Assessing the Utility of Early Warning Systems for Detecting Failures in Major Wind Turbine Components

This paper provides enhancements to normal behaviour models for monitoring major wind turbine components and a methodology to assess the monitoring system reliability based on SCADA data and decision analysis. Typically, these monitoring systems are based on fully data-driven regression of damage sensitive-parameters. Firstly, the problem of selecting suitable inputs for building a temperature model of operating main bearings is addressed, based on a sensitivity study. This shows that the dimensionality of the dataset can be greatly reduced while reaching sufficient prediction accuracy. Subsequently, performance quantities are derived from a statistical description of the prediction error and used as input to a decision analysis. Two distinct intervention policies, replacement and repair, are compared in terms of expected utility. The aim of this study is to provide a method to quantify the benefit of implementing the online system from an economic risk perspective. Under the realistic hypotheses made, the numerical example shows for instance that replacement is not convenient compared to repair

On the Use of Reciprocal Filter against WiFi Packets for Passive Radar

This paper aims at a critical review of the signal processing scheme used in WiFi-based passive radar in order to limit its complexity and enhance its suitability for short range civilian applications. To this purpose the exploitation of a reciprocal filtering strategy is investigated as an alternative to conventional matched filtering at the range compression stage. Along with the well-known advantage of a remarkable sidelobes control capability for the resulting range-Doppler response, the use of a reciprocal filter is shown to provide additional benefits for the specific sensor subject of this study. Specifically, it allows to streamline the disturbance cancellation stage and to implement a unified signal processing architecture which is capable to handle the different modulation schemes typically adopted in WiFi transmissions. Appropriate adjustments are also proposed to the theoretical reciprocal filter in order to cope with the inherent loss in term of signal-to-noise power ratio. The effectiveness of the revised signal processing scheme encompassing the reciprocal filtering strategy is proved against both simulated and experimental datasets

Reducing the Computational Complexity of WiFi-Based Passive Radar Processing

WiFi-based passive radar is considered in this paper as an effective technology for short range monitoring applications. Aiming at limiting its complexity and enhancing its suitability for civilian applications, appropriate modifications are proposed to the signal processing scheme originally designed for such sensor. Specifically, we show that a simple inversion in the order of the main processing stages, namely clutter cancellation and range compression, allows to both reduce the number of floating-point operations and relax the requirements on the data management. Moreover, the use of a reciprocal filter in lieu of a matched filter to implement the range compression stage is proved to yield a further simplification in the resulting processing scheme along with additional benefits in terms of achievable performance in the considered application. The alternative processing schemes are compared in terms of computational burden and the effectiveness of the proposed cost-effective solutions is proved against experimental datasets

OFDM based WiFi Passive Sensing: a reference-free non-coherent approach

WiFi based passive sensing is attracting considerable interest in the scientific community for both research and commercial purposes. In this work, we aim at taking a step forward in an endeavor to achieve good sensing capabilities employing compact, low-cost, and stand-alone WiFi sensors. To this end, we resort to a reference-free non-coherent signal processing scheme, where the presence of a moving target echo is sought by detecting the amplitude modulation that it produces on the direct signal transmitted from the WiFi access point. We first validate the proposed strategy against simulated data, identifying advantages and limitations. Then, we apply the conceived solution on experimental data collected in a small outdoor area with the purpose of detecting a small cooperative drone

Optimisation of Data Acquisition in Wind Turbines with Data-Driven Conversion Functions for Sensor Measurements

Operation and Maintenance (O&M) is an important cost driver of modern wind turbines. Condition monitoring (CM) allows the implementation of predictive O&M strategies helping to reduce costs. In this work a novel approach for wind turbine condition monitoring is proposed focusing on synergistic effects of coexisting sensing technologies. The main objective is to understand the predictability of signals using information from other measurements recorded at different locations of the turbine. The approach is based on a multi-step procedure to pre-process data, train a set of conversion functions and evaluate their performance. A subsequent sensitivity analysis measuring the impact of the input variables on the predicted response reveals hidden relationships between signals. The concept feasibility is tested in a case study using Supervisory Control And Data Acquisition (SCADA) data from an offshore turbine

