IS220PSVOH1A I/O excitation redundant module GE

Brand: GE

model: IS220PSVOH1A
System: Gas turbine system
Origin: United States

The GE IS220PSVOH1A 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

IS220PSVOH1A Product Introduction

GE IS220PSVOH1A Embedded Controller Module
 
GE IS220PSVOH1A Embedded Controller Module Product Details:
 
GE IS220PSVOH1A 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 IS220PSVOH1A 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 IS220PSVOH1A 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.
 
IS220PSVOH1A 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 Leveraging big data tool chainsAfter the data collected from the manufacturing product value chain is stored in the database, a data analysis system is required to analyze the data. The manufacturing data analysis system framework is shown in Figure 1. Data is first extracted, transformed, and loaded (ETL) from different databases into a distributed file system, such as Hadoop Distributed File System (HDFS) or a NoSQL database (such as MongoDB). Next, machine learning and analytics tools perform predictive modeling or descriptive analytics. To deploy predictive models, the previously mentioned tools are used to convert models trained on historical data into open, encapsulated statistical data mining models and associated metadata called Predictive Model Markup Language (PMML), and Stored in a scoring engine. New data from any source is evaluated using models stored in the scoring engine [9].A big data software stack for manufacturing analytics can be a mix of open source, commercial, and proprietary tools. An example of a manufacturing analytics software stack is shown in Figure 2. It is known from completed projects that existing stack vendors do not currently offer complete solutions. Although the technology landscape is evolving rapidly, the best option currently is modularity with a focus on truly distributed components, with the core idea of ​​success being a mix of open source and commercial components [10].In addition to the architecture presented here, there are various commercial IoT platforms. These include GE”s Predix ( www.predix.com ), Bosch”s IoT suite (www.bosch-iot-suite.com), IBM”s Bluemix ( www.ibm.com/cloud-computing/ ), ABB based on Microsoft Azure IoT services and people platform (https://azure.microsoft.com) and Amazon’s IoT cloud (https://aws.amazon.com/iot). These platforms offer many standard services for IoT and analytics, including identity management and data security, which are not covered in the case study here. On the other hand, the best approaches offer flexibility and customizability, making implementation more efficient than standard commercial solutions. But implementing such a solution may require a capable data science team at the implementation site. The choice comes down to several factors, non-functional requirements, cost, IoT and analytics.

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