The milestone discovery of green fluorescent protein (GFP) from the jellyfish Aequorea victoria, its optimisation for efficient use in plantae, and subsequent improvements in techniques for fluorescent detection and quantification have changed plant molecular biology research dramatically. Using fluorescent protein tags allows the temporal and spatial monitoring of dynamic expression patterns a...

Modern industrial power plants require continuous monitoring to ensure their safe and reliable operation. This monitoring depends heavily on accurate sensor readings from a large number of sensors, making sensors an important part of any plant. The possibility of more than a single sensor being simultaneously faulty should not be overlooked. In this paper, a nonlinear system data validation app...

This paper presents an integrated system for intelligent control and fault management in thermal power plants. This modular system consists of fuzz logic based intelligent control fuzzy petri net based plant performance monitoring and soft computing based fault diagnosis. Finally, a fault management strategy is presented, which aims at increased up – time of the plant and enhanced safety of the...

The accident at the Fukushima Daiichi Nuclear Power Plant has resulted in many cases of internal exposure to radionuclides. JAEA staff has examined the workers and the residents by measurement with a various type of whole body counters. The committed effective dose was estimated using the intake scenarios according to the object of monitoring and expected level of exposure. In the examination o...

The development of SH waveguide probes that can work under extreme conditions (Temperature>500°C, radiation) has opened up the possibility to carry out ultrasonic monitoring using SH waves on plant components that cannot be inspected otherwise. The deployment of such monitoring devices can result in substantial economic benefit by continuously supplying information about the state of a critical...

Numerous condition monitoring techniques and identification algorithms for detection and diagnosis of faults in industrial plants have been proposed for the past few years. Motors are one of the common used elements in almost all plant machinery. They cause the machine failure upon getting faulty. Therefore advance and effective condition monitoring techniques are required to monitor and detect...

Plant monitoring and diagnosis are usually integrated as one process to detect and isolate suspicious symptoms and use these to identify the root cause of the failure [1, 2]. The research reported here enables a new plant monitoring and diagnosis framework that employs multiple fuzzy rule-based decision-support system at different diagnosing stages. By employing fuzzy sets and by constructing a...

In this paper, monitoring and sensor fault detection in a waste-water treatment process are discussed. Monitoring is based on the Takagi-Sugeno fuzzy model of a plant process obtained by using Gustafson-Kessel fuzzy clustering algorithm.The paper also explains the principle of the Takagi-Sugeno fuzzy model. The main idea is to cope with the non-linearity of a monitored process. The output of th...

This paper proposes a new method to detect abnormal process state. The method is based on cluster center point monitoring in time and is demonstrated in its application to data from Olkiluoto nuclear power plant. Typical statistical features are extracted, mapped to ndimensional space, and clustered online for every time step. The process signals in the constant time window are classified into ...

This article first of all presents an innovative application of Real-Time Simulation Monitoring (RTSM), defined hereafter as “hydro-cloning”, developed by Power Vision Engineering. Second, a successful implementation of hydro-cloning is presented for the 170 MW La Bâtiaz hydroelectric power plant, HPP, owned and operated by Electricité d’Emosson SA, in the Canton of Wallis, Switzerland. The “Hy...