility of the system for natural frequencies extraction is discussed. The potential function, the probability density, the mean first-passage time and the SNR-theory are used to evaluate the TFBSR system. Firstly, through adaptive tuning parameters including barrier parameters, feedback strength, time delay and noise intensity in the TFBSR system, the weak PFY vibration signal, the noise, and the potential can be matched with each other to an extreme, and an optimal output with low-noise interference can be obtained consequently. Secondly, numerical simulation results show that the noise intensity has played an active role in the stochastic resonance effect. Finally, the combination of the TFBSR system and the improved wavelet threshold denoising model is conducive to extracting the natural frequencies of the PFY and making the estimation of the PFY tension in the spinning process. The experimental results indicate that the TFBSR system can accurately extract the natural frequency and improve the energy of the PFY vibration signal under the appropriate system parameters. [ABSTRACT FROM AUTHOR]