Making use of nanoenergy from human – Nanogenerator and self-powered sensor enabled sustainable wireless IoT sensory systems

Technology evolution from self-powered sensors to AIoT enabled smart homes

Vibration‐based piezoelectric, electromagnetic, and hybrid energy harvesters for microsystems applications: A contributed review

A low-frequency rotational electromagnetic energy harvester using a magnetic plucking mechanism

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.

Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review.

This paper investigates the performance of the conventional bispectrum (CB) method and its new variant, the modulation signal bispectrum (MSB) method, in analysing the electrical current signals of induction machines for the condition monitoring of rotor systems driven by electrical motors. Current signal models which include the phases of the various electrical and magnetic quantities are explained first to show the theoretical relationships of spectral sidebands and their associated phases due to rotor faults. It then discusses the inefficiency of CB and the proficiency of MSB in characterising the sidebands based on simulated signals. Finally, these two methods are applied to analyse current signals measured from different rotor faults, including broken rotor bar (BRB), downstream gearbox wear progressions and various compressor faults, and the diagnostic results show that the MSB outperforms the CB method significantly in that it provides more accurate and sparse diagnostics, thanks to its unique capability of nonlinear modulation detection and random noise suppression.

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A Performance Evaluation of Two Bispectrum Analysis Methods Applied to Electrical Current Signals for Monitoring Induction Motor-Driven Systems

A novel bistable electromagnetic vibration energy harvester (BEMH) is constructed and optimized in this study, based on a nonlinear system consisting mainly of a flexible membrane and a magnetic spring. A large-amplitude transverse vibration equation of the system is established with the general nonlinear geometry and magnetic force. Firstly, the mathematical model, considering the higher-order nonlinearities given by nonlinear Galerkin method, is applied to a membrane with a co-axial magnet mass and magnetic spring. Secondly, the steady vibration response of the membrane subjected to a harmonic base motion is obtained, and then the output power considering electromagnetic effect is analytically derived. On this basis, a parametric study in a broad frequency domain has been achieved for the BEMH with different radius ratios and membrane thicknesses. It is demonstrated that model predictions are both in close agreement with results from the finite element simulation and experiment data. Finally, the proposed efficient solution method is used to obtain an optimizing strategy for the design of multi-stable energy harvesters with the similar flexible structure.

Dynamic Modeling and Structural Optimization of a Bistable Electromagnetic Vibration Energy Harvester

Abstract: there have recently been significant enhancements in Micro-Electro-Mechanical Systems (MEMS) technologies, which have provided an easier and cheaper means of condition monitoring for rotating machines by installing MEMS accelerometers directly onto rotors. One critical issue in using on-rotor MEMS accelerometers is extracting the real tangential acceleration from accelerometer outputs which also contain gravitational acceleration. This paper studies and compares two different methods that can be used to eliminate the gravitational acceleration so as to characterise the rotor dynamics precisely. In the first method, the pure tangential acceleration is reconstructed by combining two orthogonal outputs of a single MEMS accelerometer attached to the rotating part. The second method uses two MEMS accelerometers mounted diametrically opposite each other on the reciprocating compressor flywheel, allowing the gravitational acceleration signal to be cancelled by summing the acceleration signals from both sensors. Based on analytical and experimental results, gravitational acceleration can be successfully eliminated by both methods, and the calculated tangential acceleration signal can effectively reflect the running status of a reciprocating compressor subject to the leakage fault.

A comparative study of gravitational acceleration cancellation from on-rotor MEMS accelerometers for condition monitoring

Conventional accelerometers installed on housing often give out less accurate diagnostic results for planetary gearbox because the mesh excitation of planet gears change with carrier movement. Recent significant advancements in low-power and low-cost Micro-Electro-Mechanical Systems (MEMS) technologies make it possible and easier to mount MEMS accelerometers directly on the rotating shaft, enabling more accurate dynamic characteristics of the rotating machine to be acquired and used for condition monitoring. In this paper, two tiny MEMS accelerometers are installed diametrically opposite each other on the low-speed input shaft of a planetary gearbox to measure the acceleration signals. The acceleration signals sensed by each MEMS will contain both the tangential acceleration and gravitational acceleration, but the latter can be removed by summing the acceleration signals from both sensors in order to characterise the rotor dynamics precisely. The experimental results show that the tangential acceleration measured on the low-speed input shaft of a planetary gearbox can clearly indicate faults, thus providing a reliable and low-cost method for planetary gearbox condition monitoring.

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Xiaoli Tang

Papers

Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review.

A Performance Evaluation of Two Bispectrum Analysis Methods Applied to Electrical Current Signals for Monitoring Induction Motor-Driven Systems

Dynamic Modeling and Structural Optimization of a Bistable Electromagnetic Vibration Energy Harvester

A comparative study of gravitational acceleration cancellation from on-rotor MEMS accelerometers for condition monitoring

Planetary gearbox fault diagnosis using an on-rotor MEMS accelerometer