Mar. 23, 2024
What do you know about the five major fault analysis methods and diagnostic tips? Let me take you to see it today.
Abnormal rotation sound detection and analysis is an analysis method that uses auscultation to monitor the working status of the bearing. Commonly used tools are long screwdrivers with wooden handles, or hard plastic tubes with an outer diameter of about 20mm. Relatively speaking, using electronic stethoscopes for monitoring is more conducive to improving the reliability of monitoring. When the bearing is in normal working condition, it runs smoothly and briskly without stagnation. The sound produced is harmonious and noise-free. You can hear a uniform and continuous "buzzing" sound, or a lower "buzzing" sound. The bearing faults reflected by abnormal sounds are as follows.
This sound is generated by the rolling elements rotating in the inner and outer rings, and includes irregular metal vibration sounds that are independent of the speed. Generally, the amount of grease in the bearing is insufficient and should be replenished. If the equipment is shut down for too long, especially at low temperatures in winter, the bearings will sometimes make a "sizzling" sound during operation, which is related to the smaller radial clearance of the bearings and the smaller penetration of the grease. The bearing clearance should be adjusted appropriately and new grease with a larger penetration should be replaced.
This sound is caused by scratches, grooves, and rust spots on the rolling elements and the inner and outer ring raceways. The period of sound is proportional to the rotation speed of the bearing. Bearings should be replaced.
This sound is caused by iron filings, sand and other impurities falling into the bearing. The intensity of the sound is small and has nothing to do with the number of revolutions. Bearings should be cleaned, re-greased or oil changed.
This sound is generally related to the loose fit between the inner ring of the bearing and the shaft or the loose fit between the outer ring and the bearing hole. When the sound intensity is high, the matching relationship of the bearings should be checked and any problems should be repaired in time.
Bearing vibration is very sensitive to bearing damage, such as peeling, indentation, rust, cracks, wear, etc., which will be reflected in the bearing and vibration measurements. Therefore, the size of the vibration can be measured by using a special bearing vibration measuring instrument (frequency analyzer, etc.), and the specific abnormality can be inferred from the frequency distribution. The measured values vary depending on the operating conditions of the bearing or the installation position of the sensor. Therefore, it is necessary to analyze and compare the measured values of each machine in advance to determine the judgment criteria. There are many detection and diagnosis technologies for rolling bearing faults, such as vibration signal detection, lubricating oil analysis and detection, temperature detection, acoustic emission detection, etc. Among various diagnostic methods, diagnostic technology based on vibration signals is the most widely used. This 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, crest 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; ·Precision diagnosis Various modern signal processing methods are used to determine the fault type and cause of the bearing that is considered to be faulty in simple diagnosis.
In the process of using vibration to conduct simple diagnosis of rolling bearings, it is usually necessary to compare the measured vibration value (peak value, effective value, etc.) with a certain predetermined judgment standard. According to whether the measured vibration value exceeds The limits given by the standard are used to determine whether the bearing is faulty and whether further precision diagnosis is needed. The judgment criteria used for simple diagnosis of rolling bearings can be roughly divided into three types:
(1) Absolute judgment standard: It is an absolute value used to judge whether the measured vibration value exceeds the limit;
(2) Relative judgment standard: The vibration of the same part of the bearing is measured regularly and compared in time. The vibration value when the bearing is fault-free is used as the standard. It is based on the ratio of the actual measured vibration value to the reference vibration value. criteria for making a diagnosis;
(3) Analogy judgment standard: It is a standard that tests the vibration of several bearings of the same model at the same part under the same conditions, and compares the vibration values with each other for judgment.
The absolute judgment standard is a standard established based on the prescribed detection method, so attention must be paid to its applicable frequency range, and vibration detection must be carried out according to the prescribed method. There is no absolute judgment standard that applies to all bearings. Therefore, absolute judgment standards, relative judgment standards and analogy judgment standards are generally used in order to obtain accurate and reliable diagnostic results.
Simple diagnosis mainly includes the following methods:
The amplitude value mentioned here refers to the peak value XP, the mean value
This is the simplest and most commonly used diagnostic method, which is diagnosed by comparing the measured amplitude value with the value given in the judgment standard.
·The peak value reflects the maximum amplitude at a certain moment, so it is suitable for fault diagnosis with instantaneous impact such as surface pitting damage.
·The diagnostic effect of the average value is basically the same as that of the peak value. Its advantage is that the detection value is more stable than the peak value, but it is generally used when the rotation speed is higher (such as above 300r/min).
·The root mean square value is averaged over time, so it is suitable for fault diagnosis where the amplitude value changes slowly with time, such as wear.
The probability density curve of the amplitude of a fault-free rolling bearing is a typical normal distribution curve; but once a fault occurs, the probability density curve may be skewed or dispersed.
A fault-free bearing whose amplitude satisfies the normal distribution law has a kurtosis value of approximately 3. With the occurrence and development of faults, the kurtosis value has a similar changing trend to the crest factor. The advantage of this method is that it has nothing to do with the rotation speed, size and load of the bearing, and is mainly suitable for the diagnosis of pitting corrosion faults.
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.
Crest factor is defined as the ratio of peak value to 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 diagnosing pitting corrosion faults. By monitoring the changing trend of XP/Xrms values over time, rolling bearing faults can be effectively predicted early and the development and changing trends of faults can be reflected.
·When the rolling bearing has no fault, XP/Xrms is a small stable value;
·When the bearing is damaged, an impact signal will be generated and the vibration peak value will increase significantly, but the root mean square value will not increase significantly at this time, so 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 returns to the size without a fault.
