一种用于部分测量系统联合输入-状态-参数估计的无迹通用滤波器：应用于车载式结构健康监测
An unscented universal filter for joint input-state-parameter estimation of a partially measured system: an application to drive-by structural health monitoring
- University of New South Wales（新南威尔士大学）
- Kyoto University（京都大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
提出无迹通用滤波器（UUF），用于非线性系统联合输入-状态-参数估计，应用于车载式桥梁健康监测，在多种场景下误差最低。
AI中文摘要：
车载式结构健康监测通过测量车辆响应来推断桥梁状况，但车辆测量值主要受路面粗糙度和车辆动力学影响。桥梁响应、接触力和桥梁参数通过车辆-桥梁相互作用（VBI）相互关联，因此联合估计这些量是可取的。本文提出了一种通用滤波器族中的新型滤波器——无迹通用滤波器（UUF），用于具有未知输入的非线性系统的联合输入-状态-参数估计。未知输入通过加权最小二乘法从新息中估计，无需演化模型或统计信息，且系统反演对前馈矩阵不施加秩条件。非线性传播通过缩放无迹变换进行线性化，线性化残差被传播到误差协方差中。对于仅加速度配置，辅助积分器从加速度测量本身形成伪测量。UUF应用于耦合的VBI系统，以接触力为未知输入，桥梁局部刚度为跟踪参数，利用车身响应和至多几个桥梁响应。在简支梁和日本钢桁架桥Old Ada Bridge的数值案例研究中，UUF与经典和最新的联合估计滤波器进行了比较，所有滤波器均采用相同的实用策略调参。在所考察的损伤严重程度、位置、路面等级和噪声水平下，UUF在大多数场景中产生最低的总误差，且其误差随损伤严重程度、位置和路面等级变化很小。在Old Ada Bridge上，它仅通过加速度测量识别了损伤构件的刚度，无需车辆悬架参数，且前馈矩阵秩亏。
英文摘要：
Drive-by structural health monitoring infers the condition of a bridge from the response of an instrumented vehicle, whose measurements are dominated by the road roughness and the vehicle dynamics. The bridge responses, contact forces and bridge parameters depend on one another through the vehicle-bridge interaction (VBI), so estimating them jointly is desirable. This paper proposes a novel filter in the Universal Filter family, the Unscented Universal Filter (UUF), for joint input-state-parameter estimation of nonlinear systems with unknown inputs. The unknown input is estimated by weighted least squares from the innovation, without any evolution model or statistics, and the system inversion imposes no rank condition on the feedforward matrix. The nonlinear propagation is linearised by the scaled unscented transform, and the linearisation residuals are propagated into the error covariances. For the acceleration-only configuration, auxiliary integrators form pseudo-measurements from the acceleration measurements themselves. The UUF is applied to the coupled VBI system, with the contact forces as the unknown input and the local stiffness of the bridge as the tracked parameter, from the responses of the vehicle body and at most a few bridge responses. In numerical case studies on a simply supported beam and the Old Ada Bridge, a steel truss bridge in Japan, the UUF is compared with classical and state-of-the-art joint estimation filters, all tuned by the same practical strategy. Across the damage severities, locations, road classes and noise levels examined, the UUF yields the lowest total error in most scenarios, and its error varies little with damage severity, location and road class. On the Old Ada Bridge, it identifies the stiffness of a damaged member from acceleration-only measurements, without the suspension parameters of the vehicle, and with a rank-deficient feedforward matrix.
