STUDY OF THE CURRENT STATE OF DEVELOPMENT OF CONTROL AND AUTOMATION SYSTEMS OF HYDRAULIC MACHINES

Abstract

Future hydraulic systems will heavily incorporate AI and ML, enhancing control precision and enabling predictive maintenance. AI-driven algorithms will increasingly be used for predictive maintenance, improving the reliability and lifespan of hydraulic systems. This integration will lead to smarter, more efficient operation, and extended equipment lifespans. The integration of IoT technology is crucial for real-time data collection and analysis, facilitating remote monitoring and control that leads to improved operational efficiency and maintenance management. The use of cloud platforms for data analysis and storage is likely to increase, enabling more sophisticated data processing and accessibility. Advanced sensors and predictive maintenance contribute significantly to safety by anticipating system failures. Reliability is also enhanced through reduced downtime and smarter maintenance schedules. The growing convergence of advanced robotics with hydraulic systems is steering these systems towards increased autonomy. Enhanced safety features will be a priority, driven by smarter sensors and control algorithms. The growing complexity of hydraulic systems underscores the need for specialized training and education in system design, maintenance, and operation. Future hydraulic machines are expected to be more customizable and flexible, with modular designs that cater to specific industry needs. A significant challenge is the adaptability of AI and ML models in dynamic, real-world conditions. Continuous learning methods are being developed to address this. In summary, the future of hydraulic machine control systems and automation looks towards greater intelligence, connectivity, efficiency, and adaptability. These trends will be underpinned by ongoing technological advancements, particularly in AI, ML, IoT, and sustainable practices.