Recent Patents on Mechanical Engineering - Volume 15, Issue 5, 2022

Background: Tooth surface wear is inevitable in helical geared transmission. Consequently, the worn profile deviates from the ideal involute one. As a result, the structural stiffness of worn tooth and contact stiffness of tooth-pair are both changed. Methods: This work presents an improved calculation method for structural stiffness of worn teeth by combining slicing and potential energy method, considering non-uniform distribution of wear amount along the tooth surface. Then, a nonlinear contact stiffness model is employed to investigate the influence of wear on contact stiffness. Meanwhile, taking wear as one kind of profile deviation, the analytical model of time-varying mesh stiffness (TVMS) of helical gear pair is derived. Furthermore, governing equations with 6 degree-of-freedom are established and influences of wear on dynamic responses are revealed. Results: Results indicate that structural stiffness of worn teeth decreases but contact stiffness does not always keep increasing or decreasing. The fluctuation of dynamic transmission error with the nonlinear contact model is not as significant as that from the constant contact stiffness model. Conclusion: The approach presented in this work is suitable for condition monitoring of helical gears in view of long-term service.

Background: When driving and working, the engine, working equipment and uneven road surface will cause severe vibrations to the wheeled excavator, which can affect efficiency and comfort. This paper discusses various patents and presents a new method of vibration reduction for excavators. Objective: The research aims to design the excavator's counterweight as a tuned mass damper (TMD) to reduce body vibration. Methods: The recent patents of TMD were investigated in this research. In this paper, the counterweight of the excavator is designed as a non-linear TMD system. The vibration models were established under the driving and crushing conditions, respectively. The vibration response of the vehicle body was calculated and analyzed through MATLAB/Simulink under driving and crushing conditions. Finally, the damping characteristics of the TMD system were discussed. Results: The vibration of the car body can be reduced by TMD. The improvement rates in vertical acceleration were 8.05%, 11.85% and 11.15% for the three classes of road surfaces for the driving conditions. The improvement rates of vertical accelerations for the three powers of crushing conditions are 16.18%, 18.32% and 23.48%, respectively. Conclusion: The vibration damping performance of the excavator was effectively improved by TMD in the main working conditions. The variation of body vertical acceleration with TMD parameters indicates the existence of optimal damping characteristics parameters for the TMD system at a fixed road surface and vehicle speed.

Background: Among the metals used in foundry, we find the austenitic stainless steels, which are used in several fields because of their mechanical properties, which can change during the heat treatments; for that, it is important to understand and control the growth of the austenite grains. Objective: Modeling austenite grain growth by considering the effects of heating temperature, holding time, and initial austenite grain size on austenite grain growth. Methods: In this paper, the austenite grain growth process of AISI 302 steel was studied in a temperature range of 900 to 1000 °C and a holding time of up to 360 minutes. Based on the experimental results and a combination of Arrhenius and Sellars type equations, a mathematical model of austenite grain growth was developed. Results: From the experimental part, it was found that the increase in heating temperature caused the dissolution of carbides; therefore, the size of austenite grains grew faster, implying a higher growth rate. The prolongation of the holding time also led to the increase in the size of the austenite grains. Conclusion: Based on statistical indicators and a comparison between experimental and predicted results, the ability of the model to predict austenite grain growth was confirmed.

Objective: In order to further study the characteristics of flow parameters in the wellbore during solid fluidization drilling, based on the physical model of solid fluidization exploration of hydrate reservoir, a gas-liquid-solid three-phase flow model is established during the drilling process. Methods: The parameter changes of wellbore pressure, section gas holdup, liquid volume fraction, temperature and wellbore hydrate decomposition rate under the influence of different wellhead choke pressure, displacement and drilling fluid density during solid fluidization are analyzed. Results: The analysis results of the case will show that under different wellhead choke pressures, hydrate begins to decompose at 400m to 500m, and with the increase in wellhead choke pressure, the wellbore pressure and the volume fraction of liquid and solid phase at the same position increase significantly, and the gas production rate and the gas volume fraction decrease. The results also show that under different drilling fluid rates, hydrate begins to decompose at 500m to 550m, and with the increase in drilling fluid rate, bottomhole pressure and wellbore temperature increase, the situation of hydrate decomposition becomes better, and gas volume fraction decreases. Conclusion: With the increase of drilling fluid density, hydrate begins to decompose at 500m to 600m, the wellbore temperature increases, and the hydrate decomposition is delayed. Meanwhile, the difference in the location of hydrate decomposition becomes smaller.

