Machine learning augmented multi-sensor data fusion to detect aero engine fan rotor blade flutter

Flutter-induced fatigue failure investigation of the fan blades of aero-engines necessitates extensive testing. During engine ground testing, strain gauges on rotor fan blades and casing vibration sensors were employed to investigate structural dynamic aspects. The correlation between strain sensor signals and fan casing vibration signals allowed the diagnosis of fluttering fan blades. For automated flutter detection during engine development testing, a machine learning-augmented information fusion methodology was developed. The method analyses casing vibration signals by extracting time-domain statistical features, intrinsic mode function characteristics through empirical mode decomposition, and recurrence quantification features. Feature vectors obtained from a relatively large set of engine tests were subjected to dimension reduction by applying machine learning techniques to rank them. Reduced feature vector space was labelled as "flutter"or "normal"based on the correlation of rotor strain gauge signals. In addition, the labelled feature vectors were employed to train classifier models using supervised learning-based algorithms such as Support Vector Machines, Linear Discriminant Analysis, K-means Clustering, and Artificial Neural Networks. Using only vibration signals from the casing, the trained and validated classifiers were able to detect flutter in fan baldes with a 99% probability during subsequent testing

Corn starch changes during tortilla and tortilla chip processing.

Objective: The present study aimed to investigate effect of addition date seed powder on the chemical composition, rheological properties, diffraction scanning colorimetric, x-ray diffraction, infra-red (IR), flavonoid, antioxidant activity, total phenolic compounds and sensory evaluation of snack from them. Methodology: Raw materials (oat and date seed flour) and snacks were analyzed for their proximate composition, rheological (rapid viscoanalyzer and following number), physical properties, color and texture were subjected to measurements using Differential Scanning Calorimetery (DSC). Each sample was tested for its color, flavor, taste, crispness, appearance and overall acceptability. Results: The obtained results revealed that, incorporation of date seed powder resulted in a significant increase in fibre and ash contents and in a decrease in protein content. Increasing DS levels in snacks led to increase the falling