The vibration of the rotating machinery for condition monitoring in gear fault detection is a popular area of study. Reliable improvements to the rotating machinery can be obtained by enhancing the machine condition monitoring. The automatic detection of a gear fault at an early stage is required to guarantee a reliable and robust rotating machinery system. In this paper, a novel method of gear fault diagnosis is proposed based on extracting a computational cheap hybrid hand-crafted feature set including the Gamma Tone Cepstral Coefficient (GTCC) and the Mel-Frequency Cepstral Coefficient (MFCC), extracted temporally from the vibration signal. The vibration signal faults have a temporal nature, so the Long Short-Term Memory (LSTM) classifier is adopted because it is suitable for time series signals. To evaluate the proposed model, a ten-fold cross validation approach is applied to two different datasets. The results obtained show that the adopted features and the LSTM classifiers are effective for gear fault detection. Additionally, the performance of the fusion of 14 coefficients for both the GTCC and MFCC exceed the state-of-the-art performance for gear fault detection and for those which use learned features using a pre-trained model.

تمت دراسة تسلسل التراص الأمثل المُثبت لمركب هجين من الزجاج/الكربون بعناية في هذا العمل، جنبًا إلى جنب مع تأثيرات اتجاه الألياف ودمج الجسيمات النانوية SiO2. تم أخذ ثلاثة اتجاهات رئيسية للألياف (0°، 45°، و90°) بعين الاعتبار، كما تم استخدام جزيئات SiO2 النانوية كتعزيز في الايبوكسي. تم استخدام إجراء التسريب لتصنيع الشرائح الهجينة. لفهم وتحليل تأثيرات اتجاه الألياف والجسيمات النانوية SiO2، تم تقييم المعلمات الميكانيكية مثل قوة الشد والانثناء في العديد من التجارب. تم إجراء اختبارات الشد والثني باستخدام عينات اختبار ذات حجم قياسي وفقًا لمعايير ASTM. تم عرض النتائج وتحليلها، وأظهرت أن زيادة سماكة اللوحة ووجود الجسيمات النانوية SiO2 عززت قوة الشد والانثناء.

A spur gear is one of the most common forms of precision cylindrical gear. In the industry, reducing the weight of gears while keeping their useful properties has become an even more pressing challenge. As a result, the investigators have made many attempts to reduce the weight of the gears. Despite these efforts, the problem still requires more research. This study presented a spur gear's modeling and finite element analysis using different materials. A three-dimensional spur gear was designed, modeled, and simulated using ANSYS software. Five different materials, including two conventional materials (stainless steel and copper alloy) and three different composite materials, including 50% carbon fibers reinforced in epoxy resin, 1.5% filler containing acetal, i.e., Graphene Reinforced Acetal, and glass-filled polyamide. Composites were fabricated by varying the graphene quantity in Acetal nanocomposites. The spur gear stress was calculated theoretically using the Hertzian equation, and FEM was analyzed using ANSYS 14.0 under limited loading conditions and rotational speed. Although the obtained results showed that both methods were comparable, there was a significant difference between the two methods when 50% carbon fibers reinforced in epoxy resin matrix were used, which is Hertzian analysis was 250.13 MPa. In contrast, this result was reduced up to 152.13 MPa in FEM. The study concluded that among the different presented materials, 50% carbon fibers reinforced in epoxy resin matrix were the optimal material for spur gear fabrication due to their high strength and low density. Hence, the spur gear material can be replaced by 50% carbon fibers reinforced in the epoxy resin matrix.

Aluminium – copper alloys have a wide range of industrial applications especially in military vehicles, rocket fins and aerospace. Solidification plays a vital role in controlling, the mechanical and tribological properties, and influencing the microstructure of metallic alloys in general and aluminium alloys in particular. Therefore, the researchers have made many efforts to figure out the solidification behaviour of Al-Cu alloys. Despite all these endeavors, however, the behavior is not yet fully understood. This research aims to investigate the effect of cooling rate on the microstructure, mechanical and tribological properties of aluminium-copper cast alloys (Al-Cu alloys) under dry sliding conditions. Four cooling rates were achieved by using four various steel moulds made of different thicknesses and one of them was surrounded with green sand, to get a lower cooling rate, with the same respective mould hole geometries. The microstructure results showed that the grain size increases with decreasing the cooling rate. While the hardness increased largely due to the refinement of the microstructure. Finally, it was concluded that the wear rate increases with decreasing the cooling rate, and this due to the reduction in hardness.

. In this study, the impact performance of the Al2024 thin plate target was determined through a numerical approach. Two different-nosed hard steel projectiles, including a blunt and a sphere, were used in order to obtain the ballistic impact of the target. ANSYS Autodyn was used to model a three-dimensional (3D) model that corresponds to a previous experimental study. The ballistic resistance of the target was numerically evaluated in terms of ballistic limit velocity, residual velocity, and energy absorption and compared at different incident angles such as 0°, 15°, and 30°. To validate the numerical outcomes, the Recht-Ipson model was used as a reference benchmark. The results of this investigation showed that when the incidence angle of a sphere-nosed projectile increased, the target's ballistic performance decreased. In contrast, the target’s ballistic resistance against a blunt-nosed projectile was little affected by the impact angle. According to the findings, the simulation results are consistent with the published numerical and experimental outcomes.