Function Analysis of Process Control System of 1450 mm Continuous Cold Rolling Production Line

This paper summarizes the Siemens process control system used in Angang's 1450mm cold tandem rolling production line , introduces the main equipment and components of the control system, and analyzes the functions of the control system such as material tracking, process communication, and rolling model.
Keywords : tandem cold rolling ; process control system ; rolling model

With the continuous production of many domestic cold rolling production lines and the increasingly complex operation of cold rolling production lines, the demand for a mature process automatic control system is imminent . Because on the one hand, such a process control system can make the production process transparent and can quickly carry out manual intervention ; on the other hand, its effective online technology and automatic control functions can fully meet the production needs . The Siemens process control system just meets these demands . It uses innovative software techniques such as neural networks and solutions to previously unsolved complex programs to optimize rolling models.
The desired parameters have been applied to the 1450mm cold rolling production line of Anshan Iron and Steel Co. , Ltd. This article analyzes the composition and function of the main equipment of the process control system, hoping to play a helpful role in the debugging of the cold tandem process control system in the future .

1 Introduction to Process Control System
The process control ( level 2 ) of the 1450mm cold tandem rolling production line uses the SUBSYS system based on the CORBA specification . CORBA ( Ccmmon Object Request Binker Anchite — tuie Common Object Request Broker Architecture ) is a standard object-oriented application system specification developed by the OMG organization . The communication information transfer between the secondary processes is realized through SUBSYS , most of the source codes of the secondary processes are written in standard C language , and the data storage adopts ORACLE 10g database management technology .
The cold tandem rolling process control system is divided into two parts: control and non-control . The control part is mainly related to the control of the rolling model, including rolling strategy , model self-adaptation , set value calculation , neural network training , roll change , calibration , roll temperature and wear model, etc. The non-control part mainly completes the communication interface between the second level and the first level, the second level and the third level , HMI , etc. Mainly includes material tracking , roll data

Management , data storage , setting value delivery , measurement value acquisition , measurement value processing, etc.
2 process control system process and function
The process and functions of the cold rolling process control system are as follows :

1. Three-level adapter A 3 ( Adapter to Level 3) : The three-level adapter connects the process computer and the three-level computer . The third level sends master data, roll data and product sequences to the process computer . A 3 converts these data and sends them to the secondary computer and stores them in the database . If a coil of strip rolling is completed, the product data is read from the database and sent to the third level .
2. Delete Database DL ( Delete Database ) : The process DL deletes the old rolled strip data records selected in the database to avoid database overflow .
3. Material Tracking MT ( Material Tracking ) : Material tracking records all materials on the entire processing line from entry to exit through volume tracking , Material is tracked through the strip from pickling to rolling mill . In case of accidental splits and tape breaks , material tracking creates a new material unit . Strip tracking process transfer of setpoints for pickling lines , Process calculations for rolling mills , Write product data to the database .
4. Acid measurement value acquisition PX ( Measured Value Acquisition Pickling Aiea) : Pickling measurement value acquisition assigns the measurement value from the basic automation to the logical measurement position , and stored in shared memory .
5. Acidity measurement processing PY ( Measured VaUie Proce s ingPicklingArea ) : The pickling measurements process reads PX collected measurements from shared memory and produces measurement rows . Those measurement location rows will be broken down into header and measurement data rows . Rows of measured values are calculated as associated mean , standard deviation , minimum , maximum, etc. The calculated measured values are passed to MT .
6. Strip Defects SD ( Strip Defects ) : The operator inputs strip defect information , including the defect start position , end position and defect type, and then transmits it to the process SD . SD will assign this information to the respective strip and store it in the secondary database .
7. Speed optimization SO ( Speed Optimization) : speed optimization calculates the most ideal pickling and rolling mill pivot speed . The goal is to increase product yield and quality .
8. Acidity setting value delivery SP ( SetpontTransns - sonPcklngArea ) : Send pickling stage setpoints to base automation.

(9) Setting value delivery ST ( Se point Tian n iss ion Tandon Aea ): sending the setting values of the current roll and the next roll ( from pre-calculation and post-calculation ) to the basic automation .

1. Shutdown processing SZ ( Mil Down Tines) : Shutdown service cycle checks the strip speed of the rolling mill , In this way the stop and duration are discovered . If for a certain period of time , the speed of the rolling mill is less than the minimum limit speed , then the shutdown event starts timing . When the mill speed is greater than the minimum limit speed for a certain period of time , The shutdown event is over . At this point the shutdown event timer expires and the duration of the shutdown is calculated .
2. Measured value acquisition TX ( MeasuredValueAc - quisition Tandem Aiea) : The measured value acquisition of the continuous rolling line accepts the measurement data from DAMA through the signal processor ( SH ) . TX stores the received measurement data to the logical measurement value position , and stores it in the shared memory for TY processing .
3. Measured value processing TY ( MeasuredValuePro - ce s ngTanden Area ) : Reads measurements from shared memory and produces measurement rows , which are split into header and measurement data rows . Rows of measured values are calculated as associated mean , standard deviation , minimum , maximum, etc. These correlated measurements are used in adaptive ( AD ) and temperature and wear models ( TW ) .
4. Set value data processing SDH ( Setup DataHandling ) : The main function is to calculate and process the set value sent to the first level .
5. Line coordination LCO (Line Cooidinator) : Line coordination is used to communicate with the first-level coordination , and coordinate the normal operation of the entire line .
6. Signal Handling SH ( SgnalHandlng ) : Signal processing is responsible for the interface between the first and second levels , processing all messages from the first level , and then sending them to each process .
7. Rolling strategy RS (Rolling Strategy) : The task of the rolling strategy is to provide data for the calculation of the set value . The data comes from material tracking requests , neuron network data , technical data .
8. Precompute PC ( PresetCalculatng ) : Setpoint calculation includes pre-calculation and post-calculation . According to the data provided by the rolling strategy, the set value is calculated and sent to the set value delivery process ST , which then sends it to the first level .
9. Neural Network NN ( Neural Netwoik ): Neural network training collects measured values during rolling and determines revised values . The modified parameters of the neural network are trained during the adaptation process . The setpoints are adjusted by the measured values to obtain an optimal rolling model .

3 PROCESS CONTROL SYSTEM OBJECT MODEL

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