Abstract

Condition monitoring can reduce machine breakdown losses, increase productivity and operation safety, and therefore deliver significant benefits to many industries. The emergence of wireless sensor networks (WSNs) with smart processing ability play an ever-growing role in online condition monitoring of machines. WSNs are cost-effective networking systems for machine condition monitoring. It avoids cable usage and eases system deployment in industry, which leads to significant savings. Powering the nodes is one of the major challenges for a true WSN system, especially when positioned at inaccessible or dangerous locations and in harsh environments. Promising energy harvesting technologies have attracted the attention of engineers because they convert microwatt or milliwatt level power from the environment to implement maintenance-free machine condition monitoring systems with WSNs. The motivation of this review is to investigate the energy sources, stimulate the application of energy harvesting based WSNs, and evaluate the improvement of energy harvesting systems for mechanical condition monitoring. This paper overviews the principles of a number of energy harvesting technologies applicable to industrial machines by investigating the power consumption of WSNs and the potential energy sources in mechanical systems. Many models or prototypes with different features are reviewed, especially in the mechanical field. Energy harvesting technologies are evaluated for further development according to the comparison of their advantages and disadvantages. Finally, a discussion of the challenges and potential future research of energy harvesting systems powering WSNs for machine condition monitoring is made.

Highlights

  • Condition monitoring is a process of judging the health status of a mechanical system, which uses various types of data to achieve change-point detection and provide a timely decision for the maintenance works [1]

  • Though significant progress has been made in various aspects, these energy harvesting (EH) technologies still have challenging deficiency of providing insufficient electricity to power the sensor nodes of wireless sensor networks (WSNs) for real-time machine condition monitoring

  • Various forms of kinetic energy induced by the motion of objects, elastic energy caused by the deformation of objects and electric potential energy resulting from conservative coulomb forces are the main mechanical energy sources found in industrial applications

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Summary

Introduction

Condition monitoring is a process of judging the health status of a mechanical system, which uses various types of data (such as temperature, vibration, strain, rotating speed, displacement, pressure, voltage, current, acoustics and operator experience) to achieve change-point detection and provide a timely decision for the maintenance works [1]. Inexhaustible energy energy sources sources are are likely likely to to exist exist in in the the environment environment around around the the mechanical mechanical systems These different forms of energy provide the possibility of supplementing or replacing additional batteries for supplying power to WSNs for machine condition monitoring in order to achieve a true wireless and maintenance-free system. Though significant progress has been made in various aspects, these EH technologies still have challenging deficiency of providing insufficient electricity to power the sensor nodes of WSN for real-time machine condition monitoring. Hybrid nanogenerators have improved the performance of energy harvesters He et al [27] has fabricated a hybrid nanogenerator through integrating the triboelectric and piezoelectric effects with electromagnetic induction to supply continuous and reliable power for transmission of temperature and vibration data. The challenges and future developments of EH technologies applied to machine condition monitoring is investigated and recommendations are made

Power Demands and Resources of WSN based Condition Monitoring
Power Consumption of a WSN based System
80 MHz or 160 MHz
Potential Energy Harvesting Sources in Machines
Local thermal imaging of mechanical components:
Energy Harvesting Techniques and Applications
Light Energy Harvesting
Relationship
Electromagnetic Energy Harvesting
Thermal Energy Harvesting
Thermoelectric Energy Harvesting
Thermoelectric
Pyroelectric Energy Harvesting
Mechanical
Piezoelectric Energy Harvesting
12. Schematic
Triboelectric Energy Harvesting
14. Structure the designed hybridized
Electrostatic Energy Harvesting
Hybrid Energy Harvesting
Wireless Sensor Network based Machine Condition Monitoring
16. Schematic
17. They are installed on
17. Electromagnetic magnetic levitation levitation
Findings
Conclusions

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