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A magnetorheological fluid (MR fluid) is mainly composed of soft magnetic particles, surfactants, and the base carrier fluid. Among these, soft magnetic particles and the base carrier fluid influence the MR fluid significantly in a high-temperature environment. Therefore, a study was carried out to investigate the changes in the properties of soft magnetic particles and base carrier fluids in high-temperature environments. On this basis, a novel magnetorheological fluid with high-temperature resistance was prepared, and the novel magnetorheological fluid had excellent sedimentation stability, of which the sedimentation rate was only 4.42% after heat treatment at 150 °C followed by one-week placement. At 30 °C, the shear yield stress of the novel fluid was 9.47 kPa under the magnetic field of 817 mT: higher than the general magnetorheological fluid with the same mass fraction. Moreover, its shear yield stress was less affected by the high-temperature environment, reducing by only 4.03% from 10 °C to 70 °C. The novel MR fluid can be applied to a high-temperature environment, effectively expanding the application range of MR fluid. [ABSTRACT FROM AUTHOR]

Magnetorheological (MR) fluid in power transmission devices, especially in high-power transmission devices, sometimes works at high temperatures owing to wall slip, particle friction, and exciting current. In such cases, effective heat dissipation is crucial. A novel water-cooling structure is proposed to deal with the negative effect of centrifugal force on heat dissipation. The magnetic circuit of the novel MR transmission device is designed on the basis of electromagnetic theory, and the magnetic field is investigated by finite element calculation. Experiments under extreme condition show that the temperature of MR fluid in the device drops sharply from 70 °C to 28 °C, and the heat generated inside the device dissipates instantly. Results show that the novel power transmission device has excellent heat dissipation effect. [ABSTRACT FROM AUTHOR]

High-precision tension control is very important for industrial production. Benefit from the unique property of magnetorheological (MR) fluid, a MR clutch is a potential device in a tension control system due to its fast response and large output dynamics. In this paper, based on the detailed analysis of axial magnetic induction intensity generated by the coil along the radial distribution, a shear-mode MR clutch with uniform magnetic field distribution along the radial direction is proposed for the tension control system. A theoretical model of torque transmission and a magnetic circuit were derived, and a magnetostatic simulation was carried out to validate the effectiveness of the proposed circuit design. Experimental evaluation was conducted to investigate the static and dynamic transmission torque property. Finally, a proportional–integral–differential controller was designed to regulate the output torque. Experimental testing demonstrated the effectiveness and practical feasibility of the MR clutch in tension control. [ABSTRACT FROM AUTHOR]

As a strong nonlinear complex system, the mine main ventilator is difficult to select eigenvalues of the ventilator fault. This study proposed a multiple eigenvalue selection method based on ensemble empirical modal decomposition (EEMD). Firstly, an experimental platform of axial flow fan was built to simulate the bearing fault and fan blade fault. Secondly, the vibration and wind pressure data of the above three faults and the normal state were collected, and the vibration signals were decomposed by EEMD. The normalized Root Mean Square Error was used to evaluate the signal separation degree of different faults under the same eigenvalue and to select the eigenvalue. Then, combined with wind pressure information, multi-data information fusion was used to construct the failure indicator vector table. Finally, the BP neural network was trained and tested with a vector table, and the fault diagnosis of the mine main ventilator was achieved. The experiment results showed that the diagnostic accuracy of test results was 98.87% after eigenvalue selection and data fusion. The method has high accuracy and adaptability, and is very suitable for mechanical equipment such as mine ventilator. [ABSTRACT FROM AUTHOR]

As a strong nonlinear complex system, the mine main ventilator is difficult to select eigenvalues of the ventilator fault. This study proposed a multiple eigenvalue selection method based on ensemble empirical modal decomposition (EEMD). Firstly, an experimental platform of axial flow fan was built to simulate the bearing fault and fan blade fault. Secondly, the vibration and wind pressure data of the above three faults and the normal state were collected, and the vibration signals were decomposed by EEMD. The normalized Root Mean Square Error was used to evaluate the signal separation degree of different faults under the same eigenvalue and to select the eigenvalue. Then, combined with wind pressure information, multi-data information fusion was used to construct the failure indicator vector table. Finally, the BP neural network was trained and tested with a vector table, and the fault diagnosis of the mine main ventilator was achieved. The experiment results showed that the diagnostic accuracy of test results was 98.87% after eigenvalue selection and data fusion. The method has high accuracy and adaptability, and is very suitable for mechanical equipment such as mine ventilator. [ABSTRACT FROM AUTHOR]

Benchmarking is one of the key management approaches to support companies to continuously improve and gain competitive advantage. However, previous benchmarking management suffered from subjectivity and one-sidedness, and the benchmarking evaluation was only to identify the benchmark and its own deficiencies, with a high degree of independence between the sub-processes. The framework is the first to jointly apply topic mining and relation extraction techniques to establish an objective index system and mine the mechanistic relations among the indexes, and finally provides a concise and interactive display of the results based on knowledge graph visualization. In this study, 50 oil and gas companies are taken as examples to carry out the case study of sustainable development benchmarking management, and a sustainable development program with strong logic and systematicity is proposed at both macro and micro levels. This study results verify that the framework can effectively improve the scientific, comprehensive and systematic nature of sustainable development benchmarking management. At the same time, the framework extends the role of the index system so that it can provide the necessary mechanistic guidance for subsequent sustainable development programmatic to achieve programmatic with a high degree of synergy. In addition, the framework has a high degree of coherence with the United Nations Sustainable Development Goals (SDGs), and the proposals put forward can not only be used to improve the sustainable development capability of companies themselves, but also contribute to the realization of the SDGs. [Display omitted] • A novel sustainable development benchmarking framework for energy companies. • A first joint application of topic mining and relation extraction for benchmarking. • Energy companies should promote localization and diversification of the workforce. • Energy companies should expand joint venture projects with developing country. [ABSTRACT FROM AUTHOR]