Effect of Silicon Carbide Nanoparticles on the Friction-Wear Properties of Copper-Based Friction Discs

To study the influence of nano-additives on the friction-wear characteristics of friction materials, the nano-sized silicon carbide particles which have excellent chemical and physical properties are considered to add in composite to form the modified friction material. The influence of the silicon carbide nanoparticles (SCN) on the friction-wear characteristics of copper-based friction materials (CBFM) is investigated via the SAE#2 (made in Hangzhou, China) clutch bench test with the applied pressure, rotating speed, and automatic transmission fluid (ATF) temperature taken into account. Moreover, the variations of friction torque and temperature are considered to evaluate the friction performance, and the variable coefficient is employed to describe the friction stability. The wear characteristics of friction materials are investigated by the disc changes in thickness and micro-morphology. The results show that the CBFM with SCN can provide a higher friction torque, which increased by 30% to 50% compared with CBFM. The variable coefficient of CBFM with SCN changes from 674 to 52 with the rotating speed raised from 600 rpm to 3000 rpm, which shows that the friction stability is relatively worse. Furthermore, the micromorphology shows that the CBFM with SCN has lower porosity and surface roughness, which increases the microscopic contact area and the coefficient of friction (COF). Simultaneously, the reduction in porosity also leads to a decrease in the cooling quality, bringing about a rapid temperature rise. Thus, the wear amount of CBFM with SCN increases significantly, especially for the friction disc in the axial middle position.

Simulation and Experimental Study on Characteristics of Multiorifice Nozzle in Radial Jet Drilling

The radial jet drilling (RJD) is a key technology to improve the development efficiency of low-permeability oil and gas resources. In order to seek a reasonable hydraulic engineering parameter combination of hydraulic radial jet drilling, to obtain the optimal hydraulic energy distribution, a jet radial horizontal drilling simulation experiment system of the casing windowing is designed. A sequence of experimental investigations focused on engineering parameters of pump displacement, rotating speed, and frequency of high-pressure plunger pump is performed, and the operability and the feasibility of the experiment are verified. To evaluate the maximum drillable length and the self-propelled force of a jet nozzle, a 3D numerical model based on ANSYS-CFX is developed to evaluate the effects of the inlet flow displacement, the flow rates ratio K , and the angle ratio F : B of the forward orifice and backward orifice of the jet nozzle on its maximum drillable length and self-propelled force by sensitivity analysis. Finally, the comparison of numerical simulation results (Ln), mathematical results (Lm), and experiment results (Le) of the maximum drillable length are presented. It is observed that the simulation results are consistent with the experiment results with an average accuracy of 97.07%. Therefore, the proposed numerical model has a good performance in predicting the maximum drillable length of the multiorifice nozzle. The research results can provide theoretical guidance for improving the rock breaking and drilling capability of radial jet drilling technology.

Diagnosis for Slight Bearing Fault in Induction Motor Based on Combination of Selective Features and Machine Learning

Induction motors are widely used in industry and are essential to industrial processes. The faults in motors lead to high repair costs and cause financial losses resulting from unexpected downtime. Early detection of faults in induction motors has become necessary and critical in reducing costs. Most motor faults are caused by bearing failure. Machine learning-based diagnostic methods are proposed in this study. These methods use effective features. First, load currents of healthy and faulty motors are measured while the rotating speed is changing continuously. Second, experiments revealed the relationship between the magnitude of the amplitude of specific signals and the rotating speed, and the rotating speed is treated as a new feature. Third, machine learning-based diagnoses are conducted. Finally, the effectiveness of machine learning-based diagnostic methods is verified using experimental data.

Band gap characteristics of friction stir additive manufactured phononic crystals

Additive Manufacturing (AM) is widely used to fabricate phononic crystals (PnCs) in recent years. Friction Stir Additive Manufacturing (FSAM) is a new-type solid state fabrication technology which is fusion free with low distortions. FSAM was selected to fabricate the designed PnCs. The manufactured specimen was distorted due to the temperature rise in the manufacturing process and the band gaps (BGs) were changed with the distortions. Results indicate that the band gap of the PnCs moves to be in higher frequency domain due to the residual distortions of the manufactured PnCs. The residual distortion of FSAM PnCs is 2.77 times smaller in comparison with the Tungsten Inert Gas (TIG) welding. So, the differences of the band gap between the designed PnCs and the FSAM specimen are only in the range of 0.15%- 0.55% due to the lower temperature rise in FSAM. The further analysis shows that the change of the BGs is caused by the growth of the inertia moment for the FSAM PnCs. With the increase of the rotating speed in FSAM, the residual distortion of the FSAM PnCs is increased due to the increase of the welding temperature. This can lead to the increase of the inertia moment, which is the key reason for the increase of the BG characteristics of the FSAM PnCs.

Production and Optimization of Bio-Based Silica Nanoparticle from Teff Straw (Eragrostis tef) Using RSM-Based Modeling, Characterization Aspects, and Adsorption Efficacy of Methyl Orange Dye

The brown teff straw was utilized in this study to produce silica using the sol-gel technique. After pretreatment, the raw material of brown teff straw was characterized. The data were analyzed using the central composite design and response surface technique, and four independent parameters, namely, temperature, NaOH concentration, rotational speed, and extraction time, were evaluated for process optimization. Before extracting silica with an alkaline solution, the silica content in the ash was determined using an AAS spectrometer. The silica content of teff straw ash is around 92.89%. The ash was treated with NaOH solution in the concentrations range of 1 M to 3 M (0.5 M interval). The extraction time varied at intervals of 55, 70, 85, 100, and 115 minutes. Temperatures were changed using magnetic stirrer equipment in the range of 80°C to 100°C (5°C interval). At 350 rpm, 400 rpm, 450 rpm, 500 rpm, and 550 rpm, the rotating speed was adjusted. The best extraction conditions for amorphous silica were 1.50 M NaOH, 109.99 min, 94.98°C, and a rotating speed of 499.57 rpm, with a maximum yield of 85.85%. XRD and FTIR analyses were used to assess the physicochemical characteristics of the extracted silica. The aqueous solutions of methyl orange were used to test the adsorption efficiency of silica. The percent of removal efficiency for methyl orange was 90.48%.

