Vibration detection of industrial equipment has become a core component of predictive maintenance. The changes in vibration signals can reflect potential faults such as bearing wear, abnormal gear meshing, and rotor imbalance. MEMS (Micro Electro Mechanical Systems) sensors, with their advantages of miniaturization, high sensitivity, and low cost, are gradually replacing traditional piezoelectric sensors and becoming the mainstream technology for vibration detection. The following introduces the main applications and technical characteristics of MEMS sensors in industrial equipment vibration detection.
(1) Monitoring of rotating machinery in industrial equipment
For industrial equipment such as motors, pumps, fans, compressors, gearboxes, generators,and turbines, MEMS vibration sensors can detect vibrations caused by uneven mass distribution in rotating components, as well as vibrations resulting from misaligned shaft centerlines at couplings (including parallel misalignment and angular misalignment). For bearing faults, MEMS vibration sensors detect incipient damage in rolling or sliding bearings (such as pitting, spalling, cracks, and wear).
(2) Condition monitoring and predictive maintenance
MEMS vibration sensors have small size and low power consumption, making them ideal for installation on critical equipment for continuous vibration data acquisition and achieving online status monitoring. By analyzing the trend changes, spectral characteristics (such as fault characteristic frequencies), envelope analysis, etc. of vibration signals, early warning of equipment failures can be provided.
(3) Shock and transient event detection
MEMS accelerometers have wideband response (DC response) characteristics and can detect events such as impact, collision, and transient vibration caused by valve opening and closing, which may cause damage to the equipment or indicate potential problems.
The ultra-low cost of MEMS sensors is the most critical factor driving their large-scale deployment. The price is much lower than traditional industrial grade vibration sensors, making it economically feasible to deploy a large number of sensors on a single device or multiple measurement points. The extremely low power consumption of MEMS sensors makes them highly suitable for battery powered wireless sensor network applications, enabling long-term maintenance free operation. MEMS sensors are small in size and light in weight, with almost no load effect (mass effect) on the measured object. They are flexible in installation methods such as bonding and magnetic attraction, making them particularly suitable for small devices or space limited scenarios.
The high-frequency response limitation of MEMS sensors is the main limitation of MEMS sensors in the field of vibration detection. Traditional piezoelectric sensors easily cover the 10kHz or even higher frequency range (such as 40kHz), while industrial grade MEMS sensors typically achieve a flat response in the 3kHz-10kHz range. This weakens the ability to detect early failures of ultra high speed bearings (whose fault characteristic frequency may be high) or high-frequency components of gear meshing, and requires careful selection of sensor models based on the characteristic frequency range of the tested equipment. In addition, standard consumer or industrial grade MEMS sensors typically operate at temperatures ranging from -40 ° C to+85 ° C or+105 ° C. For certain industrial environments (such as near engines, turbines), specialized high-temperature MEMS (up to+125 ° C or even higher) or insulation measures may be required. Piezoelectric sensors typically have a wider temperature selection range.
The MEMS vibration sensor ACM-1000 produced by Micro-Magic Inc is designed according to industrial standards and uses digital filtering technology to effectively reduce measurement noise and improve measurement accuracy. Suitable for multiple fields such as vibration testing, impact testing, shock testing, etc.
The ACM-1000 can directly output the three-axis vibration velocity, angle, amplitude (displacement), frequency, and temperature of an object, and determine whether the measured object (bridge, fan, rotating machinery bearing vibration measurement and real-time monitoring) is damaged, making it convenient for users to analyze data. For example, machine failures caused by shaft system failures (blade wear, dynamic imbalance, poor alignment), bearing failures (bearing damage, poor lubrication, bearing collision, bearing looseness), transmission failures (gear wear, belt wear, coupling wear, gear pitting and peeling), etc., can be detected in advance by vibration sensors to issue alarms, preventing the machine from continuing to work under adverse conditions and causing damage.
ACM-1000 Performance Indicators
Parameter |
Item |
ACM-1000 |
Measuring axis |
|
X、Y、Z(optional) |
Accuracy |
Vibration velocity |
1mm/s |
Vibration angle |
0.001°/s |
|
Vibration amplitude |
0.001mm |
|
Vibration frequency |
1Hz |
|
Temperature Compensation |
-40 ~ +85℃ |
|
Range |
Vibration velocity(0-50mm/s),Vibration angle(0 ~ 180°) |
|
Vibration amplitude(displacement 30mm),Vibration frequency(1~100Hz) |
||
Bandwidth(3DB) |
500HZ |
In addition, Micro-Magic Inc has also launched the ACM-100, ACM-200, and ACM-300 series high-precision accelerometer products according to different application scenarios, suitable for multiple industrial fields such as vibration testing, impact testing, fatigue monitoring, and prediction. Facilitate customers to flexibly configure according to different application scenarios.
MEMS sensors are revolutionizing the field of industrial equipment vibration detection due to their disruptive cost advantages, low power consumption, small size, and ease of digital integration. It greatly reduces the threshold for condition monitoring and predictive maintenance, making continuous monitoring possible on a wider range of devices and more measurement points, especially in vibration analysis in the mid to low frequency range (such as unbalance, misalignment, early bearing failure, looseness, etc.) and the construction of large-scale wireless monitoring networks.
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