Enterprise power generation is a dynamic production process. The monitoring equipment operation can directly reflect the production capacity and sustainability of the enterprise, providing the most powerful data guarantee for the enterprise power generation plan. At present, domestic equipment monitoring technology is divided into many types according to the type of monitoring, such as temperature monitoring, humidity monitoring, vibration monitoring, etc. The main monitoring methods include temperature and humidity recorders, single-chips, video, fiber optics, rotating machinery, etc., but the above monitoring methods exist. Different levels of defects, and industrial IoT technology can effectively complement the above monitoring methods with its many advanced technologies.
Industrial IoT technology is a collection of advanced technologies. Device monitoring mainly involves radio frequency identification technology. RFID sensing devices are used as data acquisition devices. The current information of device operation is obtained by wireless radio frequency and transmitted to data through wired networks. The processing system extracts the required device status information through intelligent analysis of the data.
At present, domestic equipment monitoring adopts the combination of RFID and wireless or wired transmission technology to ensure the timeliness and accuracy of data. The collection of real-time data can be graphically displayed in the data processing system, increasing readability and making the operator more intuitive and clear. At the same time, deep accumulation of accumulated data can be carried out to screen and analyze production equipment that may or may have problems, avoiding safety accidents in the production process and directly affecting the production efficiency of the enterprise. After screening the analyzed data, it can provide an effective data reference for the company's planning in the later stage, provide the best production and maintenance plan, and reduce the expenditure cost in the management and maintenance process.
——Application of Industrial Internet of Things in the safety monitoring of power enterprise personnel.
China's power system is currently in the stage of economic transformation. The changes in the structure of employees and the movement of personnel are accelerating, while the safety training and education are relatively lagging behind. The safety skills and self-protection awareness of employees are poor, and they cannot meet the requirements of safe production, and further increase safety production management. The difficulty is a "sensitive area" in business management. Although the current power companies have adopted a variety of management tools, such as video real-time monitoring and the development of safety production regulations, it is still unable to effectively prevent the occurrence of personnel safety accidents. Personnel safety accidents are things that power companies are reluctant to happen and do not want to see. However, there is still no effective means to monitor them. They can only be monitored and recorded through conventional means such as video surveillance, rules and regulations, and warning signs. The functions of preventive alert and automatic alarm are realized. With the advantages of industrial IoT technology, the safety monitoring of personnel based on industrial Internet of Things technology is bound to become a development trend.
The personnel security monitoring based on industrial Internet of Things technology is to realize the work, activities and monitoring of personnel in the area through the sensing network formed by various sensing devices such as video, infrared and RFID. At the same time, the collected text and image data are intelligently analyzed. The dangerous behaviors are discriminated and alarmed to reduce the casualties of the personnel. At the same time, video and RFID are used to assist in identifying the working conditions of the personnel and improving the management ability of the enterprise.
——Application of industrial Internet of Things in daily work inspections of power companies.
The “Twelfth Five-Year Plan†for safety production emphasizes “responsibility is in place, measures are in place, investment is in place, and supervision is in place†to prevent and contain major accidents, and it is clear in the main tasks that key industries such as electric power need to establish a sound safety monitoring system. As a key area of ​​concern for power companies, their safety and security work requires not only detailed rules and regulations, but also various daily links. Daily inspection is the most basic equipment inspection method in the enterprise, and it is also the most commonly used detection method for equipment failure and aging. However, what is counterproductive is that when the daily inspection system is often implemented, there will always be problems in which the implementation is not in place and the detection is not in place, resulting in constant “small problems†in the equipment, which increases the unnecessary production costs of the enterprise. At present, during the inspection, the equipment inspector only uses paper, pen and eyes to track and record the status data of the equipment. This is not only time-consuming and labor-intensive, but also the accuracy of the recorded results is suspected. Data is still not available for analysis and judgment, resulting in wasted resources. At the same time, this kind of inspection method is unsupervised, it is impossible to judge whether the inspection work is in place, and the obtained data is not authentic, which needs to be assisted and controlled by means of automated and high-precision equipment.
Based on the radio frequency identification technology and the video image processing technology, the specified equipment index parameters and environmental index parameters can be extracted according to the scene situation for analysis, and the equipment index and the environmental index parameter that do not meet the requirements are determined, and the data exceeding the standard is passed in time. The processing system alerts you to the maintenance personnel and can collect statistics on the accumulated data to provide a data reference for developing an effective annual maintenance plan.
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