Fault Diagnosis under Multiple Sequential Faults of the Rain-gauge Network Used to Control the Barcelona Sewer System
نویسندگان
چکیده
This paper discusses the problem of fault diagnosis under multiple sequential faults occurrence. In industrial applications this type of fault is the most common since the continuous operation of systems/processes is required. The fault diagnosis algorithms should cope with such type of multiple faults, but degradation in their fault isolation capabilities is introduced until the point that they should be stopped. A new algorithm to design the fault diagnosis system to be able to tolerate multiple sequential sensor faults is proposed. Finally, an example based on the raingauge sensor network of the Barcelona sewer system will be used to illustrate how the associated fault diagnosis system behaves under multiple sequential faults occurrence and to test the proposed algorithm. Copyright © 2005 IFAC.
منابع مشابه
Fault Tolerant Optimal Control of Sewer
Under the city of Barcelona, which has a population of three millions of habitants in an area of 98 Km, there is a complex sewage system with almost 1500 Km of length. That system is characterized for being unitary, that is, its collectors carry rain water and residual water. The yearly rainfall is not very high (600 mm/year), but it includes heavy storms typical of the Mediterranean climate th...
متن کامل1 Limnimeter and Rain Gauge FDI in Sewer Networks 1 using an Interval Parity Equations based Detection Approach 2 and an Enhanced Isolation Scheme
Limnimeter and Rain Gauge FDI in Sewer Networks 1 using an Interval Parity Equations based Detection Approach 2 and an Enhanced Isolation Scheme 3 4 Vicenç Puig, Joaquim Blesa 5 6 Advanced Control Systems Group (SAC), Institute of Robotics and Industrial Informatics (IRI-CSIC) ,Universitat 7 Politècnica de Catalunya (UPC), Pau Gargallo, 5 ,08028 Barcelona, Spain 8 (e-mail: [email protected]...
متن کاملDetection of Single and Dual Incipient Process Faults Using an Improved Artificial Neural Network
Changes in the physicochemical conditions of process unit, even under control, may lead to what are generically referred to as faults. The cognition of causes is very important, because the system can be diagnosed and fault tolerated. In this article, we discuss and propose an artificial neural network that can detect the incipient and gradual faults either individually or mutually. The mai...
متن کاملFault diagnosis in a distillation column using a support vector machine based classifier
Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...
متن کاملAN INTELLIGENT FAULT DIAGNOSIS APPROACH FOR GEARS AND BEARINGS BASED ON WAVELET TRANSFORM AS A PREPROCESSOR AND ARTIFICIAL NEURAL NETWORKS
In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...
متن کامل