Search Results (9)

Optimizing control specifications to prevent unbalance during the dehydration process in washing machine development is a complex task that consumes significant time and resources. Traditional methods involve expert engineers conducting various experiments and data analyses to develop optimal control specifications. However, these approaches are time-consuming and struggle to optimize diverse performance factors simultaneously. Additionally, the quality of the results heavily depends on the engineers’ experience and capabilities, making it challenging to maintain consistent quality. To overcome these limitations, a new data-driven approach is proposed. This study proposes a methodology that uses Bayesian Optimization to predict the unbalance during the dehydration process and derive optimal control specifications to minimize it. Bayesian Optimization builds a predictive model based on collected data and uses an acquisition function for efficient exploration to find the optimal solution. Through this method, we automated the optimization of unbalance prevention control specifications. Applying the proposed methodology to an actual washing machine model achieved performance equivalent to that derived by expert engineers. Specifically, we succeeded in maintaining the maximum vibration during the dehydration process below the target level and reducing the time to reach high-speed rotation (RPM) ranges. The main contribution of this study is the rapid derivation of machine learning-based optimized control specifications with minimal human intervention and small-scale experiments by building a test automation system within the home appliance development process. This approach shortened the development period and improved quality consistency. Full article

Simulating the experience of flight is a key objective of virtual reality (VR) technology. To enhance the sense of flying and immersion, we developed Drone Rider, a VR system that simulates free-flight atop a drone. In this study, we investigated whether delivering vibratory stimuli to the user’s feet could improve these sensations. While high-frequency drone propeller vibrations typically induce sensory numbness, alternative vibration patterns were explored. In Experiment 1, participants rated 13 different vibration patterns derived from various mechanical sounds, such as those from chainsaws, motorcycles, and washing machines. The motorcycle-based vibrations were most effective in enhancing both the sense of flight and immersion. In Experiment 2, we synthesized new vibration patterns by superimposing the highest-rated vibrations from Experiment 1, but no combination outperformed the original motorcycle vibration. These findings suggest that vibrations with multiple components below 100 Hz may reduce sensory adaptation and enhance the sense of flight and immersion in VR. This work provides valuable insights for developers aiming to optimize haptic feedback in VR flight simulators. Full article

Vibrating flip-flow screens are widely employed in the deep screening processes of coal washing, solid waste treatment, metallurgy, and other fields, playing a crucial role in enhancing product quality and production efficiency. The screen surface and material movement of vibrating flip-flow screens are highly complex, and there is currently insufficient understanding of their screening mechanism, limiting further optimization and application. In this paper, the Discrete Element Method (DEM), Finite Element Method (FEM), and Multi-Body Dynamics (MBD) were integrated to establish a numerical coupling model for vibrating flip-flow screens, considering material loads, screen surface deformation, and screen machine dynamics. The Response Surface Method was utilized to analyze the significant impact of relative amplitude, tension amount, amplitude of driving screen frame, vibration frequency, and screen surface inclination on screening efficiency and material velocity. The results indicate that the most significant factor influencing the screening of flip-flow screens is the screen surface inclination. Based on a BP neural network, a five-degree-of-freedom inclination surrogate model for flip-flow screens was established. The whale algorithm was employed for multi-objective optimization of the surrogate model, resulting in a screen surface inclination distribution that meets the requirements of different operating conditions. Full article

Due to friction vibration dampers’ inability to effectively dampen low loads during high-frequency dewatering, drum washing machines vibrated intensively. In order to address this problem, in this paper, a novel type of low-cost non-Newtonian fluid damper is proposed and investigated based on the non-Newtonian fluid shear thinning properties’ effect on vibration suppression during the high-frequency dewatering process of the washing machine. In contrast to other commonly used dampers, the homemade non-Newtonian fluid damper significantly suppresses the growth trend of the apparent elastic coefficient at high frequencies. A systematic investigation of damper structural parameters reveals that smaller gap height, higher piston head number, and more viscous fluid viscosity are adequate for vibration suppression and noise reduction. These results demonstrate that the non-Newtonian fluid damper can produce an excellent vibration-damping effect for the entire washing process of the washing machine, especially for the high-frequency dewatering process. The acceleration attenuation ratio can reach up to 83.49%, the energy attenuation is up to 98.44%, and the noise reduction is up to 10.38 dB. Full article

In this paper, an experimental methodology to characterize the noise paths in a washing machine with a horizontal axis was developed. The noise paths considered in this research were the noise that escapes through holes, the non-resonant path through the panels, and the noise radiated by the panels of the cabinet. The characterization method was based on several sound intensity measurements on the outside panels of the washing machine. In addition to these measurements, characterization of the radiation factor was performed by applying a method that relates intensity and vibration measurements while the structure of the washing machine is excited using a shaker. Applying the methodology to a washing machine, the main transmission path of the noise along the frequency domain where this home appliance has its highest values was identified. This methodology can provide the manufacturer with a guide to improve the acoustic performance of washing machines by applying noise control solutions in the noise path depending on the frequency domain. Full article

