The interesting to assess the condition of a structure with structural health monitoring data has gained many attentions. Most of the existing methods require the measurement at the force location. This paper presents a novel output-only condition assessment method that does not require measurement at the force location. The unknown structural damage indices and input force can be identified with the stochastic gradient descent method. The dynamic acceleration response sensitivities with respect to the unknown structural damage indices and input force are derived analytically. Both unknown damage indices and unknown input force can be identified by minimizing the discrepancy between the measured and calculated vibration data. Numerical studies on a two-dimensional truss and seven-floor frame and experimental studies on a steel frame structure are presented to verify the accuracy and efficiency of the proposed method. Results demonstrate that the damage severity, location, and unknown input force can be identified. Also, the measurement at the force location is not required. Furthermore, when 20% measurement noise is considered, the identified error is less than 5%.

中文翻译：

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基于随机梯度下降法的土木结构仅输出结构状态评估方法

利用结构健康监测数据评估结构状况的有趣问题引起了广泛关注。大多数现有方法都需要在受力位置进行测量。本文提出了一种新颖的仅输出条件评估方法，不需要在力位置进行测量。未知的结构损伤指数和输入力可以用随机梯度下降法识别。对未知结构损伤指数和输入力的动态加速度响应敏感性是分析得出的。通过最小化测量和计算的振动数据之间的差异，可以识别未知的损坏指数和未知的输入力。通过对二维桁架和七层框架的数值研究以及对钢框架结构的试验研究，验证了所提方法的准确性和效率。结果表明，可以识别损坏严重程度、位置和未知输入力。此外，不需要在受力位置进行测量。此外，当考虑 20% 的测量噪声时，识别误差小于 5%。