Optimal Maintenance Decision for Deteriorating Components in Miter Gates Using Markov Chain Prediction Model

Reliability Engineering & System Safety

Fillmore

et al. 2021

Self Cite

Operational condition assessments, using a discrete rating system, are frequently used by field engineers to assess inland navigation assets and components. Challenges such as the occasional inability to perform inspections (such as the case with locks watered in an operational state) and protocol requirements requiring ratings even when they aren't inspected lead to highly abstracted inspection data, which are also very prone to human error and misinterpretations due to inspections protocol. On the other hand, some navigational locks are equipped with structural health monitoring (SHM) systems to continuously perform assessments from data obtained in situ . This paper aims to develop a novel hybrid damage prognosis framework for miter gate component of navigational locks, by mitigating effects of human errors on the condition assessment and integrating the highly abstracted inspection data with the SHM. It overcomes two main challenges, namely (1) there is no physical or empirical model available to model the loss-of-contact degradation in the gate, and (2) the mismatches between the inspection data and the SHM system due to data abstraction. A practical case of monitoring loss-of-contact quoin block demonstrates the efficacy of the proposed framework.

Section: Overviewmentioning

confidence: 99%

“…For a given and , the degradation of the gap is first simulated using the discrete-time model given in Eqs. ( 24) and (25). From the simulation, the…”

Section: Appendix C: Estimation Of Based On the Simulation Of Gap Growthmentioning

confidence: 99%

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

Reliability Engineering & System Safety

Fillmore

et al. 2021

Self Cite

“…Using the posterior samples from to , Eq. (31) is approximated as (33) where is the k-th realization of the gap length estimation, and is given by (34) in which…”

Section: Updating Of "B" Ratings Error Ratio Based On Online Damage Estimationmentioning

confidence: 99%

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

Reliability Engineering & System Safety

Todd

2020

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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.

“…Estimating the condition of a miter gate and its components can help to reduce the risk in unscheduled maintenance events and prioritizing better schedule maintenance events. The U.S. Army Corps of Engineers (USACE) have established a discrete rating system to allow inspectors to rate the components of a miter gate based on condition and performance [4], which are used by decision-makers for maintenance and operations planning. However, inspections based on this rating system can vary for different inspectors because it is based on engineer judgement.…”

Section: Introductionmentioning

confidence: 99%

Efficient Bayesian Inference of Miter Gates Using High-Fidelity Models

Model Validation and Uncertainty Quantification, Volume 3

Ramancha

Conte

et al. 2020

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Continuous monitoring of miter gates used in navigation locks is desirable in order to prioritize maintenance and avoid unexpected failures. Substantial economic losses to the marine cargo and associated industries are caused by the closure of these inland waterway structures. Strain gauges are often installed in many of these miter gates for data collection, and various inverse finite element techniques are used to convert the strain gauges data to damage-sensitive features. One of the damage features is the development of a contact-loss "gap" between the components (i.e. quoin blocks) that support the gate laterally, which leads to load re-distribution that can induce overload in some components of the gate. Arguably, a refined finite element model of such structure can be very computationally expensive even when using linear models. An efficient way to solve an inverse problem with time-consuming model evaluations is making use of parallel model evaluations using a Sequential Monte Carlo (SMC) algorithm and parallel solution of the finite element (FE) equations using a commercial FE software. A significant advantage of SMC algorithms is that model evaluations are independent and are able to be run in parallel. In this paper, an expensive high fidelity model of a miter gate is used to infer the gap extend given a noisy set of strain measurements.