Zhejiang Special Motor Limited Company by Shares

New change of motor maintenance under the trend of Internet of things

Issuing time:2018-04-03 14:57

With the rise of the Internet of things, large data and AI technology, factory equipment ushered in a new change. More and more machines connect to the Internet to realize remote data monitoring and analysis. This scene has brought more relaxed and efficient work to the staff. However, many people are unfamiliar with this model. The blind follow up trend may not get the desired effect, so how do enterprises combine the Internet of things, big data, improve the value of the factory?

At present, the biggest application of the Internet of things in the industrial field is predictive maintenance. To ensure the continuous operation of the production line for 24 hours a long time, it is difficult to realize in the past, but today it can solve the equipment hidden trouble ahead of time by predictive maintenance, so as to prevent equipment failure.

Electric motor is the main force of today's industry. There are many motors used in various uses in the factory, such as lifting, stamping, handling, dust removal, drying and so on. The maintenance of motors has become an important item in factories. Especially in some harsh environments, users are more inclined to remote maintenance.

The decline in motor efficiency is the most common. If hundreds of motors in the factory have been reduced in efficiency, the impact on factory production is very large, and the risk of stopping is also possible. A motor failure in some production lines may cause the whole production line to be shut down. This downtime is very expensive.

In order to reduce unexpected downtime, factories will employ maintenance personnel. But the traditional maintenance method is also very expensive, because they have no better way to predict the future of the device, and still can not avoid downtime. Generally, the motor has the following maintenance methods:

After fault maintenance: meaning is to wait for the motor after failure to stop to maintain, this situation is usually damaged, the need to replace a motor, because it is not a simple thing to repair the motor at the site, this situation can only be changed first, ensure production can continue.

Preventive maintenance: in order to avoid the failure of the motor, the crew will maintain regularly according to the average running time of the motor. Usually out of safety considerations, maintenance is too early, and the parts are still in good condition and may be replaced, which does not guarantee that no new problems will occur after maintenance.

Condition monitoring and maintenance: usually, there will be some phenomena before the motor stops, such as noise, vibration and speed. The state monitoring and maintenance method is to monitor each motor, similar to the doctor stethoscope, and the maintenance personnel to determine if they need to be maintained after the diagnosis. Field inspection may be a dangerous task, and maintenance personnel should run anywhere in the factory.

With the development of Internet of things, these traditional maintenance methods will become the past. The factory will have one or more sensors for each motor. These sensors are connected to the control database to collect data of motor continuously. In the database, AI is used to learn each motor's behavior. When the motor deviates from the normal situation, it will generate alerts immediately.

This sensor based data collection is more accurate and thorough than any human detection, because many of the signs of the motor are difficult to identify with the eyes and ears, but the small changes in the device can be found through the Internet of things sensors.

The combination of the Internet of things and artificial intelligence can not only see the problem, but also scan and detect the possible problems that we call predictive maintenance. This way is very good to avoid the failure, and let the maintenance personnel know when the best maintenance time will not be too slow or too early. At the same time, according to the severity of the problem and alarm, we can even plan the downtime of the motor, so as to minimize the interference to the operation.

In factory operation, erroneous decisions or making too slow and too early decisions will bring a lot of resources and money to waste. The Internet of things helps users collect data that they haven't captured before, and learn and make better decisions through AI analysis.



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