Early detection of faults in DC motors extends their life and lowers their power usage. There are a variety of traditional and soft computing techniques for detecting faults in DC motors. Many diagnostic techniques have been developed in the past to detect such fault-related patterns. These methods for detecting the aforementioned potential failures of motors can be utilized in a variety of scientific and technological domains. Motor Power Pattern Analysis (MPPA) is a technology that analyzes the current and voltage provided to an electric motor using particular patterns and protocols to assess the operational status of the motors without disrupting production. Engineers and researchers, particularly in industries, face a difficult challenge in monitoring spinning types of equipment. In this work, we are going to explain how to use the motor power pattern/signature analysis (MPPA) of a power signal driving a servo to find mechanical defects in a gear train. A hardware setup is used to simplify the demonstration of obtaining spectral metrics from the power consumption signals. A DC motor, a set of metal or nylon drive gears, and a control circuit are employed. The speed control circuit was eliminated to allow direct monitoring of the DC motor's current profiles. Infrared (IR) photo-interrupters with a 35 mm diameter, eight-holed, standard servo wheel were employed to gather the tachometer signal at the servo's output. The mean value of the measurements was 318 V for the healthy profile, while it was 330 V for the faulty gears power data. The proposed power consumption profile analysis approach succeeds to recognize the mechanical faults in the gear-box of a DC servomotor via examining the mean level of the power consumption pattern as well as the extraction of the Power Spectral Density (PSD) through comparing faulty and healthy profiles

The difficulty of delivering electrical power to rural areas motivated the researchers to explore more accessible power sources. Hydropower is considered a desirable option due to its sustainability and lower costs. Pelton turbines have been widely used in hydropower plants because of their low installation and maintenance costs. This study provides a computational fluid dynamics (CFD) model for Pelton turbine performance under various flow conditions. The model is based on the conservation of mass principle, Newton’s second law, and the first law of thermodynamics. It is used to predict the torque produced by a turbine at different rotational speeds. Previously published experimental results for the same turbine geometry and flow parameters were used to validate the model’s predictions. Validation revealed that the model can reproduce the experimental results. This provides the required robustness for its use as a tool for turbine design and modification.

Compression buckling experimental tests was carried out for long and intermediatecolumns made of 6061-T4 AL- alloy. Two different soil corrosion time were adopted i.e.30days and 60 days using 27 samples. The experimental analysis revealed that increasing thecorrosion time negatively affects the mechanical properties of metals such as the specimensof 60 days corroded have 1.68% reduction in ultimate strength, also increasing the corrosiontime reduces the critical load such as the maximum reduction was 4.24% in critical bucklingload for 60 days corrosion time. Perry-Robertson theory was applied to the experimentaldata and it was found that the above theory can satisfactory predicted the critical bucklingload (Pcr) with a factor of safety equal to 1.2. The ratio of corroded Pcr to dry Pcr wasalways less than unity. This indication explains the effect of pitting corrosion on bucklingbehavior of 6061-T4 AL- alloy

This paper presents a novel method which is designed to detect the rotor position at standstill and also low speeds in switched reluctance motor (SRM). In this paper the inductance of phase winding is added as a part in Colpitts oscillator and will cause a change in oscillation frequency according to the rotor position. The phase inductance regularly varies with the rotor position. Experiments were carried out on three phases SRM 6/4, where the measured frequency of colpitts oscillator was converted into a voltage value by the frequency to voltage converter and were then converted into a digital value to be matched with the proposed digital processing. The Experimental results showed high accuracy in determining the values of phase inductance, which produced an estimated rotor position accurately and quickly.

This research is devoted to study the influence of different weight percent concerning to the additions of Ti and Cu on mechanical and tribological properties of AA6061. The composite materials consist of different weight percentage of Ti (0.2, 0.4, and 0.6) wt% and constant weight percentage of Cu (0.2) wt% which were fabricated by liquid metallurgy route technique. Microstructural characterization and phases have been examined by using SEM (scanning electron microscopic).SEM examination showed uniform distribution of nano Ti and Cu in AA6061. The consequences of mechanical tests demonstrated clear enhancement in mechanical properties, such as ultimate tensile strength, yield strength, young modulus, ductility% and hardness at additive percentage of 0.4% Ti+0.2%Cu nano particles incorporated into molten AA6061. Percentage of enhancement ultimate tensile strength is about 73.3%, yield strength about 82.7%, young modulus is about 21.2%, the  Vickers hardness about 42.6% and the decreasing in ductility was about 25.2% compared with the metal matrix (AA6061). The wear rate test was performed by using pin on disc rig for both hybrid nano composite and base metal (AA6061) under various loads (10,15and 20) N with sliding speed (1.282) m/sec at a (10) min’s time. The results showed a decrease in wear rate at 0.4%Ti+0.2%Cu compared with the base metal (AA6061). Improvement percentage of wear rate is about 105% at 20 N load.