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At least 55 records · Page 3

Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

Digitally enhanced services for wind power could reduce Operations and Maintenance costs as well as the Levelised Cost Of Energy. Therefore, there is a continuous need for advanced monitoring techniques which can exploit the opportunities of Internet of Things and Big Data Analytics. The heart of wind turbines is an epicyclic gearbox and rolling element bearings are often responsible for machinery stops. The vibration signatures of bearings are rather weak compared to other components. As a result a number of signal processing techniques have been proposed, focusing towards accurate and early fault detection with limited false alarms and missed detections. In Envelope Analysis an envelope of the vibration signal is estimated usually after filtering around a frequency band. Different tools, such as Kurtogram, have been proposed to select the optimum filter parameters. Monitoring techniques have reached a mature level for steady speed and load operating conditions. On the other hand, under chaniging operating conditions, it is still unclear whether the change of the monitoring indicators is due to the change of the machinery's health or due to the change of operating parameters. Recently, the authors have proposed a new tool called IESFOgram, based on Cyclic Spectral Coherence for the automatic selection of the filtering band. In this paper, the performance of the tool is evaluated on the National Renewable Energy Laboratory wind turbine gearbox vibration condition monitoring benchmarking data set which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.

17 WIND ENERGY↗

NREL’s Wind Turbine Drivetrain Condition Monitoring and Wind Plant Operation and Maintenance Research During the 2010s: A US Land-Based Perspective

The wind industry has seen tremendous growth during the past two decades, with the global cumulative installation capacity reaching more than 650 gigawatts by the end of 2019. Despite performance and reliability improvements of utility-scale wind turbines over the years, the industry still experiences premature component failures, leading to increased operation and maintenance (O&M) costs. Among various turbine components, gearboxes—and, more broadly, drivetrains—have shown to be costly to maintain throughout the design life of a wind turbine. The problem of premature component failure is industry wide. As early as 2007, the US Department of Energy (DOE) started to address this challenge through the National Renewable Energy Laboratory’s (NREL’s) reliability initiative that first focused on gearboxes and more recently expanded to entire drivetrains. The wind turbine drivetrain condition monitoring and wind plant O&M research that is the subject of this paper is part of the NREL initiative and includes a few research and development (R&D) activities conducted during the 2010s. These activities included technology evaluation during the first few years; novel monitoring technique investigation (specifically, compact filter analysis) during the middle years; and data and physics domain modeling for fault detection and prediction in recent years. A high-level summary of these activities is provided in this paper along with some key observations from each activity. Most of the work discussed has been published and can be referred to for more information. They reflect the expected evolution of wind turbine condition monitoring and O&M in the US market—primarily, a land-based perspective. In addition, we have identified several R&D opportunities that can be picked up by the research community to help industry advance in related areas, making wind power more cost competitive in the future.

17 WIND ENERGY↗

Condition monitoring requirements for the development of a space nuclear propulsion module

To facilitate the development of a space nuclear propulsion module for manned flights to Mars, requirements must be established early in the technology cycle. The long lead times for the acquisition of the engine system and nuclear test facilities demands that the engine system, size, performance, safety goals and condition monitoring philosophy be defined at the earliest possible time. These systems are highly complex and require a large multi-disciplinary systems engineering team to develop and track the requirements and to ensure that the as-built system reflects the intent of the mission. An effective methodology has been devised coupled with sophisticated computer tools to effectivly develop and interpret the functional requirements. These requirements can then be decomposed down to the specification level for implementation. This paper discusses the application of the methodology and the analyses to develop condition monitoring requirements under a contract with the National Aeronautics and Space Administration (NASA) Lewis Research Center (LeRC) Nuclear Propulsion Office (NPO).

Wagner, Robert C.↗

A Data Filter for Identifying Steady-State Operating Points in Engine Flight Data for Condition Monitoring Applications

This paper presents an algorithm that automatically identifies and extracts steady-state engine operating points from engine flight data. It calculates the mean and standard deviation of select parameters contained in the incoming flight data stream. If the standard deviation of the data falls below defined constraints, the engine is assumed to be at a steady-state operating point, and the mean measurement data at that point are archived for subsequent condition monitoring purposes. The fundamental design of the steady-state data filter is completely generic and applicable for any dynamic system. Additional domain-specific logic constraints are applied to reduce data outliers and variance within the collected steady-state data. The filter is designed for on-line real-time processing of streaming data as opposed to post-processing of the data in batch mode. Results of applying the steady-state data filter to recorded helicopter engine flight data are shown, demonstrating its utility for engine condition monitoring applications.

