Large-area strain-monitoring is highly desired in various engineering applications. Despite the fact that the commercial strain gauges have been successfully used for strain measurement, there is still big challenge f...
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Large-area strain-monitoring is highly desired in various engineering applications. Despite the fact that the commercial strain gauges have been successfully used for strain measurement, there is still big challenge for this manually-pasting based solution especially for large-area monitoring. First, the wires of multiple commercial strain gauges for large-area monitoring will exhibit remarkably abundant and complex, and eventually reduce the reliability and convenience of the measurement system. Second, the commercial terminal instrument is usually function-redundant with complicated electronic configuration to match the low-sensitive metal-foil strain gauge. Meanwhile, the wire-based signal acquisition and processing system substantially limit the compatibility for moving objects. Here we take the advantages of direct-ink-writing (DIW) 3D printed sensorarray, thereby propose a wireless-based solution for large-area strain field measurement, data transmission and processing. The sensitivity of the printed sensing unit is one order of magnitude higher than that of traditional strain gauges, while the sensorarray layout is optimized for compatibility to the strain orientation and detecting domain. A high-frequency signal acquisitor is designed and assembled with a wireless transmitter for rapid multi-point strain detection and real-time data transmission. A remote data receiver and processing terminal are developed and integrated for twin-visualization of the detected strain field. In particular, the detected strain data are processed to construct a cascaded support-vector-machine (SVM) classifier, that successfully identify motion states of moving vehicles in high precision. This study provides insight into exploring the advantages of DIW printed sensorarrays combined with specifically-designed wireless system and strain-based dynamic recognition.
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