The effective application of vibration-based damage detection (VBDD) methods as a structural health monitoring approach depends largely on the accurate measurement of modal properties, particularly the mode shapes. However, the modal properties of bridges and other civil engineering structures are commonly measured using an output-only approach and ambient excitation sources, which can lead to considerable variability in the measurements and therefore a lack of confidence in the reliability of the VBDD results. This paper proposes two data quality indicators that can be used to assess the quality of a calculated VBDD parameter in terms of its potential to confidently identify and characterize damage, based on the consistency of the parameter when obtained from different sets of vibration test data. The performance of the indicators is demonstrated by application to a simple-span slab-on-girder bridge deck and comparison to the probabilities of successfully locating nine damage cases, as calculated using transient dynamic finite element analyses under simulated randomly varying loads. The data quality indicators were found to correlate well with the probability of successful localization, and were able to reflect the varying probabilities associated with several factors, including the number of repeated random trials used to estimate the mode shapes, the distance from the damage to the nearest sensor, the proximity of the damage to simple supports, and the severity of the damage. The proposed parameters were therefore shown to be capable of determining whether the available data are of sufficient quality to confidently apply VBDD methods.

基于振动的损伤检测（VBDD）方法作为结构健康监测方法的有效应用很大程度上取决于对模态特性（尤其是模态形状）的准确测量。但是，桥梁和其他土木工程结构的模态特性通常使用仅输出的方法和环境激励源进行测量，这可能导致测量结果存在较大差异，因此对VBDD结果的可靠性缺乏信心。本文提出了两个数据质量指标，根据从不同组的振动测试数据中获得的参数的一致性，就可以可靠地识别和表征损坏的可能性而言，可以用来评估计算出的VBDD参数的质量。指标的性能通过将其应用到简单跨度大梁板桥面板上，并与通过模拟随机变化载荷下的瞬态动态有限元分析计算出的成功定位9个破坏案例的概率进行比较。发现数据质量指标与成功定位的可能性密切相关，并且能够反映与几个因素相关的变化概率，包括用于估计模式形状的重复随机试验的次数，从损伤到损伤的距离。最近的传感器，损坏到简单支撑的距离以及损坏的严重程度。因此，建议的参数显示出能够确定可用数据是否具有足够的质量来自信地应用VBDD方法的能力。