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"Performance monitoring"
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A Study of Wind Turbine Performance Decline with Age through Operation Data Analysis
Ageing of technical systems and machines is a matter of fact. It therefore does not come as a surprise that an energy conversion system such as a wind turbine, which in particular operates under non-stationary conditions, is subjected to performance decline with age. The present study presents an analysis of the performance deterioration with age of a Vestas V52 wind turbine, installed in 2005 at the Dundalk Institute of Technology campus in Ireland. The wind turbine has operated from October 2005 to October 2018 with its original gearbox, that has subsequently been replaced in 2019. Therefore, a key point of the present study is that operation data spanning over thirteen years have been analysed for estimating how the performance degrades in time. To this end, one of the most innovative approaches for wind turbine performance control and monitoring has been employed: a multivariate Support Vector Regression with Gaussian Kernel, whose target is the power output of the wind turbine. Once the model has been trained with a reference data set, the performance degradation is assessed by studying how the residuals between model estimates and measurements evolve. Furthermore, a power curve analysis through the binning method has been performed to estimate the Annual Energy Production variations and suggests that the most convenient strategy for the test case wind turbine (running the gearbox until its end of life) has indeed been adopted. Summarizing, the main results of the present study are as follows: over a ten-year period, the performance of the wind turbine has declined of the order of 5%; the performance deterioration seems to be nonlinear as years pass by; after the gearbox replacement, a fraction of performance deterioration has been recovered, though not all because the rest of the turbine system has been operating for thirteen years from its original state. Finally, it should be noted that the estimate of performance decline is basically consistent with the few results available in the literature.
Journal Article
Advanced Discretisation and Visualisation Methods for Performance Profiling of Wind Turbines
Wind turbines are typically organised as a fleet in a wind park, subject to similar, but varying, environmental conditions. This makes it possible to assess and benchmark a turbine’s output performance by comparing it to the other assets in the fleet. However, such a comparison cannot be performed straightforwardly on time series production data since the performance of a wind turbine is affected by a diverse set of factors (e.g., weather conditions). All these factors also produce a continuous stream of data, which, if discretised in an appropriate fashion, might allow us to uncover relevant insights into the turbine’s operations and behaviour. In this paper, we exploit the outcome of two inherently different discretisation approaches by statistical and visual analytics. As the first discretisation method, a complex layered integration approach is used. The DNA-like outcome allows us to apply advanced visual analytics, facilitating insightful operating mode monitoring. The second discretisation approach is applying a novel circular binning approach, capitalising on the circular nature of the angular variables. The resulting bins are then used to construct circular power maps and extract prototypical profiles via non-negative matrix factorisation, enabling us to detect anomalies and perform production forecasts.
Journal Article
Innovative approaches to productivity monitoring: Integrating work sampling and electronic performance monitoring
Electronic performance monitoring (EPM) in workforce productivity lacks quantitative indexes, such as labour rating factors (LRFs). This study introduces an integrated method using smartphones and work sampling (WS) to measure productivity based on LRF. An experiment with 10 welders in a pipe shop demonstrated the method’s effectiveness. This research aims to fill this gap using the design science research (DSR) methodology to introduce an integrated method based on electronic devices (smartphones) and human observation WS to measure productivity based on LRF. To demonstrate and evaluate this method, an experiment was carried out with industrial workers while welding steel pipes in low-carbon alloy using tungsten inert gas (TIG) and flux-cored arc welding (FCAW) methods. The results indicate the feasibility of this integrated method based on the complementarity of the WS and the EPM approach tested. The LRF using WS was determined to be 55.52% while the EPM factor was 57.78%. Also, welders are directly engaged in the welding process 75.55% of the time. Considering a standard productive state average of 50%, EPM results can represent an accuracy of 84%–96% of the LRF. The electronic method based only on the workers’ location has the limitation of not identifying idleness within the production zone (PZ); as a result, some calibration is provided by the WS method. This research contributes a low-cost, accessible approach for continuous productivity improvement. The integrated method allows for both quantitative measurement and qualitative diagnosis of productivity factors, bridging the gap between traditional and modern monitoring techniques.
Journal Article
Resource efficiency of processing plants
This monograph provides foundations, methods, guidelines and examples for monitoring and improving resource efficiency during the operation of processing plants and for improving their design. The measures taken to improve their energy and resource efficiency are strongly influenced by regulations and standards which are covered in Part I of this book. Without changing the actual processing equipment, the way how the processes are operated can have a strong influence on the resource efficiency of the plants and this potential can be exploited with much smaller investments than needed for the introduction of new process technologies. This aspect is the focus of Part II. In Part III we discuss physical changes of the process technology such as heat integration, synthesis and realization of optimal processes, and industrial symbiosis. The last part deals with the people that are needed to make these changes possible and discusses the path towards a company and sector wide resource efficiency culture. Written with industrial solutions in mind, this text will benefit practitioners as well as the academic community.
eBook
Advanced Process Control: From a PID Loop up to Refinery-Wide Optimization
Advanced process control (APC) provides distributed control systems with wider functionality thus improving operations efficiency. At the same time, APC systems create a framework for higher-level optimization solutions. The paper outlines the key features and advantages of Honeywell Profit® Suite product family enabling effective and user-friendly design of layered optimization solutions. With a case study of a major Russian refinery it overviews the development and operation history of advanced control (AC) and optimization solutions from a PID loop up to a group of interrelated process units.
