نتایج جستجو برای: statistical features vibration signal
تعداد نتایج: 1286524 فیلتر نتایج به سال:
This paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (LSSVM). Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction. The fault diagnosis method co...
Condition diagnosis of multiple bearings system is one of the requirements in industry field, because bearings are used in many equipment and their failure can result in total breakdown. Conditions of bearings commonly are reflected by vibration signals data. In multiple bearing condition diagnosis, it will involve many types of vibration signals data; thus, consequently, it will involve many f...
In practical engineering, quality control of mechanical components or parts of rotational machinery is quite important. As for rolling bearings, the defects from rolling bodies, internal ring, external ring, and retainer are more focused on. Therefore, in this work, a vibration and noise test system is developed for the defect diagnosis of mechanical components above-mentioned. The key point of...
A tractor gearbox test rig has been used to collect signals from different types of bearing faults. For vibration monitoring accelerometers have been used to obtain vibration data. For fuel-injectors a bearing checker has been used in order to collect acoustic data. One class Self Organizing Maps (OCSOM) are used for detecting faults when exposed to actual data from the system representing a ye...
Condition monitoring of machines working under non-stationary operations is one of the most challenging problems in maintenance. A wind turbine is an example of such class of machines. One of effective approaches may be to identify operating conditions and investigate their influence on used diagnostic features. Commonly used methods based on measurement of electric current, rotational speed, p...
This paper presents a review on application of wavelet transform for condition monitoring and fault diagnosis of mechanical equipment. The discrete wavelet transform performs a multilevel signal decomposition to extract fault features from the vibration signal. A review on all the literature of condition monitoring using wavelet transform is certainly not possible. The purpose of this review pa...
In order to measure the nonlinear features of micromechanical resonators, a free damped oscillation method based on stair-stepped frequency sinusoidal pulse excitation is investigated. In the vicinity of the resonant frequency, a frequency stepping sinusoidal pulse sequence is employed as the excitation signal. A set of free vibration response signals, containing different degrees of nonlinear ...
The paper investigates the possibility of decomposing vibration signals into deterministic and nondeterministic parts, based on the Wold theorem. A short description of the theory of adaptive filters is presented. When an adaptive filter uses the delayed version of the input signal as the reference signal, it is possible to divide the signal into a deterministic (gear and shaft related) part an...
This paper presents a study for identifying damage locations in an idealized steel bridge girder using the ambient vibration measurements. A sensitive damage feature is proposed in the context of statistical pattern recognition to address the damage detection problem. The study utilizes an experimental program that consists of a two-span continuous steel beam subjected to ambient vibrations. Th...
An efficient vibration estimation method for synthetic aperture radar (SAR) systems based on phase-analysis method is presented. Small vibrations, which consist of multiple frequency components and are usually rather weak, introduce phase modulation in radar echoes. They contain important signatures of objects. Extracting and analyzing the phase from radar echoes is one of the significant appro...
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