An Efficient Implementation of the Rainflow Counting Algorithm for Life Consumption Estimation
In many reliability design and model-based health management applications where load profiles are variable and unpredictable, it is desirable to have efficient cycle counting methods to identify equivalent full and half cycles within the irregular load profile. Conventional cycle-based lifetime models can then be applied directly to provide information about the life consumption of the products. The use of an off-line rainflow algorithm is a common solution for arbitrary loads, but it cannot be applied in real time in its original form. This paper presents an in-line coding algorithm which uses a stack-based implementation, and a recursive algorithm to pick out the equivalent full and half cycles of the irregular load profile. The method can be integrated easily within time-domain or serial data applications to generate equivalent full and half cycles as they occur. Thus it is of particular significance for life estimation in real-time applications where use of the traditional implementations of the counting algorithm is impractical. In comparison with the off-line traditional rainflow method, the on-line method doesn't require any knowledge of the time history of the load profile because it processes each minimum or maximum when it occurs. Therefore, it provides a more efficient cycle counting method using less memory storage, and making more efficient use of computational resources within the real-time environment.
cycle counting rainflow algorithm real time life estimation