Predictive maintenance of equipment in the field of wind power

Predictive maintenance of equipment in the field of wind power

Predictive Maintenance

Predictive Maintenance (PM) is one of the key innovations proposed by Industry 4.0. Based on continuous measurement and analysis, predictive maintenance can predict agency metrics such as the remaining life of machine parts. Key operational parameter data can aid decision making, determine the machine's operating status, and optimize machine maintenance timing.

Predictive maintenance evolved from the concept of 'state monitoring'. 'Status Monitoring' collects real-time information on the status of monitored parts; however, condition monitoring fails to proactively predict machine outages and wear and tear. Therefore, the emergence of predictive maintenance is a major turning point: more sophisticated sensors, a more efficient communication network, a powerful computing platform capable of processing large-scale data, and a random algorithm to compare data with the data pattern when the machine is in trouble. From this, we can identify, simulate and interpret the laws of machine operating parameters.

Predictive maintenance in the field of wind power

Wind power refers to the conversion of kinetic energy of wind into mechanical kinetic energy, and then the conversion of mechanical energy into electrical kinetic energy.

The wind is one of the energy sources without pollution. And it's inexhaustible and inexhaustible. For coastal islands, grassland pastoral areas, mountainous areas and highland areas where water is scarce, fuel-poor and inaccessible, wind power generation is suitable for local conditions, which is very suitable and promising. Offshore wind power is an important area for the development of renewable energy, an important force to promote wind power technology advancement and industrial upgrading, and an important measure to promote energy structure adjustment. China's offshore wind energy resources are abundant, and accelerating the construction of offshore wind power projects is of great significance for promoting coastal areas to control atmospheric haze, adjust energy structure and transform economic development mode.

But we still need to see the problem. Whether it is wind power on land or at sea, the installation location of wind turbines is in the wild and offshore, and the installation range of wind turbines is also very large. There is also a certain distance, not as concentrated as a traditional power station. In addition, the road conditions around the wind turbines are very poor, which leads to a problem that must exist in the process of wind turbine operation - maintenance and maintenance takes a long time and the efficiency is very low.

Maintenance work over the mountains

So how can we solve such a practical problem? Can we remoteen the work of overhaul? Can it be repaired only for problematic generators, thus reducing the amount of work and maintenance time?

of course can!

Predictive maintenance systems from ALPHA can help wind power plants solve this practical problem.

Based on ALPHA's huge cloud database and intelligent AI architecture, we can install wireless sensors on each wind turbine, collect real-time data such as vibration and temperature of the generator, and then input the data of each generator into the database for storage. . In the database, deep mining of the data that has been collected. Combined with ALPHA's unique intelligent AI architecture, it realizes the self-learning function of the machine, intelligently analyzes each collected data, and performs horizontal comparison with the data of our cloud database.

Our goal is to provide an intelligent warning of possible failures before the generator is about to have a problem. Combined with ALPHA's unique spare parts inventory management system, timely check the spare parts required for deployment and maintenance. Pre-aware and advance maintenance before the failure occurs.

And the only thing we need to do is this

The core of predictive maintenance expression is active maintenance, and natural systems are also intelligent and active. Even if it is unable to pay attention to the real-time analysis of the monitoring system, it will automatically push relevant warning information to the authorized personnel's mobile phone, and give the analyzed reference solution.

The value of predictive maintenance:

1

The data is collected in real time by the sensor, which reduces the workload of the human inspection. The normal operation of the generator does not need to be time-consuming to check;

2

The accuracy of the data collected by the sensor reduces errors caused by manual inspection, thereby reducing misjudgment of equipment failure;

3

Early warning of failures reduces the maintenance to be more targeted, reduces actual maintenance time, and improves efficiency;

4

Early warning of failure, reduced maintenance makes it more targeted, reduces the actual dimension combined with ALPHA spare parts inventory management system, greatly shortens maintenance preparation time, combined with intelligent AI, semester spare parts life cycle, also helps with minimum cost, minimum the spare parts inventory ensures the normal maintenance and operation of all generators.

How important is predictive maintenance in the strategic future?

Germany proposes a future strategic project for Industry 4.0, and the German engineering industry must take the lead in the definition, implementation and dissemination of predictive maintenance solutions to meet the tough challenges. Therefore, the German Mechanical Engineering Industry Association and the German Trade Fair Group , the German trade fair, have set "predictive maintenance" as one of the themes of this year's Hannover Industrial Exhibition.

It can be seen that the strategic height of predictive maintenance is absolutely unprecedented, and the benefits brought to industrial applications are unprecedented!

Alpha's monitoring and early warning system is perfect for such predictive maintenance. The monitoring and early warning plus spare parts inventory management system, the whole system is combined, truly realizes the predictive maintenance for the wind power generators, and reduces the maintenance workload, while improving the power generation efficiency and reducing the maintenance cost.

ALPHA has always been committed to making our partners' work easier and more economical with our advanced intelligent systems. The development of hardware sensors and intelligent analysis software systems comes from ALPHA's technical team!

For more information about Alpha's intelligent service cooperation, please contact us.