IS230TBAIH2C Gas turbine system Mark VI

Brand: GE

model: IS230TBAIH2C
System: Gas turbine system
Origin: United States

The GE IS230TBAIH2C turbine control module is used for various applications, including:

Electric power generation

Oil and Gas

EADS

ship

  • Email:Angela@sauldcsplc.com
  • Phone:+86 18350224834
  • WhatsApp:+8618350224834

Description

IS230TBAIH2C Product Introduction

GE IS230TBAIH2C Embedded Controller Module
 
GE IS230TBAIH2C Embedded Controller Module Product Details:
 
GE IS230TBAIH2C is an embedded controller module developed by General Electric (GE) for industrial automation and control systems.
The specific application scope of the product
will depend on the needs of system integration and industrial application, but generally speaking, this type of embedded controller module can be applied to the following categories:
 
Industrial automation: used to master and monitor various automation processes in the factory, such as production lines, machine installation,
manufacturing processes, etc.
Power industry: used for mastering and monitoring tasks in power plants and power distribution systems.
Chemical and process industries: used to monitor and grasp the production process in chemical plants, refineries, and other process industries.
Manufacturing industry: can be used to master and optimize the production process, ensuring the effectiveness of labor and product quality.
Transportation: The application in the traffic signal system, railway system, or other traffic control systems.
Construction automation: used for automation systems in construction, such as building management systems, intelligent construction control systems, etc.
Fire disposal punishment and situation control: application in the pollution fire disposal punishment plant, fire disposal punishment measures, and situation
monitoring and control system.
These are just some potential application areas, in fact, there can be more application scenarios, depending on the effectiveness and personality
of the controller module, as well as the specific needs of the customer.
 
 
General Electric has designed the processor/controller for the IS230TBAIH2C Mark VIe system. The Mark VI platform is General Electric”s Speedtronic range,
designed to manage gas or steam turbines.
It has a CIMPLICITY graphical interface and an HMI with software suitable for running heavy-duty turbines.
 
 
This IS230TBAIH2C is a single box assembly with a front panel for communication connections, two screws installed on the rear edge, and three grille holes for ventilation. The controller is designed to
be installed at the bottom of the cabinet. For a small setup that is easy to serve a triple redundant system, up to three components can be installed side by side.
 
IS230TBAIH2C uses the QNX operating system. It has a 667MHz Freescale 8349 processor. This board is powered by a 12 watt, 18-36 V DC power supply. Even at its maximum rated temperature, t
he board can operate within a temperature range of 0 to 65 degrees Celsius without the need for a fan for cooling. NFPA Class 1. This board can be used for two applications.
Contact Us
 
Mobile phone: 18350224834
 
E-mail: sauldcsplc@outlook.com
 
WhatsApp:+86 18350224834

(2) Data collection and traceability issues. Data collection issues often occur, and many assembly lines lack “end-to-end traceability.” In other words, there are often no unique identifiers associated with the parts and processing steps being produced. One workaround is to use a timestamp instead of an identifier. Another situation involves an incomplete data set. In this case, omit incomplete information parts or instances from the forecast and analysis, or use some estimation method (after consulting with manufacturing experts).(3) A large number of features. Different from the data sets in traditional data mining, the features observed in manufacturing analysis may be thousands. Care must therefore be taken to avoid that machine learning algorithms can only work with reduced datasets (i.e. datasets with a small number of features).(4) Multicollinearity, when products pass through the assembly line, different measurement methods are taken at different stations in the production process. Some of these measurements can be highly correlated, however many machine learning and data mining algorithm properties are independent of each other, and multicollinearity issues should be carefully studied for the proposed analysis method.(5) Classification imbalance problem, where there is a huge imbalance between good and bad parts (or scrap, that is, parts that do not pass quality control testing). Ratios may range from 9:1 to even lower than 99,000,000:1. It is difficult to distinguish good parts from scrap using standard classification techniques, so several methods for handling class imbalance have been proposed and applied to manufacturing analysis [8].(6) Non-stationary data, the underlying manufacturing process may change due to various factors such as changes in suppliers or operators and calibration deviations in machines. There is therefore a need to apply more robust methods to the non-stationary nature of the data. (7) Models can be difficult to interpret, and production and quality control engineers need to understand the analytical solutions that inform process or design changes. Otherwise the generated recommendations and decisions may be ignored.

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