scholarly journals Multiple Fault Identification Method in the Frequency Domain for Rotor Systems

2002 ◽  
Vol 9 (4-5) ◽  
pp. 203-215 ◽  
Author(s):  
Nicolò Bachschmid ◽  
Paolo Pennacchi
Keyword(s):  
Power Plant ◽  
Numerical Simulations ◽  
Frequency Domain ◽  
Rotor System ◽  
Fault Identification ◽  
Multiple Fault ◽  
Multiple Faults ◽  
Rotor Systems ◽  
Different Types ◽  
Types Of Faults

Fault identification in rotor systems has been studied by many authors, but the considered malfunction is one single fault only, generally an unbalance. Real machines can be affected by several different types of faults; moreover sometimes also two different faults may develop simultaneously. A model based method for identifying multiple faults acting simultaneously on a rotor system in the frequency domain is briefly described and its robustness with regards to measuring and modelling errors is evaluated, by means of numerical simulations performed on the models of two typical power plant machines: a steam turbogenerator and a gas turbogenerator.

INVESTIGATION INTO AN ARTIFICIAL NEURAL NETWORK BASED FAULT IDENTIFICATION OF HVDC CONVERTER

2004 ◽  
Vol 13 (04) ◽  
pp. 813-827 ◽  
Author(s):  
NARENDRA BAWANE ◽  
A. G. KOTHARI
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Dynamic Response ◽  
Power System ◽  
Operating Mode ◽  
Fault Identification ◽  
Network Architectures ◽  
Dc Power ◽  
Different Types ◽  
Types Of Faults

This paper explores the possibility of using neural network to identify faults that may occur in a HVDC converter system. Based on the ability of these networks to distinguish reliably between different types of faults, the feature can be suitably integrated with ANN based controller to improve the dynamic response of AC–DC power system. In this paper, different neural network architectures to distinguish different faults in HVDC converter are proposed, and comparison between them is made under different system perturbations and faults. The method is independent of the operating mode of the converter.

scholarly journals Identification of Rub and Unbalance in 320 MW Turbogenerators

2003 ◽  
Vol 9 (2) ◽  
pp. 97-112 ◽  
Author(s):  
N. Bachschmid ◽  
P. Pennacchi ◽  
A. Vania ◽  
G. A. Zanetta ◽  
L. Gregori
Keyword(s):  
Power Plant ◽  
Frequency Domain ◽  
Theoretical Background ◽  
Fault Identification ◽  
Vibration Measurements ◽  
Rotating Speed ◽  
Model Based ◽  
First Case ◽  
Identification Technique ◽  
Fossil Power Plant

This article presents two experiences of applying a model-based fault-identification method to real machines. The first case presented is an unbalance identification in a 320 MW turbogenerator unit operating in a fossil power plant. In the second case, concerning a machine of the same size but from a different manufacturer, the turbine has been affected by a rub in the sealings. This time, the fault is modeled by local bows. The identification of the faults is performed by means of a model-based identification technique in a frequency domain, suitably modified in order to take into account simultaneous faults. The theoretical background of the applied method is briefly illustrated and some considerations are also presented about the best choice of the rotating speed set of the run-down transient to be used for an effective identification and about the appropriate weighting of vibration measurements at the machine bearings.

scholarly journals Identification of Rub and Unbalance in 320-MW Turbogenerators

2004 ◽  
Vol 10 (4) ◽  
pp. 265-281 ◽  
Author(s):  
N. Bachschmid ◽  
P. Pennacchi ◽  
A. Vania ◽  
G. A. Zanetta ◽  
L. Gregori
Keyword(s):  
Power Plant ◽  
Frequency Domain ◽  
Theoretical Background ◽  
Fault Identification ◽  
Rotating Speed ◽  
Model Based ◽  
First Case ◽  
Identification Technique ◽  
Lp Turbine ◽  
Fossil Power Plant

This article presents two experiences of application of a model-based fault identification method on real machines. The first case presented is an unbalance identification on a 320-MW turbogenerator unit operating in a fossil power plant. In the second case, concerning a machine of the same size but of a different manufacturer, the Low Pressure (LP) turbine was affected by a rub in the sealings and this time, the fault was modeled by local bows. The identification of the faults is performed by means of a model-based identification technique in frequency domain, suitably modified in order to take into account simultaneous faults. The theoretical background of the applied method is briefly illustrated and some considerations also are presented about the best choice of the rotating speed set of the run-down transient to be used for an effective identification and about the appropriate weighting of vibration measurements at the machine bearings.