Experimental and Numerical Analysis of the Impeller Backside Cavity in a Centrifugal Compressor for CAES

Relying on a closed test rig of a high-power intercooling centrifugal compressor for compressed air energy storage (CAES), this study measured the static pressure and static temperature at different radii on the static wall of the impeller backside cavity (IBC) under variable rotating speeds. Simultaneously, the coupled computations of all mainstream domains with IBC or not were used for comparative analysis of the aerodynamic performances of the compressor and the internal flow field in IBC. The results show that IBC has a significant impact on coupling characteristics including pressure ratio, efficiency, torque, shaft power, and axial thrust of the centrifugal compressor. The gradients of radial static pressure and static temperature in IBC both increase with the decrease of mainstream flow or the increase of rotating speed, whose distributions are different under variable rotating speeds due to the change of the aerodynamic parameters of mainstream.

Characteristics of Hydraulic and Electric Servo Motors

Until the 1970s, hydraulic actuators were widely used in many mechanical systems; however, recently, electric motors have become mainstream by virtue of their improved performance, and hydraulic motors have largely been replaced by electric motors in many applications. Although this trend is expected to continue into the future, it is important to comprehensively evaluate which motor is most suitable when designing mechanical systems. This paper presents the results of a survey of the performance of electric and hydraulic servo motors and aims to provide quantitative data that can be used as a reference for selecting appropriate motors. We surveyed AC, AC direct, brushless DC, and brushed DC electric motors and swash plate-type axial piston, bent axis-type axial piston, crank-type radial piston, and multistroke-type radial piston hydraulic motors. Performance data were collected from catalogs and nonpublic data. We compared and evaluated the characteristics of these diverse servo motors using indexes such as torque, rotating speed, output power, power density, and power rate.

Maximization of Tensile Strength of Aluminum 6061 Alloy T6 Grade Friction Welded Joints by Using the Desirability Function

Various joining techniques are consistently used in fabrications and maintenance applications of numerous parts in manufacturing industries. Typically, the friction welding technique acquired attention in joining of aluminum and its different alloys for very general structural usages in small to medium to large-scale manufacturing sectors. This is an experimental attempt to weld aluminum 6061 alloy T6 grade of 3mm thickness metal sheets. The hexagonal-shaped steel pin of grade H13 is used. The experiment is performed by using the Taguchi L9 approach, and nine welded specimens are prepared. The chosen factors are rotating speed of the tool, tilting angle, and feed. After the welding, the tensile testing is followed for the measurement of strength of the welded samples. The analysis suggested that the chosen working limits of feed and rotational speed is significant and having impacts on weld strength. The maximum strength is obtained as 212MPa when the ranges of above said factors are 560RPM, 0degree, and 20mm/min.

DESIGN AND EXPERIMENTAL STUDY OF FLEXIBLE THRESHING UNIT FOR CHINESE CABBAGE SEEDS

In order to solve the problems of low efficiency of artificial harvesting method and high breakage rate and undepurated rate of traditional threshing method, a new flexible threshing device of Chinese cabbage seeds was designed, which was composed of flexible round head nail teeth and circular tube concave plate. Hertz contact collision theory was used to analyze and determine the structural parameters of the new threshing unit. The interaction force of different threshing elements materials were analyzed by using EDEM. The feasibility of the flexible threshing unit was verified by the comparison test of the distribution of threshed mixture. Finally, the orthogonal test was carried out to study the influence of the movement parameters of each structure on the cleaning rate and the rate of undepurated, and the weight matrix method was used to optimize it. The results indicate that under the condition the rotating speed of the threshing cylinder 750 rpm, the concave clearance 20 mm, and the feeding rate 1.4 kg/s, the threshing performance of the flexible threshing unit was the best. At this time, the breaking rate was 0.064%, and the un-threshing rate was 0.67%, which both met the relevant industry standards.

Bearing fault diagnosis using a speed-adaptive network based on vibro-speed data fusion and majority voting

Fault diagnosis of rolling bearings is key to maintain and repair modern rotating machinery. Rolling bearings are usually working in non-stationary conditions with time-varying loads and speeds. Existing diagnosis methods based on vibration signals only don’ t have the ability to adapt to rotational speed. And when the load changes, the accuracy rate of them will be obviously reduced. A method is put forward which fuses multi-modal sensor signals to fit speed information. Firstly, the features are extracted from raw vibration signals and instantaneous rotating speed signals, and fused by 1D-CNN-based networks. Secondly, to improve the robustness of the model when the load changes, a majority voting mechanism is proposed in the diagnosis stage. Lastly, Multiple variable speed samples of four bearings under three loads are obtained to evaluate the performance of the proposed method by analyzing the loss function, accuracy rate and F1 score under different variable speed samples. It is empirically found that the proposed method achieves higher diagnostic accuracy and speed-adaptive ability than the algorithms based on vibration signal only. Moreover, A couple of ablation studies are also conducted to investigate the inner mechanism of the proposed speed-adaptive network.