Transfer learning applications for anomaly detection in wind turbines

Anomaly detection in wind turbines typically involves using normal behaviour models to detect faults early. However, training autoencoder models for each turbine is time-consuming and resource intensive. Thus, transfer learning becomes essential for wind turbines with limited data or applications with limited computational resources. This study examines how cross-turbine transfer learning can be applied to autoencoder-based anomaly detection. Here, autoencoders are combined with constant thresholds for the reconstruction error to determine if input data contains an anomaly. The models are initially trained on one year's worth of data from one or more source wind turbines. They are then fine-tuned using smaller amounts of data from another turbine. Three methods for fine-tuning are investigated: adjusting the entire autoencoder, only the decoder, or only the threshold of the model. The performance of the transfer learning models is compared to baseline models that were trained on one year's worth of data from the target wind turbine. The results of the tests conducted in this study indicate that models trained on data of multiple wind turbines do not improve the anomaly detection capability compared to models trained on data of one source wind turbine. In addition, modifying the model's threshold can lead to comparable or even superior performance compared to the baseline, whereas fine-tuning the decoder or autoencoder further enhances the models' performance.Comment: 16 pages, 7 figures, preprint submitted to Energy&A

Recommended practices for wind farm data collection and reliability assessment for O&M optimization

The paper provides a brief overview of the aims and main results of IEA Wind Task 33. IEA Wind Task 33 was an expert working group with a focus on data collection and reliability assessment for O & M optimization of wind turbines. The working group started in 2012 and finalized the work in 2016. The complete results of IEA Wind Task 33 are described in the expert group report on recommended practices for "Wind farm data collection and reliability assessment for O & M optimization" which will be published by IEA Wind in 2017. This paper briefly presents the background of the work, the recommended process to identify necessary data, and appropriate taxonomies structuring and harmonizing the collected entries. Finally, the paper summarizes the key findings and recommendations from the IEA Wind Task 33 work

QOL-31. Neuropsychological functioning and quality of life in infant AT/RT survivors: focus on fluid intelligence and visual processing [Abstract]

BACKGROUND Understanding the long-term cognitive sequelae in infant brain tumor survivors remains incomplete, particularly regarding the impact of tumor type, multimodal treatment, and other patient-related factors. This retrospective analysis explores neuropsychological and quality of survival (QoS) outcomes in survivors of atypical teratoid/rhabdoid tumors (AT/RT) and extracranial malignant rhabdoid tumors of soft tissues (eMRT) and kidneys (RTK), all treated within the same framework. Neuropsychological data from children with AT/RT were compared to data from children with non-irradiated low-grade glioma (LGG). METHODS Patients (0 - 36 months at diagnosis) underwent various treatments, including radio-chemotherapy for AT/RT (n = 13) and eMRT/RTK (n = 7), chemotherapy only for LGG (n = 4) and eMRT/RTK (n = 1), or observation for LGG (n = 11). Neuropsychological evaluations were conducted at a median of 6.8 years (AT/RT), 6.6 years (eMRT/RTK), and 5.2 years (LGG) post-diagnosis. RESULTS Impairments were observed for all tumour types. Patients with AT/RT exhibited impairments in fluid intelligence (p =.041; d = 1.11) and visual processing (p =.001; d = 2.09) when compared to LGG-patients. Both groups demonstrated deficits in psychomotor speed and attention abilities (p <.001–.019; d = 0.79–1.90). Diagnosis significantly predicted cognitive outcomes, whereas gender and age-related variables did not. QoS outcomes for all rhabdoid patients indicated lower scores in psychosocial functioning (p =.023; d = 0.78) and quality of life (p =.006; d = 0.79) compared to healthy controls. CONCLUSIONS Infant rhabdoid tumor survivors experience cognitive and quality-of-life sequelae. Patients with AT/RT are especially vulnerable to impairments in fluid intelligence and visual processing, while infant LGG-patients without radiotherapy demonstrated comparable deficits in psychomotor and attention abilities. Close monitoring of neuropsychological and quality of life outcomes is crucial for early onset and multimodal treatment