Underground gangue filling technology in coal mines is one of the effective ways to realize green mining. In this paper, a process of underground raw coal primary selection is proposed, which is based on a mechanical sieve jig as the main washing equipment. It refers to the structure of the ground mechanical moving sieve jig. It optimizes and improves the main structure of the jig machine’s driving mechanism and gangue discharge mechanism. It meets the requirements of the technology and the narrow space environment in the underground mine and realizes the effective separation of coal and gangue. In the jigging process of a moving sieve, it is very important to keep the jig bed stable and precisely control the quantity of gangue discharge for improving the system separation accuracy and efficiency. In this paper, a control method based on a fuzzy logic combination is proposed to realize the fuzzy logic control of the motor speed of gangue discharging, which aims at the nonlinear, time-varying uncertainty and pure lag characteristics of the control system of the underground moving sieve jig. Further industrial experiments were carried out and we obtained the variation law of the gangue’s quality in the moving sieve and the output curve of the gangue motor frequency under three working conditions. The experimental results show that the fuzzy logic control algorithm can quickly stabilize the jig bed in the vibrating sieve when the quantity of gangue changes abruptly or fluctuates greatly. It improves the separation efficiency of coal and gangue and effectively solves the problems of nonlinearity, time-varying and hysteresis in the control process of the moving sieve jig. Full article

Magnetorheological (MR) dampers have been widely investigated and proposed for vibration mitigation systems because they possess continuous variability of damping coefficient in response to different operating conditions. In the conventional design of MR dampers, a separate controller and power supply are required, causing an increment of complexity and cost, which are not suitable for home appliances like washing machines. To solve these issues and to reuse wasted energy from vibration of washing machines, in this study, a self-powered shear-mode MR damper, which integrates MR damping and energy-harvesting technologies into a single device, is proposed. The MR damper is composed of an inner housing, on which magnetic coils are wound directly, and an outer housing for covering and creating a closed magnetic circuit of the damper. The gap between the inner housing and the moving shaft is filled with MR fluid to produce the damping force. The energy-harvesting part consists of permanent magnets fastened together on the shaft and induction coils wound directly on slots of the housing. The induced power from the induction coils is directly applied to the excitation coils of the damping part to generate a corresponding damping force against the vibration. In order to achieve optimal geometry of the self-powered MR damper, an optimization for both the damping part and the energy harvesting part of the proposed dampers are conducted based on ANSYS finite element analysis. From optimal solutions, a prototype of the proposed damper is designed in detail, manufactured, and experimentally validated. Full article

Microelectromechanical system (MEMS)-based piezoelectric energy harvesting (PEH) devices can convert the mechanical vibrations of their surrounding environment into electrical energy for low-power sensors. This electrical energy is amplified when the operation resonant frequency of the PEH device matches with the vibration frequency of its surrounding environment. We present the electromechanical modeling of two MEMS-based PEH devices to transform the mechanical vibrations of domestic washing machines into electrical energy. These devices have resonant structures with a T shape, which are formed by an array of multilayer beams and a ultraviolet (UV)-resin seismic mass. The first layer is a substrate of polyethylene terephthalate (PET), the second and fourth layers are Al and Pt electrodes, and the third layer is piezoelectric material. Two different types of piezoelectric materials (ZnO and PZT-5A) are considered in the designs of PEH devices. The mechanical behavior of each PEH device is obtained using analytical models based on the Rayleigh–Ritz and Macaulay methods, as well as the Euler–Bernoulli beam theory. In addition, finite element method (FEM) models are developed to predict the electromechanical response of the PEH devices. The results of the mechanical behavior of these devices obtained with the analytical models agree well with those of the FEM models. The PEH devices of ZnO and PZT-5A can generate up to 1.97 and 1.35 µW with voltages of 545.32 and 45.10 mV, and load resistances of 151.12 and 1.5 kΩ, respectively. These PEH devices could supply power to internet of things (IoT) sensors of domestic washing machines. Full article

Reduction of noise generated by devices is an important problem, both in industrial environments where high sound pressure levels may damage hearing, and in households where the sound pressure level is usually moderate, but may cause discomfort and stress. Classically used passive methods often have poor performance for low frequencies. Alternatively, active control can be used to improve noise reduction in this frequency range. In the proposed approach, noise generated by devices may be reduced by controlling vibrations of the casing. The authors previously confirmed the performance of the proposed active control approach using a dedicated noise-canceling casing. Herein, we describe further development and application of the method to an off-the-shelf washing machine. Electrodynamic actuators were installed on four walls of the washing machine. The performance of the control systems was experimentally evaluated during the real spinning phase and the results are reported here. Full article