Optimal maintenance decisions for deteriorating quoin blocks in miter gates subject to uncertainty in the condition rating protocol

Abstract

Condition assessments and rating systems are frequently used by field engineers to assess inland navigation assets and components. The goal of these assessments is to initiate effective risk-informed budget plans for maintenance and repair/replace. Ideally, a degradation model of every component failure mode in the gate would facilitate maintenance decision-making. However, sometimes there is no clear physical understanding how a damage progresses in time; for example, it isn't clear how the bearing gaps change in time in the quoin blocks of a miter gate. Therefore, this is one motivation for the framework proposed in this paper, which integrates Structural Health Monitoring with a Markov transition matrix built from historical condition assessment.To show the applicability of this framework, two examples are presented of how to find the optimal time to plan for maintenance of components in miter gates i) static maintenance planning based on operational condition assessment (OCA) ratings only and ii) dynamic maintenance planning based on integration of damage diagnostics based on monitoring data and failure prognosis based on OCA ratings. In addition, this paper presents a new Bayesian approach to estimate the ratio of errors in the OCA ratings, which allows for improved accuracy in OCA rating-based prognosis.

A Novel Framework for Integration of Abstracted Inspection Data and Structural Health Monitoring for Damage Prognosis of Miter Gates

“…The degradation model obtained in Sec. 3.3 can then be used for failure diagnostics and prognostics using the approach presented in Vega et al [16], using the following state and measurement equations…”

“…The equations above can then be solved recursively in a timely manner as been discussed in Vega et al [16]. Based on the failure diagnostics and prognostics of the gap growth, the remaining useful life of a miter gate can be estimated at every time step t k as … COMMENT 4: Please go back over the equations, some parameters are not defined for example f(t) in equation (35).…”

An alternative quantification of the value of information in structural health monitoring

“…Since the relationship between the gap-length and the strain data is highly non-linear and complex, we numerically infer the posterior distribution by using particle filters (see [21,31,16]). Evaluation of the likelihood |Θ ( | ) at numerous values of at different time periods using the full finite element model is exorbitantly expensive.…”

“…This goal is achieved by a modern paradigm involving periodically-spaced or continuous data acquisition, extraction of relevant features to establish the damage detection or classification hypothesis, and evaluating the hypothesis under all the sources of uncertainty and variability that inevitably corrupt the monitoring and inference process. SHM is integrated with predictive degradation/failure and demand/loads models ("prognosis") into a decision-making framework for optimal life cycle management of the structure [2]. However, the benefits related to improved decision-making that an SHM system is expected to bring to life cycle management are balanced by the costs that it incurs.…”

“…We consider the inland waterway navigation infrastructure as an application case. The locks and dams that comprise the inland waterway navigation infrastructure consist of multi-hundreds of billions of dollars of capital investment in a major economic transportation corridor [14,15,16]. The United States Army Corps of Engineers (USACE) spends further billions of dollars in maintaining and operating this infrastructure, where the unscheduled shutdown of these assets and dewatering for inspection or repair is very costly [17,18,19].…”