Intelligent Expert System-Rotary Kiln Machine

Following problems exist in the manual operation of rotary kiln machine production:

• For the process control requirements, the operator's operation experience is uneven, and the operation mode is different, which cannot be strictly unified;

• They may bring emotions into their work, and their working state depends on their sense of responsibility;

• The mobility of operators is increasing year by year, and the staff training of operators is gradually emerging;

• With the development of society, the investment of enterprises to employees is increasing year by year;

• It is difficult for operators to observe the field data in real-time and deal with them in time.

The expert intelligent control system of rotary kiln is based on multivariable and large time-delay model predictive control algorithm. It adopts a variety of complex control technologies and is established on the basis of independent research and development of multivariable predictive control system modeling software, simulation software and operation management software. And the expert intelligent control system is based on the expertise and experience provided by the operator, with the help of computer control technology, simulation experts in the production process of each operation variable real-time intelligent process control.

The advantages of an expert intelligent control system of a rotating kiln are as follows:

It can improve the automation level of rotating kiln and ensure the long-term stable operation of rotary kiln.

Increase the service life of equipment, reduce the workload of operators and unnecessary losses caused by misoperation.

Realize the optimization control of coal consumption and power consumption in the production process to achieve the control requirements of energy-saving and emission reduction, stable production and quality.

The core technology of an expert intelligent control system includes the following aspects:

• Neural network technology: Imitating biological neurons, self-learning adjustment through online data collection;

• Model identification technology: Using the actual field data to establish a high-precision control model;

• Combined model predictive control algorithm: An effective control method for multivariable interaction and large time-delay systems;

• Fuzzy control technology: Based on the knowledge of experts, it is easy to design and suitable for the control of nonlinear, time-varying and pure delay systems;

Rotary kiln machine online vibration monitoring system:

Rotary kiln is the key equipment in the coal mining process line, and its normal operation is very important. In the long-term operation process, it is prone to various faults, and there are great hidden dangers. In addition, the traditional equipment management usually adopts the mode of preventive maintenance combined with spot inspection, which is based on time to prevent early failures and increase equipment reliability; Although preventive maintenance can reduce unscheduled downtime, it relies too much on the experience of on-site management personnel and lacks the support of real-time operation status data of equipment. As a result, the final maintenance decision is not based on the actual status of equipment. This mode may cause "under maintenance" and "over maintenance". However, the security system installed on-site for key units often lacks the diagnostic analysis function or is difficult to effectively use the diagnostic function. It can only find late faults, which will also bring risks to equipment operation and affect enterprise management level and equipment operation efficiency.

The online vibration monitoring system of rotary kiln continuously collects vibration data by setting vibration sensor and data acquisition card on the bearing of main motor, pinion and other transmission parts, and analyzes the collected data by fault diagnosis and analysis software and professional engineers to form equipment state conclusion. The online monitoring system can not only judge the current state of the equipment, but also roll to predict the future state of the equipment, realize the recording and tracking of each stage in the whole life cycle of the equipment, and realize the monitoring and prediction of power frequency fault, mechanical component damage, etc.

The value of building an online vibration monitoring system is as follows:

• Ensure continuous production and equipment safety

• Judge and predict the state of equipment

• Achieve predictive maintenance, reduce unexpected downtime and improve enterprise efficiency

• Help upgrade operation and maintenance mode