In recent years, prognostic and health management (PHM) has played an important role in industrial engineering. Efficient remaining useful life (RUL) prediction can ensure the development of maintenance strategies and reduce industrial losses. Recently, data-driven based deep learning RUL prediction methods have attracted more attention. The convolution neural network (CNN) is a kind of deep neural network widely used in RUL prediction. It shows great potential for application in RUL prediction. A CNN is used to extract the features of time-series data according to the spatial feature method. This way of processing features without considering the time dimension will affect the prediction accuracy of the model. On the contrary, the commonly used long short-term memory (LSTM) network considers the timing of the data. However, compared with CNN, it lacks spatial data extraction capabilities. This paper proposes a double-channel hybrid prediction model based on the CNN and a bidirectional LSTM network to avoid those drawbacks. The sliding time window is used for data preprocessing, and an improved piece-wise linear function is used for model validating. The prediction model is evaluated using the C-MAPSS dataset provided by NASA. The predicted results show the proposed prediction model to have a better prediction performance compared with other state-of-the-art models.

Wu, Z.; Xiang, Y.; Li, M.; Iqbal, M., and Xu, G, 2019. Investigation of accumulator main parameters of hydraulic excitation system. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 613–622. Coconut Creek (Florida), ISSN 0749-0208.The accumulator is a special container which used for accumulate energy and its responsiveness plays an important role in improving hydraulic system performance. Therefore, it can be seen from the current research results that most scholars focus on the bladder-type accumulator owing to the reflection of the bladder-type accumulator is fast. The hydraulic system with a bladder-type accumulator is adapted to absorb shock pressure and eliminate pressure pulsations. However, due to the sudden change of the reversing valve or the sudden stop of the actuator, the pressure shock will occur in the hydraulic system, and the relief valve will not be able to move, which will cause the pipeline to vibrate. In severe cases, the hydraulic pipe will be broken and caused a safety accident. In actual use, the effect of absorbing pressure shock is not ideal due to improper selection of accumulator parameters. Therefore, the main objective of this study is to use theoretical analysis, computer simulation and experimental research to analyse the influence of accumulator parameters on the hydraulic system.

This article intends a hybrid energy harvesting shock absorber design which comprehends energy harvesting of automobile suspension vibration dissipation. A mathematical model of the energy harvesting prototype is established, and simulation results show that the dissipation energy can be recovered by varying the feed module, thereby got the damping forces ratio at different compression and extension stroke. The energy conversion from hydraulic energy to mechanical energy mainly then mechanical energy converted into electrical energy furthermore we can rechange our battery from this recovered energy. The advanced mathematical model and prototype proposed maximum ride comfort meanwhile recovered the suspension energy and fuel saving. This article shows the simulation results verifying it with prototype test results. The damping force of expansion stroke is higher than the damping force of compression stroke. The damping characteristics curves and speed characteristics curves verify the validity by simulation and prototyping damper at different amplitudes of off-road vehicles. The Hydraulic Electromagnetic Regenerative Shock Absorber (HESA) prototype characteristic is tested in which 65 watts recovered energy at 1.67 Hz excitation frequency. So, 14.65% maximum energy recovery efficiency got at 20 mm rod diameter and 8 cc/rev motor displacement. The damping characteristics of the HESA prototype examined and it has ideal performance as the standard requirements of the National Standard QC/T 491–1999.

This paper discusses the impact of Fischer-Tropsch（F-T）diesel and methanol blended fuel, tentative engine was operated with fueled having F-T diesel and methanol blended fuel to compare the combustion and vibration characteristics. For this, 4100QBZL turbocharged diesel having parameters of F-T diesel fuel, FM5, FM10, FM15 methanol volume content was 5%, 10%, and 15% respectively have been selected for the experiment. Experimental studies have shown that when fueling with F-T diesel fuel, the ignition delay is shorter, the premixed combustion rate peak is lower, and vibration acceleration increases slightly than diesel fuel. Compared to the pure F-T diesel, the blended fuel has longer ignition delay period, higher the rate of pressure rise, combustion start point delayed, burning capacity increase, such as thermal efficiency is improved and vibration acceleration increased significantly.

Silicon Carbide Double Diffused Metal Oxide Semiconductor (SiC-DMOS), having a more comprehensive bandgap, fast switching and low power losses, has been rapidly developed and applied. This paper elaborates a detailed analysis of switching losses by comparing Si IGBT and SiC DMOS under the same voltage parameters and identical conditions. The switch’s characteristics are evaluated and contrasted in various gate resistances. In addition, a gate driver is designed to calculate the switching losses of IGBT and SiC DMOS at different frequencies. Then they are respectively used in the buck converter. The experimental platform is built to test and validate that the SiC DMOS buck converter achieves faster dynamic performance and higher efficiency than Si IGBT.

Due to its high strength, good corrosion resistance, wear resistance, thermal stability, and oxidation resistance, high entropy alloys have great potential for application in engineering. High-entropy alloys based on the Al-Co-Cr-Fe-Ni system exhibit exceptional mechanical properties, including high strength, corrosion resistance, and thermal stability, making them promising candidates for engineering applications. This study investigates the microstructure and mechanical properties of AlxCoCrFeNi (x = 0.4, 0.8, 1.2) high entropy alloys fabricated via arc melting and laser melting deposition (LMD). Results demonstrate that increasing aluminum content induces a phase transition from a face-centered cubic (FCC) to a body-centered cubic (BCC) structure, significantly enhancing hardness from 163.1 HV (x = 0.4) to 513.7 HV (x = 1.2) while reducing ductility. The Al0.8CoCrFeNi alloy, with a balanced FCC/BCC biphasic structure, achieves optimal mechanical performance, exhibiting a compressive strength of 2105 MPa and 36.7% elongation. LMD-produced alloys display refined microstructures, such as eutectic formations, attributed to rapid cooling rates. The study highlights the critical role of aluminum in tailoring phase composition and mechanical behavior, offering insights for designing high entropy alloys with customized properties. However, challenges such as brittleness in high-Al-content alloys and unexplored anisotropy in LMD samples warrant further investigation. These findings advance the understanding of high entropy alloy processing-microstructure-property relationships, supporting their potential in high-performance applications.