Background: With the rapid development of the power system, oil-immersed transformers are widely used in the substation and distribution system. The faults of oil-immersed transformers are a large threat to the power system. Therefore, it is significant that the faults of oil-immersed transformers can be diagnosed accurately. Objective: To accurately diagnose the faults of oil-immersed transformers through machine learning methods and swarm intelligence algorithms. Methods: To accurately diagnose the faults of oil-immersed transformers, a fault diagnosis method based on T-distributed stochastic neighbor embedding and support vector machine is proposed. The improved beetle antennae search algorithm is used to optimize the parameters of the support vector machine. Firstly, the non-coding ratio method is used to obtain nine-dimensional characteristic indices. Secondly, the original nine-dimensional data are reduced to three-dimensional by T-distributed stochastic neighbor embedding. Lastly, the data after dimensionality reduction are used as the input of the support vector machine optimized by improved beetle antennae search algorithm and the fault types of transformers can be diagnosed. Results: The accuracy rate is 94.53% and the operation time is about 1.88s. The results indicate that the method proposed by this paper is reasonable. Conclusion: The experimental results show that the method proposed by this paper has a high accuracy rate and low operation time. Mixed faults that are difficult to diagnose also can be diagnosed by this paper's method. In the era of big data, there is a lot of data on transformers, so the method proposed in this paper has certain engineering significance.

Background: In response to the current need for the development of large-scale wheat combine harvesters, this paper carried out the structural design and performance test of a large feed volume wheeled wheat combine harvester. Methods: Based on the characteristics of wheat plants, this paper designed a wheeled wheat combine harvester with a feed rate of 10kg/s. Subsequently, the structural parameters and design process of the main working components, such as the header feeding device, the conveying device, the threshing device, the separation and cleaning device, the walking device, the cab, and the straw crushing device, are elaborated. The strength of the key parts was checked by finite element simulation, and the structural parameters were optimized. Results: The results show that the large feed volume combine harvester which designed in this paper can achieve an entrainment loss rate of less than 2.39% and a cleaning loss rate of less than 0.26%, significantly lower than the current 3% loss rate and there is almost no unclean and broken situation. Conclusion: This research provides a reference for the design of a large feed volume combine harvester.

Background: Technological progress is based on the development of different types of materials. Among the materials most solicited, we mention metals and alloys. The development of these materials has been initiated and resulted in a wide range of metallic materials, including austenitic manganese, constituting, until today, a center of interest for various research works given their wide use in the industry as well as the recent progress by observation and characterization instruments. Objective: The aim of the paper is to investigate the heat treatment conditions of high manganese austenitic steel and to determine their influence on the structure and mechanical properties. Methods: The samples were subjected to an austenitization treatment at five different temperatures: 980 °C, 1000 °C, 1020 °C, 1040 °C, and 1060 °C for 1 hour. The experimental techniques used are hardness, nanoindentation tests, optical microscopy and X-ray diffraction. Hardness and microhardness measurements were performed to determine the wear behavior of the studied steels. Results: The results indicated that the temperature affects the microstructure; by increasing the austenitizing temperature with pronounced growth of the austenite as well as the dissolution of carbides M7C3, the nano hardness and the modulus of elasticity decreases considerably. Conclusion: The heat treatment of materials modifying the microstructure is closely related to the mechanical behavior of the austenitic manganese steel. Therefore, the control of structural changes by heat treatment is essential to obtain the desired properties. The established heat treatment conditions of the obtained steel can be suitable for several industrial applications.