Simon, Donald L.↗

Condition monitoring and false alarm reducing of sensors in NPP - 222

With more and more application of digital I and C systems in nuclear power plants (NPP), more and more sensors are also required. Large amount of sensors really can make contribution to the condition monitoring of systems and equipment in NPP, whereas the heavy use also increases the malfunction risk of sensor self. Therefore the reliability and effectiveness of sensors must be guaranteed first. Thus the condition of sensors should be monitored first in a NPP. Since the precise mathematical models of sensors in complex systems are relative difficult to establish, however quantity of operating data can be easily obtained due to the wide application of digital I and C systems, thus this article adopts principal component analysis (PCA) to carry out condition monitoring for sensors. The PCA model developed for sensors is proved to be effective with operating data acquired from a real NPP. It can detect and isolate the fault when an artificial fault is imposed to the normal data. Then the monitoring results are further processed by another control limit (second confidence limit) besides T 2 and Q statistics (first confidence limit) in PCA. The value of second confidence limit is calculated based on the probability statistics of T 2 and Q statistics. And simulation tests show that the application of the second confidence limit can greatly reduce false alarms in the PCA model and the model performance can be greatly improved with the application of false alarms reducing method. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Exploring the Feasibility of Modern Fiber Optics in Offshore Mooring Condition Monitoring

This project explored the feasibility of using fiber-optic sensing technologies for condition monitoring of offshore synthetic mooring lines used in marine renewable energy systems. The work focused on evaluating optical fiber materials, interrogation methods, and rope-embedment approaches capable of enabling distributed strain or elongation measurements along mooring lines.

16 TIDAL AND WAVE POWER↗

Liquid Core Detection and Strand Condition Monitoring in a Continuous Caster Using Optical Fiber

Real-time monitoring of the liquid core position during the continuous casting of steel has been demonstrated using low-cost distributed optical-fiber-based strain sensors. These sensors were installed on the containment roll support structures in the segments of a production continuous caster to detect the position of the solid–liquid interface and monitor the strand condition during the continuous casting. Distributed Fiber Bragg Grating sensors (FBGs) were used in this work to monitor strain at six roll positions in the caster. The sensor performance was first validated by comparing optical strain measurements with conventional strain gauge measurements in the lab. Next, optical strain measurements were performed on an isolated caster segment in a segment maintenance facility using hydraulic jacks to simulate the presence of a liquid core under the roll. Finally, the sensors were evaluated during caster operation. The sensors successfully detected the load increase associated with the presence of a liquid core under each instrumented roll location. Incidents of bulging and roll eccentricity were also detected using frequency analysis of the optical strain signal. The liquid core position measurements were compared using predictions from computer models (digital twins) in use at the production site. The measurements were in good agreement with the model predictions, with a few exceptions. Under certain transient caster operating conditions, such as spraying practice changes and SEN exchanges, the model predictions deviated slightly from the liquid core position determined from strain measurements.

47 OTHER INSTRUMENTATION↗

Modeling of Vertical Motor-driven Pump for Simulation of a Fault Signature \\ for Condition Monitoring

As part of the ongoing effort to transition from preventive maintenance strategies to condition-based maintenance strategies in nuclear power plants, there is significant reliance on using machine learning techniques. To develop a robust machine learning model that can diagnose all the fault modes of a vertical motor-driven pump, data capturing the unique signature of each fault mode is required. In practice, it is difficult to collect or capture data that captures all the fault modes from a single plant site. So to address this situation, a computational model of a vertical motor-driven pump is developed using the multipurpose finite element software COMSOL Multiphysics. The developed model is used to generate simulated data under normal operation and is compared with the vibration data collected using vibration sensors. Once the simulation model is verified under normal operating condition, simulated data for the fault mode for which minimal or no evidence is available in historical plant process data is developed. This simulated data is used to develop fault signatures to achieve robust predictive models. This paper presents modeling details and verification of the model that can used to generate data for fault modes that are not available at a plant site for condition monitoring purpose.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Modeling of Vertical Motor-driven Pump for Simulation of a Fault Signature \\ for Condition Monitoring

