دانلود مقاله ISI انگلیسی شماره 65306
عنوان فارسی مقاله

عیب یابی گیربکس سیاره ای با استفاده از روش تصادفی رزونانس تطبیقی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
65306 2013 12 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Planetary gearbox fault diagnosis using an adaptive stochastic resonance method
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Mechanical Systems and Signal Processing, Volume 38, Issue 1, 5 July 2013, Pages 113–124

کلمات کلیدی
گیربکس های سیاره ای - رزونانس تصادفی تطبیقی؛ استخراج ویژگی ضعیف؛ عیب یابی
پیش نمایش مقاله
پیش نمایش مقاله عیب یابی گیربکس سیاره ای با استفاده از روش تصادفی رزونانس تطبیقی

چکیده انگلیسی

Planetary gearboxes are widely used in aerospace, automotive and heavy industry applications due to their large transmission ratio, strong load-bearing capacity and high transmission efficiency. The tough operation conditions of heavy duty and intensive impact load may cause gear tooth damage such as fatigue crack and teeth missed etc. The challenging issues in fault diagnosis of planetary gearboxes include selection of sensitive measurement locations, investigation of vibration transmission paths and weak feature extraction. One of them is how to effectively discover the weak characteristics from noisy signals of faulty components in planetary gearboxes. To address the issue in fault diagnosis of planetary gearboxes, an adaptive stochastic resonance (ASR) method is proposed in this paper. The ASR method utilizes the optimization ability of ant colony algorithms and adaptively realizes the optimal stochastic resonance system matching input signals. Using the ASR method, the noise may be weakened and weak characteristics highlighted, and therefore the faults can be diagnosed accurately. A planetary gearbox test rig is established and experiments with sun gear faults including a chipped tooth and a missing tooth are conducted. And the vibration signals are collected under the loaded condition and various motor speeds. The proposed method is used to process the collected signals and the results of feature extraction and fault diagnosis demonstrate its effectiveness.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.