Digital intelligent control software

Application of Kotuo Electric Control System in Steel Pipe Diameter Expansion Lines

The automated steel pipe expanding line is a forming production line for straight-seam welded metal pipes. Its primary function is to reshape deformed and bent straight-seam steel pipes into uniform, straight round pipes. It is an essential piece of equipment for the oil and chemical industries used in the transportation of steel pipes.

The control system for the automated steel pipe expanding line has high requirements for response speed and positioning accuracy. The Kete electric control system, utilizing Siemens PLCs, servo drives, and the WINCC SCADA system, has been designed to create a real-time, dynamic control system. The system employs numerous motion control algorithms and trajectory planning algorithms, which can effectively enhance the production efficiency of the automated steel pipe expanding line.

I. System Architecture Design

1. Hardware Architecture

The automated steel pipe expanding line control system employs a Siemens S7-1500 PLC, which supports motion control process object functions and can optimize the positioning accuracy and response speed of the production line’s motion equipment.

The I/O substation system employs ET200SP distributed I/O modules, which are discretely arranged around various control points and actuator units throughout the system. Data exchange among these modules is conducted via a Profinet bus, enabling precise control and feedback from each module. This approach significantly reduces the length of signal control wiring, thereby helping customers save substantial costs and construction time.

2. Servo drive

The automated steel pipe expanding line control system utilizes the SINAMICS S120 drive system, adopting a multi-drive configuration with a shared DC bus. This allows the kinetic energy generated by Device A to be fed back via the DC bus to Device B as driving power, significantly reducing the overall energy consumption of the system and enabling substantial electricity cost savings for the customer each year. Meanwhile, the extensive use of servo drives has improved both the response time and execution accuracy of the system’s actuators, resulting in cycle-time optimization that exceeds the customer’s expectations.

3. Network Architecture

The system adopts a ring topology, enabling redundant communication functionality without increasing the number of network cables or costs. All devices within the system—such as PLCs, instruments, controllers, and servos—are uniformly equipped with Profinet bus interfaces, simplifying cable routing and significantly enhancing the system’s resistance to interference.

The system network is divided into three hierarchical layers based on functional purpose: the data layer, the control layer, and the instrumentation layer. The data layer is responsible for communicating with upstream systems—ERP and MES systems—and acquiring production schedules and process parameters via OPC UA. The control layer handles communication between controllers and remote I/O devices within the system. The instrumentation layer is responsible for data communication with field instruments, sensors, and downstream subsystems. These three network segments utilize distinct IP address ranges and are separated by VLANs, ensuring that while maintaining data exchange among the segments, they remain mutually independent. This approach not only reduces network load but also enhances communication stability.

4. Security Architecture

The system is configured with a three-tier managed switch and an industrial firewall, enabling internal-external network isolation and functional zone-based management. This effectively isolates network risks such as external viruses, DDoS attacks, and IP address conflicts, thereby ensuring the security of the system’s internal network.

II. Script Optimization and Application of the Difference Compensation Algorithm

1. Trajectory Discretization

Complex trajectories—such as circles or curves—are broken down into countless tiny straight-line segments (or curve segments), and the target trajectory is approximated by leveraging the synchronized motion of servo axes. For example, in the process of expanding and straightening steel pipes, it is necessary to uniformly expand the pipe circumference. By employing an interpolation algorithm, the circular trajectory can be decomposed into multiple tiny linear segments, and multi-axis coordination can then be used to achieve arc-shaped motion.

2. Multi-axis motion coordination

Real-time computation and distribution of the positions and velocities of multiple servo axes—such as the X, Y, and Z axes or rotary axes—are performed to ensure that each axis moves in synchronized fashion according to a specific ratio. In an expanding machine, as the die expands radially, it is simultaneously accompanied by axial movement. By using an interpolation algorithm to control the velocity ratio between the two axes, the machine can achieve an expanding motion along a helical trajectory.

3. Real-time error compensation

The actual positions of each axis are collected in real time via a feedback system (such as an encoder), and compared with the theoretical positions calculated through interpolation. Control parameters are dynamically adjusted to minimize motion errors and ensure trajectory accuracy.

4. Trajectory Planning and Parameter Matching

Based on the wall thickness and diameter specifications of the expanded-diameter component, the velocity profile of the interpolation algorithm—such as S-shaped acceleration and deceleration—is adjusted to prevent deformation of the pipe or wear on the die caused by motion shocks. For example, when expanding thin-walled pipes, the incremental velocity of interpolation is reduced and the density of trajectory points is increased, thereby enhancing the smoothness of the motion.

5. Optimization of variable management

By using UDTs (User-Defined Data Types), we can replace the traditional single-variable management approach with structured variables, thereby achieving reuse of variable structures. UDTs allow us to package related signals into a unified structure, enhancing data cohesion and making variable meanings clearer. Through template-based creation, we can quickly generate standardized data structures, reducing the need for repetitive definitions. UDT templates can be reused across different projects or program blocks—once defined, they can be referenced multiple times without further redefinition. Variables are associated via UDT templates, which reduces the risk of namespace conflicts and facilitates centralized management. When the UDT definition is modified, all related variables are automatically updated in sync, eliminating the need to manually adjust scattered variable declarations and significantly improving maintenance efficiency.

6. Dynamic Response Optimization

When the expanding machine encounters sudden changes in load—such as uneven hardness at pipe joint locations—the interpolation algorithm must, in conjunction with the PLC’s real-time interrupt function, swiftly adjust the motion parameters of each axis to prevent trajectory deviation. For example, by using the PLC’s high-speed input module to collect force sensor data in real time, when a sudden change in expanding force is detected, the interpolation algorithm’s displacement increment is immediately corrected, thereby preventing equipment overload.