A rotating machine acoustic emission monitoring system powered by multi-source energy harvester

This working paper introduces a multi-source energy harvesting powered acoustic emissions (AE) monitoring system for the applications of rotating machine fault detections. This wireless sensor prototype records the AE signal at approximately 200KHz frequency. It performs fast Fourier transform (FFT) and compares the results with known fault patterns. An energy harvesting solution utilizes vibrational, thermal and light energy as the power supply for the AE wireless sensor node. The multiple-source energy harvester proposed in this work generates 1.56mW from 25--48mg vibration energy and 3.37mW from thermoelectric energy when deployed on the 62°C metal surface of air compressor. This AE wireless sensor prototype combines with the batteryless energy harvesting power supply in order to provide a self-powered health monitoring solution for wide range of rotating machinery

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

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

Advanced Fault Diagnosis and Health Monitoring Techniques for Complex Engineering Systems

Over the last few decades, the field of fault diagnostics and structural health management has been experiencing rapid developments. The reliability, availability, and safety of engineering systems can be significantly improved by implementing multifaceted strategies of in situ diagnostics and prognostics. With the development of intelligence algorithms, smart sensors, and advanced data collection and modeling techniques, this challenging research area has been receiving ever-increasing attention in both fundamental research and engineering applications. This has been strongly supported by the extensive applications ranging from aerospace, automotive, transport, manufacturing, and processing industries to defense and infrastructure industries

2012 PWST Workshop Summary

No abstract availabl

Data reduction strategies.

Based on the variety of methods available for gathering data for the aircraft health status, the challenge is to reduce the overall amount of data in a trackable and safe manner to ensure that the remaining data are characteristic of the current aircraft status. This chapter will cover available data reduction strategies for this task and discuss the data intensity of the SHM methods of Chaps. 5 to 8 and established approaches to deal with the acquired data. This includes aspects of algorithms and legal issues arising in this context

Advanced Materials and Technologies in Nanogenerators

This reprint discusses the various applications, new materials, and evolution in the field of nanogenerators. This lays the foundation for the popularization of their broad applications in energy science, environmental protection, wearable electronics, self-powered sensors, medical science, robotics, and artificial intelligence

IMPACT-BASED PIEZOELECTRIC ENERGY HARVESTING SYSTEM EXCITED FROM DIESEL ENGINE SUSPENSION

Vibration energy harvesting systems are using real ambient sources of vibration excitation. In our paper, we study the dynamical voltage response of the piezoelectric vibrational energy harvesting system (PVEHs) with a mechanical resonator possessing an amplitude limiter. The PVEHs consist of the cantilever beam with a piezoelectric patch. The proposed system was subjected to the inertial excitation from the engine suspension. Impacts of the beam resonator are useful to increase of system’s frequency transition band. The suitable simulations of the resonator and piezoelectric transducer are performed by using measured signal from the engine suspension. Voltage outputs of linear (without amplitude limiter) and nonlinear harvesters were compared indicating better efficiency of the nonlinear design