As part of the ongoing effort to transition from preventive maintenance strategies to condition-based maintenance strategies in nuclear power plants, there is significant reliance on using machine learning techniques. To develop a robust machine learning model that can diagnose all the fault modes of a vertical motor-driven pump, data capturing the unique signature of each fault mode is required. In practice, it is difficult to collect or capture data that captures all the fault modes from a single plant site. So to address this situation, a computational model of a vertical motor-driven pump is developed using the multipurpose finite element software COMSOL Multiphysics. The developed model is used to generate simulated data under normal operation and is compared with the vibration data collected using vibration sensors. Once the simulation model is verified under normal operating condition, simulated data for the fault mode for which minimal or no evidence is available in historical plant process data is developed. This simulated data is used to develop fault signatures to achieve robust predictive models. This paper presents modeling details and verification of the model that can used to generate data for fault modes that are not available at a plant site for condition monitoring purpose.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Integrated Boiler Management through Advanced Condition Monitoring and Component Assessment

The objective of this project, supported by the U.S. Department of Energy (USDOE) under DEFE0031683, is to develop, demonstrate, and support technology transfer of an integrated boiler management system inclusive of distributed sensing and near real-time damage assessment tools to provide for the first highly accurate condition monitoring system for boiler components.

01 COAL, LIGNITE, AND PEAT↗

Condition monitoring of wind turbine drivetrains: state-of-the-art technologies, recent trends, and future outlook

As global wind capacity expands, reducing operations and maintenance costs is critical to lowering the levelized cost of energy. This paper explores the state of the art in condition monitoring and prognostic strategies for wind turbine drivetrains, which are among the most failure-prone and maintenance-intensive subsystems. Current diagnostic methodologies are evaluated, covering supervisory control and data acquisition (SCADA) data, high-frequency vibration and acoustic analysis, machine learning and digital twin frameworks. Finally, practical challenges are identified that limit wide-scale industrial adoption, in order to guide future research and industrial efforts.

17 WIND ENERGY↗

Reusable rocket engine turbopump condition monitoring

Significant improvements in engine readiness with reductions in maintenance costs and turn-around times can be achieved with an engine condition monitoring systems (CMS). The CMS provides health status of critical engine components, without disassembly, through monitoring with advanced sensors. Engine failure reports over 35 years were categorized into 20 different modes of failure. Rotor bearings and turbine blades were determined to be the most critical in limiting turbopump life. Measurement technologies were matched to each of the failure modes identified. Three were selected to monitor the rotor bearings and turbine blades: the isotope wear detector and fiberoptic deflectometer (bearings), and the fiberoptic pyrometer (blades). Signal processing algorithms were evaluated for their ability to provide useful health data to maintenance personnel. Design modifications to the Space Shuttle Main Engine (SSME) high pressure turbopumps were developed to incorporate the sensors. Laboratory test fixtures have been designed for monitoring the rotor bearings and turbine blades in simulated turbopump operating conditions.

Hampson, M. E.↗

Digital Twin Based Condition Monitoring of LCC-LCC Inductive Power Transfer Systems

Inductive power transfer (IPT) systems provide a flexible, hands-free charging opportunity to electric vehicles (EV). The resonant network components and the transmitter and receiver coils are often subjected to high voltages or currents. Component aging in the compensation network and coils of resonant IPT systems is detrimental to the reliability and power transfer efficiency of the IPT system. Monitoring the component health of such multi-element complex systems requires robust optimization algorithms. This paper discusses condition monitoring of a resonant IPT system for an EV charger using a digital twin model. A hybrid estimation algorithm based on genetic algorithms and adaptive particle swarm optimization is developed to estimate the parameters of the digital twin model. Simulation results are used to verify the monitoring capabilities of the developed algorithm under various operating conditions of the IPT system.

