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FAG Bearing Abnormal Sound Detection Method

Writer: Eric Bearing Limited

There are two ways to detect abnormal sound of FAG bearings. One is the noise detection method based on acoustics, and the other is the detection method based on vibration.

1. Detection method of abnormal sound

(1) Noise detection method

In a silencing environment where the basic noise is less than 20db, a high-quality microphone is used to extract the bearing sound pressure signal at a certain distance and direction, and the abnormal sound components are extracted through a certain analysis method. It is a direct measurement method for abnormal sound.

(2) Vibration detection method

It is an indirect detection method of abnormal sound, which can be divided into qualitative detection method and quantitative parameter detection method. Among them, the qualitative detection method is divided into monitoring abnormal sound method and observing vibration waveform method. The quantitative parameter detection method is to use the measured parameter values ​​related to the abnormal sound in the tested bearing vibration signal, such as the peak value of the vibration and the crest factor to evaluate the abnormal sound of the bearing.

(3) Measuring instruments for measuring abnormal sound of bearings:

There are many measuring instruments for measuring abnormal bearing sound. These bearing measuring instruments can measure the effective value of bearing vibration and also measure the peak value, crest factor and pulse number reflecting the abnormal bearing sound parameters.  Enough stock for FAG 61852M bearings , if you are looking for , pls contact us . 

2. Vibration signal analysis and diagnosis

FAG bearing vibration is very sensitive to bearing damage, such as peeling, indentation, corrosion, cracks, wear, etc., will be reflected in the bearing and vibration measurement. Therefore, by using a special bearing vibration measuring device (frequency analyzer, etc.), the magnitude of the vibration can be measured, and the specific abnormal situation can be inferred from the frequency distribution. The measured value varies depending on the use condition of the bearing or the installation position of the sensor, so it is necessary to analyze and compare the measured value of each machine in advance to determine the judgment standard.

There are many kinds of FAG rolling bearing fault detection and diagnosis technologies, such as vibration signal detection, lubricating oil analysis and detection, temperature detection, acoustic emission detection, etc. Among the various diagnostic methods, the vibration signal-based diagnostic technology is the most widely used. The technology is divided into two types: simple diagnostic method and precise diagnostic method. Simple diagnosis uses various parameters of the vibration signal waveform, such as amplitude, form factor, crest factor, probability density, kurtosis coefficient, etc., as well as various demodulation techniques to make preliminary judgments on the bearing to confirm whether there is a fault; precise diagnosis uses Various modern signal processing methods determine the fault category and cause of the bearing that is considered to be faulty in the simple diagnosis.

3. Acoustic emission detection

The principle of acoustic emission detection technology is that when materials are deformed or cracked by external or internal forces, the phenomenon of releasing strain energy in the form of elastic waves is called acoustic emission. The technology of using instruments to detect and analyze acoustic emission signals and use acoustic emission signals to infer the source of acoustic emission is called acoustic emission detection technology, which uses the phenomenon that particles within a substance release strain energy in the form of elastic waves due to relative motion to identify and understand substances Or the internal state of the structure.

Acoustic emission signals include burst type and continuous type. The burst acoustic emission signal consists of pulses that are distinguished from the background noise and can be separated in time; the single pulse of the continuous acoustic emission signal is indistinguishable. In fact, continuous acoustic emission signals are also composed of a large number of small burst-type signals, but they are too dense to distinguish. In the case of poor running of rolling bearings, both sudden and continuous acoustic emission signals may be generated. The relative movement between the contact surfaces of the various components of the bearing (inner ring, outer ring, rolling element and cage), Hertz contact stress caused by rubbing, and surface cracks, wear, indentation, etc. due to failure, overload, etc. Faults such as grooving, occlusion, poor lubrication caused by rough surface, surface hard edges caused by lubricating pollution particles, and pitting caused by current passing through the bearing, all produce sudden acoustic emission signals.

The continuous acoustic emission signal mainly comes from poor lubrication (such as the failure of the lubricating oil film, the immersion of pollutants in the grease), which leads to the oxidation and wear of the bearing surface, resulting in global faults, excessively high temperatures, and frequent occurrence of local bearing faults. These factors result in a large number of sudden acoustic emission events in a short period of time, resulting in continuous acoustic emission signals. During the operation of the rolling bearing, its failure (whether it is surface damage, crack or wear failure) will cause the elastic impact of the contact surface to generate an acoustic emission signal. This signal contains a wealth of rubbing information, so acoustic emission can be used to monitor and Diagnose rolling bearing faults.

4. Vibration signal detection

FAG rolling bearing fault detection simple diagnosis method using rolling bearing vibration signal analysis fault diagnosis method can be divided into simple diagnosis method and precise diagnosis method. The purpose of simple diagnosis is to preliminarily judge whether the rolling bearing that is classified as the object of diagnosis is malfunctioning; the purpose of precise diagnosis is to determine the fault category and cause of the bearing that is considered to be malfunctioning in the simple diagnosis. The following mainly introduces several methods of simple diagnosis:

(1) Amplitude value diagnosis method

The amplitude value mentioned here refers to the peak value XP, the mean value X (for simple harmonic vibration, the average value within half a period, for bearing shock vibration, the average value after absolute value processing) and the root mean square value (effective value) Xrms . This is the simplest and most commonly used diagnostic method. It is diagnosed by comparing the measured amplitude value with the value given in the criterion. The peak value reflects the maximum value of the amplitude at a certain moment, so it is suitable for fault diagnosis with instantaneous impact such as surface pitting damage. The average value used for diagnosis is basically the same as the peak value. Its advantage is that the detected value is more stable than the peak value, but it is generally used in the case of higher speed (such as 300r/min or more). The root mean square value is averaged over time, so it is suitable for fault diagnosis where the amplitude value changes slowly over time like wear.

(2) Probability density diagnosis method

The probability density curve of the amplitude of the trouble-free rolling bearing is a typical normal distribution curve; and once a failure occurs, the probability density curve may appear skewed or scattered.

(3) The kurtosis coefficient diagnosis method

A non-faulty bearing whose amplitude satisfies the normal distribution law has a kurtosis value of about 3. With the emergence and development of faults, the kurtosis value has a trend similar to the crest factor. The advantage of this method is that it has nothing to do with the bearing speed, size and load, and is mainly suitable for the diagnosis of pitting corrosion faults.

(4) Form factor diagnosis method

Crest factor is defined as the ratio of peak to average (XP/X). This value is also one of the effective indicators for simple diagnosis of rolling bearings.

(5) Crest factor diagnosis method

The crest factor is defined as the ratio of the peak value to the root mean square value (XP/Xrms). The advantage of this value for simple diagnosis of rolling bearings is that it is not affected by bearing size, speed and load, nor is it affected by changes in sensitivity of primary and secondary instruments such as sensors and amplifiers. This value is suitable for the diagnosis of pitting faults. By monitoring the trend of XP/Xrms value over time, it is possible to effectively predict the failure of rolling bearings early and reflect the development trend of the failure. When the rolling bearing is fault-free, XP/Xrms is a small stable value; once the bearing is damaged, an impact signal will be generated, and the vibration peak value will increase significantly, but the root mean square value has not increased significantly at this time. Therefore, XP/Xrms increases; when the fault continues to expand and the peak value gradually reaches the limit value, the root mean square value begins to increase, and XP/Xrms gradually decreases until it recovers to the size when there is no fault.

Through the application of the above detection methods on the key equipment FAG bearing components to track and detect their operating conditions, the hidden dangers of the equipment bearing parts can be effectively diagnosed, early prevention can be made to ensure the normal use of the equipment.