Intelligent operation and maintenance management of the blower is an important part of industrial equipment management, and the use of sensor technology, data analysis and remote monitoring can achieve remote diagnosis, prediction and overhaul of the equipment, and improve the reliability and operational efficiency of the equipment.

First of all, in the operation of the blower, the installation of various sensors can monitor the equipment operation in real time, such as pressure, flow, vibration, shaft temperature and other data. These sensors can transmit the data to a data centre via a wireless network for data analysis and processing. Through the five levels of data-driven efficiency improvement, such as descriptive analysis, exploratory analysis, diagnostic analysis, predictive analysis and prescriptive analysis, in-depth analyses can be conducted on the operating status of the equipment, and potential problems can be detected in a timely manner.

Secondly, using data analysis technology, the operating data of the blower can be deeply mined and analysed to discover the potential problems and failure trends of the equipment. For example, excessive pressure, excessive flow, inlet filter clogging, rotating parts touching and other problems of the blower can be found through data analysis, and corresponding measures can be taken in a timely manner, such as lowering the pressure, lowering the flow, removing obstacles, shutting down the machine for inspection, and so on.

In addition, remote diagnosis and overhaul of the blower can be achieved through remote monitoring technology. For example, through the blower remote monitoring IoT platform, it is possible to monitor the operating status of the equipment in real time and remotely control and maintain the equipment. At the same time, through online monitoring of the electrical parameters of the blower, energy consumption can be accurately calculated, and reasonable maintenance strategies can be formulated with the monitoring data.

Finally, through intelligent operation and maintenance management, the reliability and operational efficiency of the equipment can be improved. For example, energy-saving transformation and operation adjustment through intelligent O&M system can effectively improve the operating efficiency of the blower. The maximum efficiency of the modified blower is 893%, and the shaft power can be reduced by 133%, which saves 580,000kW/h of electricity per year.

In summary, the use of sensor technology, data analysis and remote monitoring and other means can achieve intelligent O&M management of the blower and improve the reliability and operational efficiency of the equipment.