Embedded real-time and in-situ fatigue life monitoring sensor with load types identification

Abstract

Structural fatigue failure has always been a widely concerned research in mechanical equipment. It requires more and more real-time monitoring of structural damage before cracks appear for the intelligent development of modern equipment. Based on embedded technology, a real-time fatigue in-situ fatigue life monitoring sensor (FLMS) is proposed, which has the function of load spectrum identification and linear cumulative damage calculation. The sensor can realize wireless communication through LoRa integration module. After experimental verification, the number of remaining cycles, residual damage and remaining time life can be calculated quickly for different types of loads. The fatigue life prediction error for cycle load is basically within 22%. The maximum and minimum calculation error under random load of the FLMS are 2.27 times and 1.01 times, respectively. And they can be displayed in real time and stored regularly. The integrated sensor can realize the real-time fatigue life prediction of the structure and promote the intelligent development of fatigue life monitoring of the equipment. • This paper proposes a real-time monitoring method for identification of load types based on embedded processor. • The real-time fatigue life monitoring of the FLMS is realized through algorithm integration. • The life error for cycle load is basically within 22%, and it is kept at 2.3 times for random load.