Process Data Acquisition – PDA

-- Detailed analysis of quality manage&industrial big data sources

高速数采方案

High speed data acquisition scheme

系统

System

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1 Background and significance

12 HDC - Hot rolled high-frequency high-density Digital steel Coil

2 PDA - data acquisition and analysis system

13 CDC - Cold rolled Digital steel Coil

3 LTA - Long historical Trend Analysis system

14 DSP - Digital Steel Plate

4 HDS - open time series high frequency Historical database

15 DTP - Digital Steel Pipe

5 DBU - Database system and Upgrade tools

16 CDS - Continuous casting Digital Slab

6 DCC - Digital Coil Conversion and full process quality management

17 TDA - Typical high-speed Data Acquisition scheme

7 CFS - Coil Fast Search and statistics system

18 QMS - Quality Manage and analysis System

8 DSO - Device diagnostic Synchronous Oversampling system

19 Common debugging tools and development board

9 RSA - Roll Spalling Alarm and Quick Stop System

20 Project performance and typical project application

10 RCM - Roller Current Monitoring system

21 Research Form for PDA System Configuration in the Steel Industry

11 HDP - High frequency density and speed Data Platform construction

 

7 CFS - Coil Fast Search and statistics system

Google, Baidu, and Taobao are civil big data searches, with most of their data being triggered event based. iSearch is an industrial big data search, with similarities and significant differences. The latter is mainly high-frequency temporal and high-density conversion based.

Digital steel coils are vast amounts of data on the millisecond and centimeter scales. If traditional databases are used to search and count certain indicators among tens of millions of steel coils, the calculation time will be on the hour scale, which is difficult to accept in practical work.

The search and statistics speed of CFS (Coil Fast Search system) is hundreds of times faster than traditional databases, achieving the ability to search for 10000 steel pieces that meet the requirements in tens of millions of steel coils in seconds, and calculate certain indicators of these 10000 steel pieces, return extraction data and statistical results. For example, the search and statistics of all steel coils in 20 years are performed once, and the results are returned in 3 seconds. The configuration file iSearch Searchini. Simultaneously supporting control networks, office networks, wide area networks, etc.

The search statistics results can be saved to local or remote files, databases, or received through MQTT. It supports file sharing, direct opening, FTP, and HTTP downloading, and provides download services for raw high-frequency data.

7.1 Changes in working methods

The traditional method is to save a certain statistical calculation result every day and summarize it when needed. If you want to modify a certain statistical accuracy range, you need to organize and calculate all the historical data once. The workload is huge and time-consuming, and some of the original data may have been lost. iSearch performs statistical calculations on the original high-frequency data every time, and the accuracy range can vary according to needs.

7.2 Changes in work platforms

Transforming from fixed and explicit computing to distributed high-speed computing primarily focused on search, the number of floating-point operations per second can reach tens or even hundreds of billions.

7.3 Changes in data frequency granularity

Transforming from event triggered, second or meter level data accuracy to millisecond or centimeter level data accuracy.

7.4 System structure

Figure 7.1 CFS Signal Flow Chart

7.5 Implementation scheme

Figure 7.2 Schematic diagram of CFS system structure

The iSearch supports B/S and C/S architectures.

7.6 Slice Indicator Search Statistics

The search range and statistical output value of the steel coil can be selected according to the following figure, and each steel can be divided into a maximum of 21 slices.

Figure 7.3 iSearch Search Interface

Figure 7.4 Storage of search statistics results in csv files and databases

7.7 Special Characteristics Identification - Steel Grade Development and Evaluation

Special characteristic templates are defined by users, and any steel grade can be identified according to various templates. Steel grade developers establish statistical parameters for their respective steel grades to guide decision-making.

Figure 7.5 Special Characteristic Identification Search - Steel Grade Development

7.8 Guidance on the position where strip steel should be cut off

Some special steel grades such as BS700MCK2 are particularly sensitive to temperature, and the excess parts should be cut off as much as possible before delivery to avoid a large number of quality objections.

Figure 7.6 Guidance on the position of strip steel to be cut

7.9 Search and download the original data of theme slicing

Raw data is an important basis for analysis. A complete digital steel coil records thousands of variables. The CFS search system can quickly generate a list of steel coils and signals that users are interested in a certain topic .csv files can be stored in the database at the same time. All signal raw data in the topic is saved in .bin format for direct analysis and download. The length range can be specified when searching for raw data, The export method can be 1 point per meter, multiple points per meter, or how many points to export.

Figure 7.7 Search Download Theme Slice Raw Data

Figure 7.8 Steel coil list stored in csv file and database

 

Apparatus test&Fault diagnosis&Quality analysis

Millisecond data sampling

Real-time data compression

Capture signal instantaneous mutation

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PDAServer    PDAClient