What are the best practices for using acoustic sensors to monitor lubrication conditions? (original) (raw)

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Acoustic sensors are devices that measure sound waves and vibrations in machines and equipment. They can be used to monitor lubrication conditions, such as the presence and quality of oil or grease, and detect signs of friction, wear, and damage. Lubrication is essential for reducing friction, heat, and wear in moving parts, and optimizing it can improve performance, efficiency, and reliability. In this article, you will learn what are the best practices for using acoustic sensors to monitor lubrication conditions, and how they can help you prevent breakdowns, save costs, and extend the life of your assets.

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Choose the right sensor type

There are different types of acoustic sensors, such as microphones, piezoelectric transducers, ultrasonic sensors, and acoustic emission sensors. Each type has its own advantages and limitations, depending on the frequency range, sensitivity, noise rejection, and installation requirements. For monitoring lubrication conditions, you should choose a sensor type that can capture the relevant sounds and vibrations of your equipment, such as the squeaks, clicks, and knocks that indicate insufficient or poor lubrication. You should also consider the environmental factors, such as temperature, humidity, dust, and interference, that may affect the sensor performance and durability.

• Train your system on good operative bad or dry operation, the friction sounds are different, then set up a machine learning function that identifies good and just reports on once an hour as good, and then discords and anomalies to record and report to server side. Good is edge.

Install the sensor correctly

The location and orientation of the sensor can have a significant impact on the quality and accuracy of the data. You should install the sensor as close as possible to the source of the sound or vibration, such as the bearing, gear, or shaft, and avoid any obstacles or barriers that may block or distort the signal. You should also align the sensor with the direction of the sound or vibration, and secure it firmly to avoid any movement or loosening. You should follow the manufacturer's instructions and recommendations for the best installation practices, and test the sensor functionality and calibration before using it.

• Sound travels through the air efficiently so location of sound sensors is not so important to get against the source. You could deploy close listeners and far listeners.

Set the appropriate parameters

The parameters of the sensor, such as the sampling rate, frequency range, amplitude threshold, and signal processing, determine how the data is collected and analyzed. You should set the parameters according to the characteristics and specifications of your equipment, and the lubrication condition indicators that you want to monitor. For example, you may want to set a higher sampling rate and frequency range for high-speed or high-frequency equipment, or a lower amplitude threshold and signal processing for low-level or intermittent sounds or vibrations. You should also compare the baseline data with the current data to identify any changes or anomalies that may indicate lubrication problems.

• Use machine learning, fast Fourier transform and principal component analysis models here, there are probably loads more to look at, let the models find the good Vs bad, discord and anomaly.

Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

• We tested this inside the large port side quay cranes in Felixstowe. One point not covered here is the volume of data created, what if you use 100 x monitoring sensors on a site, what does your data look like?

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