Survivors of infant atypical teratoid/rhabdoid tumors present with severely impaired cognitive functions especially for fluid intelligence and visual processing: data from the German brain tumor studies

Background The contribution of tumor type, multimodal treatment, and other patient-related factors upon long-term cognitive sequelae in infant brain tumor survivors remains undefined. We add our retrospective analysis of neuropsychological and quality of survival (QoS) outcome data of survivors of atypical teratoid/rhabdoid tumors (ATRT) and extracranial malignant rhabdoid tumors of the soft tissues (eMRT) and kidneys (RTK) treated within the same framework. Neuropsychological data from children with ATRT were compared to data from children with non-irradiated low-grade glioma (LGG). Patients and methods Following surgery, patients (0–36 months at diagnosis) had received radio-chemotherapy (up to 54 Gy; ATRT: n = 13; eMRT/RTK: n = 7), chemotherapy only (LGG: n = 4; eMRT/RTK: n = 1) or had been observed (LGG: n = 11). Neuropsychological evaluation employing comparable tests was performed at median 6.8 years (ATRT), 6.6 years (eMRT/RTK), and 5.2 years (LGG) post diagnosis. Results We detected sequelae in various domains for all tumor types. Group comparison showed impairments, specifically in fluid intelligence (p = .041; d = 1.11) and visual processing (p = .001; d = 2.09) in ATRT patients when compared to LGG patients. Results for psychomotor speed and attention abilities were significantly below the norm for both groups (p < .001–.019; d = 0.79–1.90). Diagnosis predicted impairments of cognitive outcome, while sex- and age-related variables did not. QoS outcome for all rhabdoid patients displayed impairments mainly in social (p = .008; d = 0.74) and school functioning (p = .048; d = 0.67), as well as lower overall scores in psychosocial functioning (p = .023; d = 0.78) and quality of life (p = .006; d = 0.79) compared to healthy controls. Conclusion Survivors of infant ATRT experience various late effects in cognition and QoS following multimodal treatment, while infant LGG patients without radiotherapy demonstrated comparable impairments in psychomotor and attention abilities. Early onset and multimodal treatment of rhabdoid tumors require close monitoring of neuropsychological and QoS sequelae

Failure Modes, Effects and Criticality Analysis for Wind Turbines Considering Climatic Regions and Comparing Geared and Direct Drive Wind Turbines

The wind industry is looking for ways to accurately predict reliability and availability of newly installed wind turbines. Failure modes, effects and criticality analysis (FMECA) is a technique utilized to determine the critical subsystems of wind turbines. There are several studies in the literature which have applied FMECA to wind turbines, but no studies so far have used it considering different weather conditions or climatic regions. Furthermore, different wind turbine design types have been analyzed applying FMECA either distinctively or combined, but no study so far has compared the FMECA results for geared and direct-drive wind turbines. We propose to fill these gaps by using Koppen-Geiger climatic regions and two different turbine models of direct-drive and geared-drive concepts. A case study is applied on German wind farms utilizing the Wind Measurement &amp; Evaluation Programme (WMEP) database which contains wind turbine failure data collected between 1989 and 2008. This proposed methodology increases the accuracy of reliability and availability predictions and compares different wind turbine design types and eliminates underestimation of impacts of different weather conditions

Performance and Reliability of Wind Turbines: A Review

Performance (availability and yield) and reliability of wind turbines can make the difference between success and failure of wind farm projects and these factors are vital to decrease the cost of energy. During the last years, several initiatives started to gather data on the performance and reliability of wind turbines on- and offshore and published findings in different journals and conferences. Even though the scopes of the different initiatives are similar, every initiative follows a different approach and results are therefore difficult to compare. The present paper faces this issue, collects results of different initiatives and harmonizes the results. A short description and assessment of every considered data source is provided. To enable this comparison, the existing reliability characteristics are mapped to a system structure according to the Reference Designation System for Power Plants (RDS-PP®). The review shows a wide variation in the performance and reliability metrics of the individual initiatives. Especially the comparison on onshore wind turbines reveals significant differences between the results. Only a few publications are available on offshore wind turbines and the results show an increasing performance and reliability of offshore wind turbines since the first offshore wind farms were erected and monitored