By analyzing acceleration responses, researchers have devised an innovative way to detect structural damage in bridges, which is a big step forward in structural health monitoring. This mechanism extrapolates trendlines for acceleration data using quadratic regression and is, therefore, much better than techniques based on filters such as moving average, Savitzky–Golay, and so forth.

Varying truckload velocities tested the method in studying a 25-meter bridge with simple support simulated in ABAQUS. Cracks were introduced at the bottom of the bridge to simulate structural damage. This showed that the new method was able to correctly determine damages without monitoring dynamic modal parameters or needing it in noisy environments. Whatever the scenario, the method placed damage accurately in all cases when truck velocities were up to 4 m/s; the accuracy decreased to eight m/s.

This approach has several benefits: it’s online, it operates quickly, and it doesn’t require any baselines, making it suitable for continuous monitoring of building structures. The method is a more efficient way to detect damage on bridges, which results in greater safety during their use and reduced maintenance work while offering a means of managing them better in the future. The research points out that increased security for people’s lives and better use of resources are possible due to such an approach.