Emergence of low cost, low power sensors and connectivity options has made smart manufacturing possible like never before.
Case Study: Machine health monitoring using automated vibration monitoring
As machines are subjected to wear and tear it is necessary either to apply regular, and possibly redundant, preventative maintenance program or monitor their health periodically. A preventative maintenance program contract is given to an agency who will send its personnel periodically to monitor vibration parameters periodically. The approach is very costly as the company has to bear the cost and travel of personnel. Besides, the data monitoring is not continuous leading to high chances of failure and unpredictability.
Machines have permanently mounted sensor and RF connectivity modules. Sensors will monitor parameters such as vibration and temperature continuously and the information is sent to factory cloud gateway using BLE or RF subGhz. The sensors and RF connectivity modules are very low power to be even powered by battery. The data is sent to the cloud from gateway for analytics and FFT analysis.
The analysis of vibration signature of the machine enable to detect greatly in advance various type of fault or improper use such as load balance, misalignment, bearing defect, gear mesh etc.
Role of Sensors in making Industry Smart
Accelerometer is used to provide the acceleration which the Industrial machines are subjected to in all three axis X, Y and Z. It also determines the tilt angle of machines or robotic arm. If the machine is stationary in horizontal position then its X and Y axis will give 0g output whereas z-axis will give 1g output. 1g is the gravity which is experienced by every object on earth. If the machine rotates by 90deg on X axis then X and Z will give 0g and Y axis will start giving 1g. During the tilt X, Y and Z will give output which lies between 0 and 1g. The values can then be applied to trigonometry formulas to arrive at tilt angle of the machine.
Accelerometer are also used to give linear acceleration in horizontal and vertical direction. This data can be used to calculate velocity, direction and even rate of change of altitude of the machine.
Accelerometer is also used to detect the vibration which the machine is experiencing. When an accelerometer is mounted on motor it can give critical input to detect the type of fault. The frequency of fault caused by motor balance, bearing defect and gear mesh are different from one another. This information can be used to predict the maintenance requirement of motor.
Gyroscope sensor detects angular velocity in three axis. So it can detect rate of change of angle in pitch, roll and yaw. The change in angle information is used to provide stability to machine and to prevent it from wobbling. The information from gyroscope is fed to motor control drivers to control the speed of motors dynamically to provide the stability to machines or robotic arms. Gyroscope also ensure that machines or robotic arms rotate at exact angle which is expected by user controls.
Magnetic compass as the name suggests gives the sense of direction to the machine or robotic arm. It gives data of magnetic field in three X, Y and Z which the device is subjected to. This data is then fed into algorithms in the microcontroller to give heading angle w.r.t magnetic north. This information is then used to detect geographical directions.
To get accurate direction the magnetic data should be complemented by tilt angle data from the accelerometer. The tilt data along with magnetic data will then be used to calculate accurate direction.
A magnetic compass is very sensitive to hard iron, soft iron or angle of operation. Hard iron is the presence of hard permanent ferro-magnetic material in the vicinity of sensor. It creates a permanent shift in compass reading. Soft iron is the presence of weak ferro-magnetic material, circuit traces etc. It create a variable shift in the sensor reading. So a magnetic sensor calibration algorithm is needed to filter out these anomalies. It is important for the algorithm to do fast calibration with minimum effort by the user.
A barometer working principle is to convert atmospheric pressure into altitude. Pressure sensor can detect earth’s atmospheric pressure. The data from Barometer helps in machine or robotic arm navigation and achieve desired altitude. Very good estimation of ascend and descend speeds is vital for many machines including robots. STMicroelectronics has introduced a new pressure sensors, the LPS22HD, with 200Hz of data rate to address this requirement of altitude estimation.
The Humidity sensor can detect humidity parameter which can be used at weather station, condensation level monitoring, air density monitoring and gas sensors measurement correction.