Journal Article
Building energy information systems: user case studies
Measured energy performance data are essential to national efforts to improve building efficiency, as evidenced in recent benchmarking mandates, and in a growing body of work that indicates the value of permanent monitoring and energy information feedback. This paper presents case studies of energy information systems (EIS) at four enterprises and university campuses, focusing on the attained energy savings, and successes and challenges in technology use and integration. EIS are broadly defined as performance monitoring software, data acquisition hardware, and communication systems to store, analyze, and display building energy information. Case investigations showed that the most common energy savings and instances of waste concerned scheduling errors, measurement and verification, and inefficient operations. Data quality is critical to effective EIS use, and is most challenging at the subsystem or component level, and with non-electric energy sources. Sophisticated prediction algorithms may not be well understood but can be applied quite effectively, and sites with custom benchmark models or metrics are more likely to perform analyses external to the EIS. Finally, resources and staffing were identified as a universal challenge, indicating a need to identify additional models of EIS use that extend beyond exclusive in-house use, to analysis services.
Journal Article
Biomarkers and Detection Platforms for Human Health and Performance Monitoring: A Review
Human health and performance monitoring (HHPM) is imperative to provide information necessary for protecting, sustaining, evaluating, and improving personnel in various occupational sectors, such as industry, academy, sports, recreation, and military. While various commercially wearable sensors are on the market with their capability of “quantitative assessments” on human health, physical, and psychological states, their sensing is mostly based on physical traits, and thus lacks precision in HHPM. Minimally or noninvasive biomarkers detectable from the human body, such as body fluid (e.g., sweat, tear, urine, and interstitial fluid), exhaled breath, and skin surface, can provide abundant additional information to the HHPM. Detecting these biomarkers with novel or existing sensor technologies is emerging as critical human monitoring research. This review provides a broad perspective on the state of the art biosensor technologies for HHPM, including the list of biomarkers and their physiochemical/physical characteristics, fundamental sensing principles, and high‐performance sensing transducers. Further, this paper expands to the additional scope on the key technical challenges in applying the current HHPM system to the real field. Detecting biomarkers with novel or existing sensor technologies is emerging as critical human monitoring research. This review provides a broad perspective on the state‐of‐art biosensor technologies for human health and performance monitoring, including the list of biomarkers and their physiochemical/physical characteristics, fundamental sensing principles, high‐performance transducers, and the key technical challenges in applying the current system to the real field.
Journal Article
Effect of formation, ball in play and ball possession on peak demands in elite soccer
This study examined the most demanding passages of match play (MDP) and the effects of playing formation, ball-in-play (BiP) time and ball possession on the 1-min peak (1-min
) demand in elite soccer. During 18 official matches, 305 individual samples from 223 Italian Serie A soccer players were collected. MDP and 1-min
were calculated across playing position (central defenders, wide defenders, central midfielders, wide midfielders, wide forwards and forwards). Maximum relative (m·min
) total distance (TD), high-speed running (HSR), very high-speed running (VHSR), sprint (SPR), acceleration/deceleration (Acc/Dec), estimated metabolic power (P
) and high-metabolic load (HML) distance were calculated across different durations (1-5, 10, 90 min) using a rolling method. Additionally, 1-min
demand was compared across playing formation (3-4-1-2, 3-4-2-1, 3-5-2, 4-3-3, 4-4-2), BiP and ball/no-ball possession cycles. MDP showed large to verylarge [effect-size (ES): 1.20/4.06] differences between 1-min
vs all durations for each parameter. In 1-min
, central midfielders and wide midfielders achieved greater TD and HSR (ES:0.43/1.13) while wide midfielders and wide forwards showed greater SPR and Acc/Dec (ES:0.30/1.15) than other positions. For VHSR, SPR and Acc/Dec 1-min
showed fourfold higher locomotor requirements than 90-min. 1-min
for Acc/Dec was highest in 4-3-3 for forwards, central and wide midfielders. 1-min
was lower during peak BiP (BiP
) for HSR, VHSR and Acc/Dec (ES: -2.57/-1.42). Comparing with vs without ball possession, BiP
was greater (ES: 0.06/1.48) in forwards and wide forwards and lower (ES: -2.12/-0.07) in central defenders and wide defenders. Positional differences in MDP, 1-min
and BiP
were observed. Soccer-specific drills should account for positional differences when conditioning players for the peak demands. This may help practitioners to bridge the training/match gap.
Journal Article
A teamwork effectiveness model for agile software development
Teamwork is crucial in software development, particularly in agile development teams which are cross-functional and where team members work intensively together to develop a cohesive software solution. Effective teamwork is not easy; prior studies indicate challenges with communication, learning, prioritization, and leadership. Nevertheless, there is much advice available for teams, from agile methods, practitioner literature, and general studies on teamwork to a growing body of empirical studies on teamwork in the specific context of agile software development. This article presents the agile teamwork effectiveness model (ATEM) for colocated agile development teams. The model is based on evidence from focus groups, case studies, and multi-vocal literature and is a revision of a general team effectiveness model. Our model of agile teamwork effectiveness is composed of shared leadership, team orientation, redundancy, adaptability, and peer feedback. Coordinating mechanisms are needed to facilitate these components. The coordinating mechanisms are shared mental models, communication, and mutual trust. We critically examine the model and discuss extensions for very small, multi-team, distributed, and safety-critical development contexts. The model is intended for researchers, team members, coaches, and leaders in the agile community.
Journal Article