PM864AK01 3BSE018161R1 ABB Main Processor Module DCS/Distributed Control System

Description

The automation platform PM864AK01 configured by ABB takes an AC 800PEC controller as the core, including the Compact800 HMI system with seamless integration of control and human-machine image functions, as well as supporting fast I/O modules and corresponding communication modules, which are used to replace the original HMI image system, control system and PLC. The original DC drive system, thickness gauge system, magnetic ruler roll gap detector, detection elements, remote I/O modules and other field equipment are all used continuously, thus reducing the overall investment of the electric control system.
In view of the great success of the five stand continuous rolling project in Boxing County, Kerui’s management awarded ABB with the contract for upgrading the electric control system of four single stand cold rolling mills PM864AK01 at the end of April 2016. ABB immediately started the project implementation, and completed the preparation work before the commissioning of design, programming, hardware platform construction, system integration, simulation and simulation testing in the office within three months; The project implementation team entered the site at the end of July 2016, and the commissioning of the first rolling mill was successfully completed at the beginning of August, and the commissioning of the second rolling mill was successfully completed at the end of August. All the above drawbacks were eliminated, and a new benchmark of electric control system for single stand cold rolling mill was set in Boxing County.

4 Project achievements
4.1 Simplify complexity and greatly improve production efficiency
The operation and production process of the old system completely depends on the operator’s input setting and on-site adjustment, and the judgment of faults also depends on experience. The operator’s labor intensity is high and the effect is poor. The reconstructed system provides the accurate set value of model calculation, and the cause of the fault is clear. PM864AK01 field regulation is also replaced by real-time model calculation feedforward compensation, which greatly reduces the operation intensity and improves the efficiency of fault diagnosis.
Before transformation, the inlet tension needs to be adjusted for 18 times and the outlet tension needs to be adjusted for 12 times; After transformation, the system automatically compensates and dynamically adjusts the compensation without manual intervention.
4.2 Improve product quality
4.2.1 Plate shape
In the rolling process, with the different rolling speed, the friction in the roll gap will have a significant change. If the corresponding system solution can not be handled in time, it will have a significant impact on the shape of the plate (wave wrinkle, side wave, intermediate wave, etc.). The solution of this problem benefits from the calculation of various feedforward compensation coefficients online and the application of continuous self-learning optimization results, and the system provides good conditions for shape improvement.
Before the transformation, the artificial intervention lags behind, and the process of speed increase and speed decrease will cause hundreds of meters of side waves and middle wave wrinkles; After transformation, there is no need for manual intervention, and the plate shape is consistent in the process of speed increase and speed decrease. See Figure 4 for comparison of results before and after transformation.
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Figure 4 Shape Improvement before and after Automation System Upgrading
4.2.2 Improve thickness control accuracy
In the process of debugging, it is found that the noise level of the thickness gauge system itself is very high. The measured value record of the thickness gauge when the unit is stopped (the curve of the measured value at a point under the static state of the strip steel) shows that the standard deviation reaches 0.781 μ m。
In addition, this type of rolling mill generally has the disadvantage of low dynamic accuracy. Thanks to accurate model preset value and feedforward compensation after transformation, the dynamic accuracy has been greatly improved, basically reaching the accuracy similar to the static accuracy (standard deviation 1.4 μ m. It includes 0.7 μ M)

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