Weldehawaryat, Lidya Mussie [graduate research ass↗

Rocket plume spectrometry: A system permitting engine condition monitoring, as applied to the technology test bed engine

The appearance of visible objects in the exhaust plume of space shuttle main engines (SSME) during test firings is discussed. A program was undertaken to attempt to identify anomalous material resulting from wear, normal or excessive, of internal parts, allowing time monitoring of engine condition or detection of failure precursors. Measurements were taken during test firings at Stennis Space Center and at the Santa Suzanna facility in California. The results indicated that a system having high spectral resolution, a fast time response, and a wide spectral range was required to meet all requirements, thus two special systems have been designed and built. One is the Optical Plume Anomaly Detector (OPAD). The other instrument, which is described in this report, is the superspectrometer, an optical multichannel analyzer having 8,192 channels covering the spectral band 250 to 1,000 nm.

Powers, W. T.↗

Real-time Condition Monitoring of Power Modules in Grid-tied Power Converter

This paper proposes and demonstrates a real-time condition monitoring method using gate driver integrated sensing circuits and sensor fusion algorithms. Power device on-state voltage (VDSon) measurement and junction temperature (Tj) sensing circuits with high noise immunity are built and integrated into an adaptive gate driver circuit for power modules. Considering the inherently noisy measurement environment of power converters, VDSon together with several other measurements are fused together to provide accurate descriptions of the stress and degradation of each power device. Furthermore, the gate driver circuit can actively control the turn-on gate voltage (VGSon) for each device based on the stress and degradation state. The proposed sensing circuits and power device condition assessment algorithms are implemented in a 75 KVA grid-tied power converter. This paper focuses on the sensing circuits hardware designs and testing in grid-tied power converter prototype and device stress index generation. More comprehensive results on the device state of health index generation will be presented in future work.

Fan, Junchong↗

Application of Cable Condition Monitoring Technologies to Assess Age-Related Degradation of Industrial Cables Installed in Harsh Environments

The aging of electrical cables has been the subject of substantial research and development (R&D) projects performed by national and international laboratories, universities, and private organizations for many years. This R&D was conducted to develop guidance, equipment, and techniques to support aging management of in-service cables in industrial facilities such as nuclear power plants, research reactors, waste facilities, and fuel fabrication plants. Through these research efforts, condition monitoring technologies have been developed that can determine the severity of age-related degradation that occurs in industrial cables and insulation polymers during service. This paper summarizes the results of aging assessments that were performed for cables installed in two U.S. nuclear power plants, one a pressurized water reactor and one a boiling water reactor. These cables had been in service for over 40 years and during plant operation were exposed to harsh environmental conditions including elevated temperatures and radiation. For these assessments, a comprehensive series of measurements was performed to assess the aged condition of the cables. These cables came from different manufacturers, were manufactured in different years, and were constructed with a variety of jacket and insulation polymers including chloro-sulfonated polyethylene (CSPE), cross-linked polyethylene (XLPE)/cross-linked polyolefin (XLPO), neoprene, and ethylene propylene rubber (EPR). The goal of these assessments was to determine the current aged condition of the cable polymers and provide an estimate of how long the cable insulation materials could remain exposed to their in-service environmental conditions before reaching their end-of-life condition. Both nuclear power plants have received license renewals to extend their operation from 40 to 60 years, and the utilities need objective evidence to show that critical components such as cables will be able to function safely and reliably during the extended operating period. Furthermore, the results of these assessments showed that the cables exhibited different aged conditions depending on the type of polymers they were constructed with and the environment they were exposed to during service. Some of the cables and insulation polymers showed signs of significant age-related degradation and were estimated to have approximately 5 years of remaining service life. Other cables exhibited no signs of significant age-related degradation and were estimated to have 50 years or more of remaining service life. Using the results of these cable aging assessments, plant personnel were able to (1) determine the overall aged condition of cables and insulation polymers using objective test results, (2) identify aged or degraded cables before they caused operability issues, and (3) avoid unnecessary and costly replacement of cables that can continue to operate safely and reliably.

36 MATERIALS SCIENCE↗