Robust ultrasonic damage detection under complex environmental conditions using singular value decomposition

• Singular value decomposition can be used to robustly identify damage from ultrasonic records.
• The method is robust to environmental and operational variations, eg. temperature.
• We conducted field experiments on an active pipe under complex environmental conditions.
• SVD damage detection performs well on data collected in 7 months in different operating conditions.
• The method can be implemented in an online manner for long-term monitoring.

Guided wave ultrasonics is an attractive monitoring technique for damage diagnosis in large-scale plate and pipe structures. Damage can be detected by comparing incoming records with baseline records collected on intact structure. However, during long-term monitoring, environmental and operational conditions often vary significantly and produce large changes in the ultrasonic signals, thereby challenging the baseline comparison based damage detection. Researchers developed temperature compensation methods to eliminate the effects of temperature variation, but they have limitations in practical implementations.In this paper, we develop a robust damage detection method based on singular value decomposition (SVD). We show that the orthogonality of singular vectors ensures that the effect of damage and that of environmental and operational variations are separated into different singular vectors. We report on our field ultrasonic monitoring of a 273.05 mm outer diameter pipe segment, which belongs to a hot water piping system in continuous operation. We demonstrate the efficacy of our method on experimental pitch–catch records collected during seven months. We show that our method accurately detects the presence of a mass scatterer, and is robust to the environmental and operational variations exhibited in the practical system.