Published September 1, 2019 | Version v1
Journal article

Power-efficient piezoelectric fatigue measurement using long-range wireless sensor networks

  • 1. Department of Engineering, University of Cambridge, Cambridge CB2 1PZ (United Kingdom)
  • 2. Department of Civil and Environmental Engineering, University of California at Berkeley, Berkeley, CA (United States)

Description

In this paper we describe the design of a proof-of-concept wireless embedded sensor system for continuous strain cycle monitoring as a method for fatigue life assessment on civil structures. Monitoring of strain cycles is energy demanding, and therefore not suited to energy-constrained devices, as it requires continuous acquisition of strain data with a high sampling rate, followed by data processing using algorithms for peak-trough detection and cycle counting. To overcome this drawback, at the core of our proposed design is a piezoelectric-based analogue sensor system that can achieve as much as a factor of 9 increase in energy efficiency compared with the conventional approach. The key component is an analogue peak-trough detector that offloads the computation in peak-trough detection from the microcontroller, thus eliminating the need for continuous sampling. The function of the detector is coupled with an energy-efficient interrupt-driven software design for acquisition and strain cycles calculation, which is carried out by using a standard form of the rainflow cycle counting algorithm. For wireless communication and networking, LoRa and LoRaWAN are adopted as core modules. We illustrate the performance of our proposed solution by way of simulation and laboratory experiments. Results show a good agreement in measurement of strain cycles between our proposed system and the conventional approach. Thus, our solution proves to be promising for real fatigue measurement applications. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1361-665X/ab2c46

Additional details

Identifiers

Publishing Information

Journal Title
Smart Materials and Structures (Print)
Journal Volume
28
Journal Issue
9
Journal Page Range
[17 p.]
ISSN
0964-1726

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
53025189
Subject category
S36: MATERIALS SCIENCE;
Descriptors DEI
ALGORITHMS; CALCULATION METHODS; DATA PROCESSING; ENERGY DEMAND; ENERGY EFFICIENCY; FATIGUE; PIEZOELECTRICITY; SENSORS; SIMULATION; STRAINS
Descriptors DEC
DEMAND; EFFICIENCY; ELECTRICITY; MATHEMATICAL LOGIC; MECHANICAL PROPERTIES; PROCESSING