The exploitation of cyclostationarity properties of vibratory signals is now more widelyused for monitoring rotating machinery and especially for diagnosing bearing defects. Theacoustic emission (AE) technology has also emerged as a reliable tool for preventivemaintenance of rotating machines. In this study, we propose an experimental study thatcharacterizes the cyclostationary aspect of acoustic emission (AE) signals recorded from adefective bearing (40 μm on the outer race) to see its efficiency to detecta defect at its very early stage of degradation. An industrial sensor (UE10 000) is used.An electrical circuit converts the high frequency signal into an audible signal byheterodyning. The cyclic spectral density, which is a tool dedicated that put intoevidence the presence of cyclostationarity, is used for characterizing thecyclostationary. Two new indicators based on this cyclostationary technique are proposedand compared for early detection of defective bearings.

This work is interested to the analysis of the vibratory signals coming from a millingoperation. The objective is the detection of cutting tool breakage using thecyclostationary tools. Initially, we will show that the vibration signals captured fromthe milling operation are cyclostationary. The proposed cyclostationary methods are thefirst and second order synchronous statistics and the spectral correlation. A test rig,composed of a milling machine (cutter with 5 teeth) and a workpiece, is used to extractthe vibration signals that are angular sampled in the free fault case and one broken toothcase. This test rig is instrumented with three accelerometers, installed in the threedirections, and an optical encoder that allows the angular sampling. Then we will see thatthe angular sampling of the signals captured from a milling operation is essential topreserve the cyclostationary properties destroyed, in the case of the temporal sampling,by speed fluctuations. The proposed method capacity to detect the broken tooth is shown.The synchronous statistics of order 1 and order 2 detect the broken tooth presence and itsemplacement. The spectral correlation analysis distinguishes the broken tooth presence,but is not practical for the diagnosis. For that, an indicator based on the spectralcorrelation is proposed.

In some Global Positioning System (GPS) signal propagation environments, especially in the ionosphere and urban areas with heavy multipath, GPS signal encounters not only additive noise but also multiplicative noise. In this paper we compare and contrast the conventional GPS signal acquisition method which focuses on handling GPS signal acquisition with additive noise, with the enhanced GPS signal processing under multiplicative noise by proposing an extension of the GPS detection mechanism, to include the GPS detection model that explains detection of the GPS signal under additive and multiplicative noise. For this purpose, a novel GPS signal detection scheme based on high order cyclostationarity is proposed. The principle is introduced, the GPS signal detection structure is described, the ambiguity of initial PseudoRandom Noise (PRN) code phase and Doppler shift of GPS signal is analysed. From the simulation results, the received GPS signal at low power level, which is degraded by additive and multiplicative noise, can be detected under the condition that the received block of GPS data length is at least 1·6 ms and sampling frequency is at least 5 MHz.

In this paper, the cyclostationary characteristics of electrical signals will beexploited in order to detect the rotor faults of an asynchronous machine. These defectsare the most complex in terms of detection since they interact with the 50 Hz carrier witha weak band occupied in frequency. The testing ground used includes an industrialthree-phase wound rotor asynchronous motor of 400 V, 6.2 A, 50 Hz, 3 kW, 1385 rpmcharacteristics. The rotor fault has been carried out by adding an extra 40 mΩ resistanceon one of the rotor phases (i.e. 10% of the rotor resistance value per phase,Rr = 0.4Ω). From the stator voltage andcurrent acquisition, and by application of the Time Synchronous Averaging (TSA) method tothe stator current, the electrical signal will be conditioned in order to obtain asensitive indicator allowing to easily distinguish the healthy cases from defective ones.

This paper presents a detailed experimental analysis of the cyclostationary properties of low-frequency (LF) noise sources of microwave bipolar devices, in order to improve the LF noise description in compact models. Such models are used to help designers on predicting circuit performances such as phase and amplitude noise in oscillators. We start by reviewing the most relevant experimental and simulation results on the subject, and then investigate the model of conductance fluctuations proposed to explain the 1/f noise of carbon resistors. This simple linear case serves as a basis for understanding the complex case of a non-linear device under large-signal periodic operation. We then present the large-signal small-signal analysis of a pumped junction, focusing on the process of converting the fundamental LF noise process, a current fluctuation, into voltage fluctuations. We show why a stationary noise model would lead to an increase of the voltage noise observed around DC when the device is pumped, while the voltage noise would decrease if a cyclostationary model was used. A great amount of experimental data is presented not only to support our analysis, but also as a mean to distinguish between the two noise processes under consideration: stationary or cyclostationary. The goal of our noise measurement technique was to maximize the difference between those two concepts. Throughout the paper, we revisit some known concepts and show how some experimental results may lead to misinterpretations.

La cyclostationnarité, propriété propre aux processus dont les caractéristiques évoluentcycliquement au cours du temps, offre un cadre particulièrement adapté à l’analyse denombreux signaux acoustiques et vibratoires. Après avoir rappelé les spécificités del’approche cyclostationnaire dans le contexte mécanique, nous montrons à travers plusieursexemples les possibilités qu’elle autorise dans des domaines d’application liés audiagnostic des machines, à l’identification des systèmes mécaniques et à la séparation desources vibro-acoustiques.