Membrane transport proteins in human melanoma: associations with tumour aggressiveness and metastasis

BACKGROUND: Malignant melanoma, generally described as incurable, is notoriously refractory to chemotherapy. The mechanisms contributing to this have not yet been defined and the contributions of drug efflux pumps, implicated in chemo-resistance of many other cancer types, have not been extensively investigated in melanoma. METHODS: In this study, expression of multi-drug resistant (MDR1/P-gp and MRP-1) proteins was examined, by immunohistochemistry, in archival specimens from 134 melanoma patients. This included 92 primary tumours and 42 metastases. RESULTS: On assessing all specimens, MRP-1 and MDR1/P-gp expression was found to be common, with the majority (81%) of melanomas expressing at least one of these efflux pumps. Although there is significant association between expression of these pumps (P=0.007), MRP-1 was found to be the predominant (67% of cases) form detected. chi(2) analysis showed significant associations between expression of MRP-1 and/or MDR1/P-gp and the aggressive nature of this disease specifically increased Breslow's depth, Clark's level and spread to lymph nodes. This association with aggressiveness and spread is further supported by the observation that a significantly higher percentage of metastases, than primary tumours, express MRP-1 (91% vs 57%; P<0.0001) and MDR1/P-gp (74% vs 50%; P=0.010). CONCLUSION: The predominant expression of these pumps and, in particular, MRP-1 suggests that they may be important contributors to the inherent aggressive and resistant nature of malignant melanoma

Podoplanin Associates with CD44 to Promote Directional Cell Migration

Podoplanin, a cancer-associated glycoprotein, interacts with CD44. Both glycoproteins are coordinately upregulated during tumor progression. Podoplanin–CD44 interaction in the cell membrane occurs mainly in migrating cells, and it seems to be required for podoplanin-mediated cell migration and directionality

Co-expression of CD147 (EMMPRIN), CD44v3-10, MDR1 and monocarboxylate transporters is associated with prostate cancer drug resistance and progression

Background: The aim of this study is to seek an association between markers of metastatic potential, drug resistance-related protein and monocarboxylate transporters in prostate cancer (CaP). Methods: We evaluated the expression of invasive markers (CD147, CD44v3-10), drug-resistance protein (MDR1) and monocarboxylate transporters (MCT1 and MCT4) in CaP metastatic cell lines and CaP tissue microarrays (n=140) by immunostaining. The co-expression of CD147 and CD44v3-10 with that of MDR1, MCT1 and MCT4 in CaP cell lines was evaluated using confocal microscopy. The relationship between the expression of CD147 and CD44v3-10 and the sensitivity (IC50) to docetaxel in CaP cell lines was assessed using MTT assay. The relationship between expression of CD44v3-10, MDR1 and MCT4 and various clinicopathological CaP progression parameters was examined. Results: CD147 and CD44v3-10 were co-expressed with MDR1, MCT1 and MCT4 in primary and metastatic CaP cells. Both CD147 and CD44v3-10 expression levels were inversely related to docetaxel sensitivity (IC50) in metastatic CaP cell lines. Overexpression of CD44v3-10, MDR1 and MCT4 was found in most primary CaP tissues, and was significantly associated with CaP progression. Conclusions: Our results suggest that the overexpression of CD147, CD44v3-10, MDR1 and MCT4 is associated with CaP progression. Expression of both CD147 and CD44v3-10 is correlated with drug resistance during CaP metastasis and could be a useful potential therapeutic target in advanced disease

Protection by Anti-β-Glucan Antibodies Is Associated with Restricted β-1,3 Glucan Binding Specificity and Inhibition of Fungal Growth and Adherence

Anti-β-glucan antibodies elicited by a laminarin-conjugate vaccine confer cross-protection to mice challenged with major fungal pathogens such as Candida albicans, Aspergillus fumigatus and Cryptococcus neoformans. To gain insights into protective β-glucan epitope(s) and protection mechanisms, we studied two anti-β-glucan monoclonal antibodies (mAb) with identical complementarity-determining regions but different isotypes (mAb 2G8, IgG2b and mAb 1E12, IgM). C. albicans, the most relevant fungal pathogen for humans, was used as a model