MATLAB Implementation of Rainflow Counting Method for Fatigue Analysis

The rainflow counting method is a widely used algorithm in fatigue analysis, primarily employed to process load time-history data and convert it into cycles suitable for fatigue damage calculation. The following outlines the core approach for implementing the rainflow counting method in MATLAB:

Data Preprocessing Raw load spectra first require necessary preprocessing, such as noise removal, smoothing, or peak extraction. Ensure data points accurately reflect load variation trends using MATLAB functions like `smoothdata` or `findpeaks` for efficient signal processing.

Rainflow Counting Core Steps The core logic of the rainflow method involves identifying complete cycles in load sequences and recording each cycle's amplitude and mean value. Implementation typically includes: Identifying local peaks and valleys in the load sequence using `islocalmax` and `islocalmin` functions. Extracting closed stress-strain hysteresis loops (i.e., complete cycles) according to specific rules through iterative comparison algorithms. Recording each cycle's range (amplitude) and mean value using array operations for efficient data storage.

Fatigue Damage Calculation Based on cycle data extracted from rainflow counting, calculate each cycle's contribution to total fatigue damage using material S-N curves (stress-life curves). Implement Miner's linear cumulative damage rule through vectorized calculations with `cumsum` for optimal performance.

MATLAB Implementation Optimization Leverage MATLAB's vectorized operations to enhance computational efficiency, replacing loop structures with matrix operations. Encapsulate the algorithm into reusable functions using `function` definitions with proper input/output parameters.

Results Output Final output should include statistical tables of cycle amplitudes and means, plus cumulative damage results. For visualization, generate load cycle distribution histograms using `histogram` or Rainflow matrix plots with `imagesc` for intuitive analysis.

This method applies to fatigue life prediction in mechanical, aerospace, and civil engineering fields, effectively addressing fatigue analysis under random loading conditions through programmable cycle counting techniques.