The vibration frequency components of rolling bearings are very rich, including both low-frequency components and high-frequency components, and each specific fault corresponds to a specific frequency component. The task of precision diagnosis is to separate specific frequency components through appropriate signal processing methods to indicate the existence of specific faults. Commonly used precision diagnostics include the following.
Low-frequency signals refer to vibrations with frequencies below 8kHz. Generally, acceleration sensors are used to measure the vibration of rolling bearings, but the vibration speed is analyzed for low-frequency signals. Therefore, the acceleration signal must be converted into a speed signal by an integrator after passing through a charge amplifier, and then pass through a low-pass filter with an upper cutoff frequency of 8 kHz to remove the high-frequency signal. Finally, the frequency component is analyzed to find the characteristic frequency of the signal. diagnosis.
The frequency range of the intermediate frequency signal is 8~20kHz, and the frequency range of the high frequency signal is 20~80kHz. Since acceleration can be directly analyzed for mid- and high-frequency signals, after the sensor signal passes through the charge amplifier, the low-frequency signal is directly removed by a high-pass filter, then demodulated, and finally frequency analysis is performed to find the characteristic frequency of the signal.
The temperature of the bearing can generally be estimated from the temperature outside the bearing chamber. It is more appropriate if the oil hole can be used to directly measure the temperature of the bearing outer ring. Usually, the temperature of the bearing begins to rise slowly as the bearing operates, and reaches a stable state after 1 to 2 hours. The normal temperature of bearings varies depending on the machine's heat capacity, heat dissipation, rotation speed and load. If the lubrication and installation are improper, the bearing temperature will rise sharply and abnormally high temperatures will occur. At this time, the operation must be stopped and necessary preventive measures must be taken.
High temperatures often indicate that the bearing is in an abnormal condition. High temperatures are also harmful to bearing lubricants. Sometimes bearing overheating can be attributed to the bearing's lubricant. If the bearing is rotated continuously for a long time at a temperature exceeding 125°C, the service life of the bearing will be reduced. Causes of high-temperature bearings include: insufficient or excessive lubrication, impurities in the lubricant, excessive load, bearing damage, insufficient clearance, high friction caused by oil seals, etc.
Therefore, continuous monitoring of bearing temperature is necessary, whether measuring the bearing itself or other important parts. If operating conditions remain unchanged, any temperature change may indicate a malfunction. Regular measurement of bearing temperature can be done with the help of a thermometer, such as the SKF digital thermometer, which can accurately measure bearing temperature and display it in units of °C or Fahrenheit. The importance of bearings means that when they are damaged, it will cause the equipment to shut down. Therefore, it is best for such bearings to be equipped with temperature detectors. Under normal circumstances, bearings will have a natural temperature rise immediately after lubrication or relubrication that lasts for one or two days.
The lubricant analysis method uses ferrography analysis technology, which is a method particularly suitable for identifying and predicting rolling fatigue. A part of the lubricating oil of the rolling bearing is extracted as an oil sample, and a high gradient magnetic field is used to deposit the solid foreign matter contained in the oil sample flowing through the magnetic field on a glass sheet in proportion to its size, so that the shape, size, color, and material of the foreign matter particles can be observed. , so that the type of wear can be clearly identified, the operating status of the machine can be predicted, and hidden dangers can be discovered in time. In principle, ferrography technology is mainly aimed at identifying strong magnets such as steel, but it also has excellent identification capabilities for non-ferrous metals such as copper, sand, organic matter, seal debris and other foreign matter. When steel-like spherical particles with a diameter of 1 to 5 μm appear in the oil sample, it is certain that the bearing has begun to develop fatigue micro-cracks. When fatigue spalling particles with a length to thickness ratio of 10:1 appear in the oil sample, and the length is greater than 10 μm, abnormal fatigue wear in the bearing has begun. When the length is greater than 100 μm, the bearing has failed. The third type of fatigue debris is fatigue flakes with a length-to-thickness ratio of 30:1, with a length of 20 to 50 μm, and the flakes often contain cavities. At the onset of fatigue, the number of such flakes will increase significantly, which together with spherical particles can be a sign of the onset of fatigue.
The principle of acoustic emission detection technology is that when a material is deformed or cracked due to 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 using the acoustic emission signals to infer the source of acoustic emission is called acoustic emission detection technology. It uses the phenomenon that the particles inside the material release strain energy in the form of elastic waves due to relative motion to identify and understand the material. or structure internal state.
Acoustic emission signals include burst type and continuous type. The burst acoustic emission signal consists of pulses that are different from the background noise and can be separated in time; the single pulses of the continuous acoustic emission signal are indistinguishable. In fact, continuous acoustic emission signals are also composed of a large number of small burst signals, but they are too dense to be distinguished.
When rolling bearings are not operating properly, both sudden and continuous acoustic emission signals may be generated. The relative motion between the contact surfaces of the bearing components (inner ring, outer ring, rolling elements and cage), the Hertzian contact stress caused by friction, and surface cracks, wear, indentations, etc. caused by failure, overload, etc. Failures such as grooving, occlusion, surface roughness caused by poor lubrication, surface hard edges caused by lubrication contamination particles, and pitting corrosion caused by current passing through the bearing will all produce sudden acoustic emission signals.
Continuous acoustic emission signals mainly come from global failures caused by oxidative wear on the bearing surface due to poor lubrication (such as failure of the lubricating oil film, infiltration of contaminants in the grease), excessive temperatures, and frequent local failures of the bearings. These factors cause a large number of sudden acoustic emission events in a short period of time, thus generating continuous acoustic emission signals.
During the operation of a rolling bearing, its failure (whether it is surface damage, crack or wear failure) will cause elastic impact on the contact surface and produce an acoustic emission signal. This signal contains rich friction information, so acoustic emission can be used to monitor and Diagnose rolling bearings.
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