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3. Empirical Mode Decomposition Empirical mode decomposition (EMD) [GEO 14, HE 13, HUA 98b] consists in decomposing every signal x(t) in a combination of components, called intrinsic mode functions (IMFs), which represent the simple oscillating modes of the signal. In general, the component with the smallest period (high frequency) is considered as the first IMF. The components with the longest periods (low frequency) are then decomposed according to their order to obtain the following IMFs. The interest of this method is that it is possible to isolate the frequency bands that contain the defect by retaining only the correspondent IMFs.

8). 7. 8. First extracted IMF 90 100 Processing: From Data to Health Indicators 43 If p10 satisfies the condition of an IMF, then it is considered as the first component of x(t). 4) Otherwise, it is considered as an initial signal and the steps from 1 to 3 are repeated. 6] The process resulting from the four steps above is called sifting. It is repeated until an instant k, correspondent to pik , such that the average curve between the upper and lower envelopes is close to zero in any point. 7] where m1(k−1) is the average of the upper and lower envelopes of the signal p1(k−1) .

1. Types of sensors There are different types of sensors that work according to different physical principles and are manufactured with different technologies. The goal here is not to describe the operating principle of every sensor, but, rather, to take the inventory of sensors and their utilization domains. More details on these categories can be found in [ASC 03]. We can distinguish current generating sensors, charge generating sensors, resistive sensors, inductive sensors, capacitive sensors, and sensors for highly perturbed environments.

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Aircraft Stability and Control by A. W. Babister


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