# Evaluation Method for Creep Damage of P92 Steel Based on Magnetic Barkhausen Noise and Magnetoacoustic Emission

## TL;DR

This paper introduces a new non-destructive method using magnetic signals to detect creep damage in P92 steel used in power plant boilers.

## Contribution

A novel MAE-MBN composite system combined with PCA is proposed for accurate creep damage assessment in P92 steel.

## Key findings

- The MAE-MBN system with PCA effectively differentiates creep stages in P92 steel.
- Time-domain and frequency-domain features of MBN and MAE signals correlate with creep life ratios.
- PCA reduces non-monotonic feature variability, enabling clear clustering of creep damage levels.

## Abstract

The application of ultra-supercritical power plant boilers is becoming increasingly widespread. P92 steel, as a typical material used for boiler main steam pipes, plays a critical role in unit safety, making the detection of its creep damage highly significant. However, existing conventional non-destructive testing methods are difficult to effectively detect creep damage. To address this issue, a magnetoacoustic emission (MAE)–magnetic Barkhausen noise (MBN) composite measurement system is developed, which is adapted to 20 Hz and 0.3 A sine wave excitation to trigger the synchronous pickup of MBN and MAE signals of P92 steel. After collecting signals with different creep life ratios (0%~100%) under working conditions of 650 °C and 100 MPa, time-domain (absolute mean, peak value, etc.) and frequency-domain (bandwidth) features are extracted. In response to the non-monotonicity between the magnetoacoustic features and the creep damage grade, principal component analysis (PCA) is introduced to reduce dimensionality. Different creep levels of samples in the two-dimensional principal component space are presented as clear gradient clustering, achieving the accurate differentiation of creep stages. Research has shown that the MAE-MBN composite system combined with PCA can effectively characterize the creep damage of P92 steel, providing a novel non-destructive detection path for the in-service life assessment of power plant components.