Abstract:
A method and system for establishing sets of blade frequency values for each rotating blade of a rotor assembly at two or more different points in time and determining an indication of blade health from the change in the blade frequency values is provided. Blade frequency values are determined by receiving measurements of vibratory responses from blade monitoring equipment (20) and processing via a processing device (30) vibration data as a system of rotating blades to extract a frequency of each blade. Sets of blade frequency values are compared to determine a change in the blade frequency values for each rotating blade to provide the indication of blade health.
Abstract:
Method and apparatus for vibration-based automatic condition monitoring of a wind turbine (1), comprising the steps of: determining a set of vibration measurement values of the wind turbine (1); calculating a frequency spectrum of the set of vibration measurement values; calculating a cepstrum of the frequency spectrum; selecting at least one quefrency in the cepstrum, and detecting an alarm condition based upon an amplitude of the cepstrum at the selected quefrency, and a wind turbine (1) therefor.
Abstract:
This invention comprises a vibration sensor for detecting engine knock. The sensor has a tuning mechanism which is mechanically resonant with a preselected vibrational frequency. The resonating movements of this tuning mechanism are adapted to apply varying stress to an associated magnetostrictive element. A magnetic biasing element imparts a magnetization to the magnetostrictive element and a detecting means is associated with the magnetostrictive element for detecting changes in the magnetization caused by the varying applied stress.
Abstract:
A signal processing technique (30 of figure 2) that decomposes complex, dynamically changing non-stationary signals from machine components such as bearings into different scales by means of a continuous wavelet transform (34 of figure 2). The envelope signal in each scale is then calculated from the modulus of the wavelet coefficients (36 of figure 2). Subsequently, Fourier transform (38 of figure 2) is performed repetitively on the envelope of the signal at each scale, resulting in an 'envelope spectrum' of the original signal at the various scales. The final output (42 of figure 2) is a three-dimensional scale-frequency map that indicates the intensity and location of the defect- related frequency lines. The technique is generic in nature, and applicable not only to machine condition monitoring, but also to the health monitoring of a wide range of dynamic systems, including human beings.
Abstract:
A vibration wave detector in which: a plurality of resonator beams, each having a different length and being allowed to resonate at a specific frequency, are provided; a piezoresistor is installed in each resonator beam; and the piezoresistors are parallel-connected so that vibration is converted to an electric signal by the piezoresistors so as to output the sum of vibration waveforms at the respective resonator beams. It is possible to control a gain of a specific frequency band by changing a voltage to be applied to the parallel circuit or changing the resistance value of each piezoresistor.
Abstract:
Es ist ein Schwingungs-Sensor anzugeben, welcher eine oder mehrere Zungen aufweist, die durch mechanische Schwingungen angeregt werden und der besonders einfach und wirtschaftlich in kleinen Abmessungen herstellbar ist. Die Zungen sind aus einem Substrat geätzt, wobei auf dem Substrat auch die Einrichtungen zur Umsetzung der mechanischen Schwingungen der Zunge in elektrische Signale und Einrichtungen zur Auswertung derselben auf dem Substrat untergebracht sind. Ein derartiger Schwingungs-Sensor kann beispielsweise zur Erkennung des Verschleißes bei mechanisch bewegten Teilen benutzt werden, bei denen kritische Schwingungen den Verschleiß in einem sehr frühen Stadium anzeigen. Hierbei kann es sich beispielsweise um die Lager drehbarer Wellen von Motoren und Turbinen handeln.
Abstract:
Dans ce procédé d'identification d'une source d'un signal, le signal est enregistré puis analysé afin de déterminer son spectre. Il comporte en outre les étapes suivantes :
a) parallèlement à l'enregistrement du signal, des paramètres significatifs des conditions dans lesquelles l'enregistrement a été réalisé sont mémorisés, b) après analyse du signal et détermination de son spectre, détection de raies émergeant du bruit de fond du signal avec un seuil d'émergence prédéterminé, c) comparaison de chaque raie détectée avec tout ou partie d'un ensemble de signatures de sources identifiées et répertoriées dans une base de données établie avant l'enregistrement, d) pour chaque raie, sélection éventuelle de signatures pouvant correspondre à cette raie, et en fonction du nombre de signatures retenues, réalisation d'une consolidation éventuellement, d'une désambiguïsation ou d'une quantification de la source correspondant à la raie.