Research on remote hydro-generator sets diagnosis system

A type of remote monitoring and diagnosis system is brought forward which based on Matlab Web Server.Firstly,wavelet packet decomposition is introduced to acquire energy features of which reflect hydrogenerator sets performance to be Feature Parameter.Then these Feature Parameters can be adopted as BP Neural Network input variable to realize fault diagnosis.Most of all,it is the first time to adopt Matlab Web Server to hydro-generator sets faults diagnosis field to implement distributed remote monitoring and diagnosis system.Therefore,remote diagnosis application is independent from the OS used on server side.There is no need for software maintenance by clients.And clients can finish remote diagnosis by Web Browser and without installation of Matlab-software.Client users can monitor and diagnose hydro-generator sets by Browser.Finally,further research work is pointed out such as hydro-generator sets fault modeling,accelerating BP Neural Network learning speed and convergence property,improving data transfer speed of Matlab Web Server to meet the needs of real-time diagnosis for hydropower generator sets.

Study of Internet-based Open Remote Diagnostic System

With the wide application of information technologi es , Internet-based remote diagnosis (IRD) of plant will surely become the main se rvice mode of corporations in the future. Therefore, it has received a great dea l recognition from academia and the industry. The IRD technology, which is based upon database, computer, and network technologies is the focus of correlative r esearch all over the world. Although some scientific institutions have developed primary IRD systems, their functions are quite narrow with many shortcomings. I n short, the standard of remote diagnosis has not been created, in particula r the network manufacture and diagnostic resources cannot be shared extensiv ely, so the systemic open character has not been developed enough to create the efficiency and the scope of the existing remote diagnostic systems. Aimed at improving the limitations mentioned above, in this paper we try to develop Web -CORBA open remote diagnosis architecture over the Internet, which is based on the existing troubleshooting software. We have designed and realized the general -purpose data interface of the software and some Java applets functional module s. Thereby the software’s open character and application field get widened. Our current research is focused on building the remote intelligent diagnosis center on the basis of the Web-CORBA architecture. Some basic functions have been app lied. Further, we put forward the project of combining the enterprise interior d iagnostic system to the remote diagnosis center, and make a study of building th e remote diagnosis object network architecture. The open remote diagnostic syste m based on Internet offers many advantages. Also, with the CORBA distributed obj ect technology, the distributed diagnostic resources can be connected as a coope rative diagnosis object system, in order that all the resources can be shared to the full extent, and the advanced diagnostic technique can be applied as soon a s possible. This is the inevitable trend of the diagnostic technology.

Intelligent Information Management in Aquaponics to Increase Mutual Benefits

Aquaponics are feedback and two player systems, in which fish and crops mutually benefit from one another and, therefore require close monitoring, management and control. Vast amount of data and information flow from the aquaponics plant itself with its huge amount of smart sensors for water quality, fish and plant growth, system state etc. and from the stakeholder, e.g., farmers, retailers and end consumers. The intelligent management of aquaponics is only possible if this data and information are managed and used in an intelligent way. Therefore, the main focus of this paper is to introduce an intelligent information management (IIM) for aquaponics. It will be shown how the information can be used to create services such as predictive analytics, system optimization and anomaly detection to improve the aquaponics system. The results show that the system enabled full traceability and transparency in the aquaponics processes (customers can follow what is going on at the farm), reduced water and energy use and increased revenue through early fault detection. In this, paper the information management approach will be introduced and the key benefits of the digitized aquaponics system will be given.