PSI - Issue 57

Jeroen Van Wittenberghe et al. / Procedia Structural Integrity 57 (2024) 95–103 Author name / Structural Integrity Procedia 00 (2019) 000 – 000

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structures are exposed to varying operational and environmental conditions, the need for effective structural health monitoring (SHM) methodologies becomes increasingly important. This paper presents an SHM approach that has been developed for industrial overhead cranes. The long-term performance and integrity of these structures can be compromised by fatigue damage. Consequently, the early detection of structural deterioration and the implementation of proactive maintenance strategies are imperative to ensure their sustained operation and minimize the risk of failures. Generally speaking, SHM systems utilize measured values to asses the integrity of an asset. This assessment can be based on the measured data alone (so-called datadriven approaches) or data can be used as an input for a model or a digital twin (so-called model-driven approach) (Moallemi et. al. (2021)). In both cases, machine learning algorithms are typically used to categorize events and detect anomalies from the continuous data stream (Azimi et. al. (2020)). For large welded steel structures (e.g. overhead cranes), diverse measurement techniques are applied such as: vibration-based monitoring, acoustic emission analysis, strain gauges (Yoon et. al. (2022)), fiber-optic sensors (Sadeghi et. al. (2023)) In addition, approaches based on supervisory control and data acquisition (SCADA)as input parameters for the integrity assessment (Santos et. al. (2020)) can be applied. Overhead cranes are critical installations of a steel plant. A steel plant can easily have more than 100 cranes running over many kilometers of runway girders. Overhead cranes are subjected to a large number of cyclic loads during their operation, which can lead to fatigue cracking and other forms of damage. Their correct and safe operation is critical while lifting and handling loads. Therefore, industrial cranes are subjected to periodic inspections and maintenance. These inspections add to the maintenance cost and only give information on the condition of a crane at a certain moment. The largest and most complex cranes of a steel plant are the steelmaking cranes, such as the casting crane shown in Fig. 1. These cranes have a typical capacity of 400 tons.

Fig. 1: Example of a large capacity casting crane at ArcelorMittal steel plant.

Nomenclature FBG

fibre bragg grating

RBF radial basis function SCADA supervisory control and data acquisition SHM structural health monitoring

2. Background To explore the possibilities of SHM for crane infrastructure, ArcelorMittal participated in the SafeLife projectwhere a feasibility study was carried out on a crane runway girder. In addition, a railway bridge and an offshore windmill