For every physical parameter, e.g. temperature, pressure, lighting, humidity, etc. there’s an associated sensor that detects the value and transmits it to a connected system, which in recent years has been some form of electronics (RTUs), via a wireless or wired medium. Two physical parameters in particular hold great importance in the monitoring, control and automation of systems, i.e. Temperature and Vibration.
The market is flooded with various types of temperature and vibration sensors, and for good reason, since these two physical quantities are enough to allow engineers or specialists to judge the condition of a machine/locality/process. In addition to providing valuable insights into the process they are monitoring, the information provided by these sensors can be used for Predictive Maintenance which is a vital aspect of Industrial Automation. An array of temperature and vibration sensors installed within a plant floor can be tied with a Big Data installation and bring Prescriptive functions to the table.
The QM42 is a two-in-one, Vibration and Temperature Monitoring sensor that can provide physical measurements with a high degree of accuracy. Capable of detecting dual-axis vibration, the sensor is housed within a robust IP67-rated zinc alloy body allowing it to function in harsh environments. It is available in both Wireless and Wired models so that choice can be made according to the on-field requirement.
The QM42VT is ideal for monitoring a machine’s health. Its functionality is highlighted by its ability to measure RMS velocity, giving engineers timely visibility of any problems before they become too severe and result in downtime. When paired with Banner’s wireless node, it can be used to provide local indication, wirelessly send the reading to a central server, or send the data to a gateway for further processing. Typical machines that the sensor can monitor include:
The QM42’s feature set doesn’t only appeal on paper; the product has proved its mettle through successful installations within various systems.
Any commercial building, be it a high rise or otherwise, is usually installed with rooftop air handling units as part of the HVAC. Large overhead cranes are typically employed for their installation. As they are installed on rooftops, it is difficult to keep a regular check on them, especially if they are installed in a region where weather conditions can change abruptly. If for any reason, failure occurs the results can be damaging to the entire building. In addition, if any minor fault creeps into the units for an extended period of time, they can even face permanent damage, which may require complete replacement. This can add up the labor and procurement cost.
Predictive maintenance can be employed through the use of temperature and vibration sensors that can prevent disruption of operations and avoid complete failure by providing real-time insights into the condition of each unit.
A QM42 can be connected to a wireless node can be mounted onto the fan motors, collecting continuous vibration data. This is transmitted onto a Wireless Controller from where a comparison can be made against user-defined setpoints. If the values exceed the threshold values, the customer can be notified through email or text messages, engaging the concerned building management teams. This solution can also be extended to provide real-time information to an HMI that can accumulate data over time and help schedule maintenance activity well before any fault can develop.
Exhaust fans are used in major industrial production units to create negative airflow, providing a route to harmful fumes out of the plant floor. This is necessary to ensure workplace safety and to meet the necessary safety regulations.
These exhaust fans are installed in hard-to-reach places and therefore stoppages are extremely challenging to identify in time. If a fault develops and failure occurs, the result can affect the workplace and result in a loss of productivity. Furthermore, the repair procedures may delay production processes even further due to the unavailability of the required tools and manpower on-site.
A QM42 sensor unit mounted on fan motors can collect continuous vibration data, transmitting it to a wireless controller that runs a machine learning algorithm. The information can be sent over to the cloud, and be compared to set thresholds, in response to which alarms can be triggered. In this case, the nature of the collected data can be studied to determine the exact cause of failure. For instance, a fault in the bearings would have a different vibration signature compared to a fault in any other component. The following chart explains the various faults and their effect on the vibration data.
Unbalanced cutting heat and spindle bearing wear on high-speed profiling machines can lead to unplanned downtime and loss of productivity. This is particularly true for wood trim profiling machines with high-speed spindles where chipped or worn knives can lead to excess product waste along with downtime.
A vibration sensor mounted perpendicular to the profiler shaft can sense unbalanced knife position, misalignment, and bearing wear & tear. A QM42 vibration sensor can collect the spindle vibration values, transmitting them to a controller where actions can be executed after comparisons with defined thresholds.
Machine Learning plays a great role in this application as vibration sampling can be performed to allow easy and early identification of faults. In addition, multi-colored indicator lights can be used for quick rectification alerts, with a distinct color being used to represent a specific fault. This can speed up maintenance times and allow production to be kept at a maximum.
It is quite evident from the nature of the practical applications above that the use of the QM42VT or any other sensor of similar design and features, isn’t limited to that of monitoring. Through the transmission of real-time data onto a Wireless Controller, predictive maintenance can be put to use to allow precise fault detection rather than giving general maintenance alerts. This sits perfectly with the futuristic framework of a Smart Factory/Industry 4.0 and can be used as basis for further expansion of the plant floor in terms of sensory sophistication.
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