Classification of rolling bearing fault diagnosis skills

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Classification of rolling bearing fault diagnosis skills

Source: China Bearing Network Time: 2017-12-27
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The fault diagnosis skills of rolling bearings mainly include oscillation diagnosis skills, iron spectrum diagnosis skills, temperature diagnosis skills, acoustic diagnosis skills, oil film resistance diagnosis skills and fiber monitoring diagnosis skills; in the meantime; oscillation, iron shop, temperature diagnosis skills are most widely used.
1. When the operation of the bearing component of the oscillating diagnosis skill is fatigued, indented or partially corroded, the bearing will exhibit a periodic pulse signal. This periodic signal may have a sensor mounted on the bearing housing (speed type or acceleration). Type) to accept; after the analysis of the oscillating signal to confirm the bearing fault.
Features: Oscillation diagnosis skills are widely used, online monitoring can be completed, diagnosis is fast; the diagnosis theory is sophisticated.
Application scale: unique monitoring of bearing problems in rotating machinery.
2. The ferrography diagnosis skill bearing wear particles have close contact with their working conditions. The smooth oil with wear particles passes through a strong magnet. 谇 懦 淖饔 淖饔 淖饔 淖饔 拢 匆 匆 匆 匆 匆 匆 匆 匆 匆 媛 媛 媛 媛 媛 媛惶 谔 谔 谔 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14
Features: The machine does not need to collapse, the investment is low; the effect is good, the early fatigue failure of the bearing can be found, and the wear mechanism can be studied.
Application scale: It is suitable for the diagnosis of smooth bearing with smooth oil; it is difficult to use grease-smooth bearings.
3. The oil film resistance test has a smooth and outstanding bearing; because of the action of the oil film; there is a large resistance between the inner and outer rings. Therefore, the resistance of the inner and outer rings of the bearing is measured; the abnormality of the bearing can be discriminated.
Features: The same evaluation criteria can be applied to different working conditions. Abnormal diagnosis of external surface shedding, indentation, cracks, etc. is poor.
Application scale: suitable for occasions where the rotating shaft is exposed.
4. Fiber Optic Monitoring and Diagnosis Skills Fiber monitoring is a diagnostic technique for extracting signals directly from the outer surface of a bearing ring. A displacement sensor made of an optical fiber bundle includes a beam of emitting fibers and a bundle of receiving fibers. The beam is transmitted from the beam of the beam through the end face of the sensor and the bearing. The gap of the outer surface of the ferrule is reflected back; it is received by the receiving fiber bundle; it is converted into an electrical signal by the photoelectric element; after being analyzed and disposed of the electrical signal; the bearing condition can be evaluated.
Features: The fiber displacement sensor has high sensitivity and directly extracts the signal from the bearing surface. The signal-to-noise ratio is improved, which can directly reflect the manufacturing quality, appearance wear, load, smoothness and void condition of the rolling bearing.
Scale of application: Suitable for machines where the sensor can be mounted in the housing.
5. If the temperature is diagnosed, the bearing will have some abnormality; the temperature of the bearing will change. Therefore, according to the change of temperature, it can diagnose the bearing fault; but the ability to discriminate is very low.
Features: a simple diagnosis, a better discriminating effect on bearing burns.
Application scale: a simple routine diagnosis for bearings in machines.
6. Acoustic emission diagnosis skills metal materials because of internal lattice dislocations, grain boundary slippage may be due to the onset and development of internal cracks; both require the release of elastic waves; this representation is called the acoustic emission appearance. When the rolling bearing seizures or cracks; Different types of acoustic emission signals; this can be used to evaluate bearing conditions.
Features: rapid diagnosis, concise, online monitoring.
Application scale: new skills developed in recent years; less use in bearing condition monitoring.
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