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In gearbox fault diagnosis, identifying the fault type and severity simultaneously, as well as the compound fault containing multiple faults, is necessary.

To diagnose multiple faults simultaneously, this paper proposes a multichannel and multi-task convolutional neural network (MCMT-CNN) model.

Experiments were conducted on a bearing dataset containing different fault types and severities and a gearbox compound fault dataset. The experimental results show that MCMT-CNN can effectively extract features of different tasks from vibration signals, with a diagnosis accuracy of more than 97%.

Vibration signals at different positions and in different directions are taken as the MC inputs to ensure the integrity of the fault features. Fault labels are established to retain and distinguish the unique features of different tasks. In MCMT-CNN, multiple task branches can connect and share all neurons in the hidden layer, thus enabling multiple tasks to share information.

This paper aims to guide the implementation of noise reduction measures in hoistway and reduce the aerodynamic noise generated by elevator operation, this paper aims to propose an aerodynamic noise analysis method that can solve the flow field in hoistway.

A turbulence-acoustic model solving the flow field in a hoistway and a numerical wind hoistway model of the ultra-high-speed elevator were established by using large eddy simulation (LES) and Curle acoustic theory.

The characteristics of pulsating flow field and aerodynamic noise around ultra-high-speed elevator are analyzed. The asymmetric characteristics of the flow field could be observed using the turbulent kinetic energy and the instantaneous vortexes in the wind hoistway model. Vortex shedding, air flow separation and recombination around the car were the key factors for aerodynamic noise generation. The sound pressure level was approximately linear to the logarithm of car speed. The increase of car deflection angle in a certain range would reduce the peak frequency of wake noise and increase the sound pressure level (SPL) value.

This paper provides important guidance for researches studying the aerodynamic noise in the hoistway and the technical personnel that look for the reduction measures, which greatly improves the shortcomings in the numerical simulation of the aerodynamic noise of the hoistway.

The paper aims to evaluate how progressive stakeholders view the adoption of contemporary techniques such as virtual technology in driving sustainable quality in an emerging economy context.

The authors adopted a systematic literature review to develop the theoretical framework for virtual reality (VR) technology adoption in sustaining quality in agriculture production. The framework was refined after discussion with a panel of academic experts. The refined theoretical framework was further empirically validated using Partial Least Square Structure Equation Modelling.

The study focuses on the future perspective of the perception for progressive farming with the adoption of VR technology in an emerging economy. The data were collected from the stakeholders (farmers, collectives, cooperative, etc.), for their future perspectives for the adoption of VR technology and sustainable quality agriculture production. The study may help build up VR technology in emerging economies which may take years to be established.

The perception of the future perspective of VR technology study conducted has limitations. The findings are well established on technology adoption; however, the technology used will take many extra years to find its application in the agriculture sector. The study offers insightful theoretical, managerial and policy implications for sustainable quality in agriculture production through the adoption of virtual reality (VR) technology. The authors found very few works that focused on VR technology adoption.

The study discusses VR, which has an impact on sustaining the quality of agriculture production. The study has notable managerial and policy implications that suggest the future perspective for VR technology in agriculture production. The study is an unexplored area that needs research to capture future perspectives.