Application of Model Based Diagnosis in Two-Span Rotor System with Two Unbalance Faults

2011 ◽  
Vol 199-200 ◽  
pp. 780-783
Author(s):  
Yue Gang Luo ◽  
Song He Zhang ◽  
Hong Liang Yao ◽  
Bang Chun Wen
Keyword(s):  
Numerical Simulations ◽  
Least Squares ◽  
Rotor System ◽  
Fault Identification ◽  
Residual Vibration ◽  
Vibration Signals ◽  
Least Squares Fitting ◽  
Identification Method ◽  
Model Based

The model based fault identification method was used to identify the two unbalance faults in two-span rotor system. The unbalance location and magnitude were identified using least squares fitting approach by the system’s transient residual vibration. The all-phasic FFT technique was used to analyze the original phases of vibration signals. The unbalance location and magnitude of the rotor system can be detected by using only a few sensors. Numerical simulations and experiment on rotor system with two unbalance faults were used, which proved the efficiency of the method.

scholarly journals Tracking a Decentralized Linear Trajectory in an Intermittent Observation Environment

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2127
Author(s):  
Wasi Ullah ◽  
Irshad Hussain ◽  
Iram Shehzadi ◽  
Zahid Rahman ◽  
Peerapong Uthansakul
Keyword(s):  
Tracking System ◽  
Fault Detection And Isolation ◽  
Sensor Data ◽  
Processing Unit ◽  
Tracking Systems ◽  
Multiple Faults ◽  
Different Types ◽  
Core Issues ◽  
Types Of Faults

Faults and failures are familiar case studies in centralized and decentralized tracking systems. The processing of sensor data becomes more severe in the presence of faults/failures and/or noise. Effective schemes have been presented for decentralized systems, in the presence of faults only. In some practical scenarios of systems, there are certain interruptions in addition to these faults. These interruptions may occur in the form of noise. However it is expected that the decision about the sensor data is difficult in the presence of noise. This is because the noise adversely affects the communication amongst sensors and the processing unit. More complexity is expected when there are faults and noise simultaneously. To deal with this problem, in addition to existing fault detection and isolation schemes, the Kalman filter is employed. Here, a generic discussion is provided, which is equally applicable to other situations. This work addresses various faults in the presence of noise for decentralized tracking systems. Local single faults and multiple faults in the presence of noise are the core issues addressed in this paper. The proposed work is comprised of a general scenario for a decentralized tracking system followed by a case study of a target tracking scenario with and without noise. The presented schemes are also tested for different types of faults. The proposed work presents effective tracking in the presence of noise and faults. The results obtained demonstrate the acceptable performance of the scheme of this work.

scholarly journals Faults Identification and Corrective Actions in Rotating Machinery at Rated Speed

2006 ◽  
Vol 13 (4-5) ◽  
pp. 485-503 ◽  
Author(s):  
Nicolò Bachschmid ◽  
Paolo Pennacchi
Keyword(s):  
Frequency Domain ◽  
Rotating Machinery ◽  
Fault Identification ◽  
Operating Speed ◽  
Huge Amount ◽  
Rotor Systems ◽  
Rotating Speed ◽  
Normal Operating ◽  
Vibration Data ◽  
Model Based

Malfunction identification in rotor systems by means of a model based approach in the frequency domain during long lasting speed transients (coast-down procedures in large turbo-generators), where a huge amount of vibration data at different rotating speeds is usually collected, has proved to be very effective. This paper explores the possibility to adapt this method to the situation when the vibration data are available at one rotating speed only, which in real machines is generally the normal operating speed. It results that single speed fault identification can be successful, but does not allow to discriminate between different malfunctions that generate similar symptoms. Neverthless the identification results can be used to define corrective balancing masses.

Vibration Analysis of Rotor System by Combined Adaptive Time-Frequency Analysis and Independent Component Analysis

2011 ◽  
Vol 474-476 ◽  
pp. 1406-1411
Author(s):  
Bin Li ◽  
Yu Guo ◽  
Yan Chun Ding ◽  
Ting Wei Liu ◽  
Jing Na ◽  
...  
Keyword(s):  
Independent Component Analysis ◽  
Frequency Analysis ◽  
Component Analysis ◽  
Rotor System ◽  
Independent Component ◽  
Time Frequency Analysis ◽  
Multiple Faults ◽  
Rotor Systems ◽  
Time Frequency ◽  
Adaptive Time

Traditional time-frequency analysis methods such as short-time Fourier transform (STFT) and Wigner-Ville distribution (WVD) cannot always work effectively for the complex rotor systems where the multiple faults are involved. A noise cancellation method for the rotor faults detection is proposed in this paper by combining the independent component analysis (ICA) scheme and the adaptive time-frequency analysis (ATFA) approach. In the proposed method, the raw picked data are first separated into different independent components (ICs) via the ICA according to the different vibration sources. Then the ICs are processed by the ATFA to obtain a clear vibration character for the fault diagnosis. Experiments on a rotor system with hybrid fault of the rotor imbalance and the bolt looseness are introduced to verify the feasibility and validity of the proposed scheme.

ACCURACY RATING MEASUREMENT OF VIBRATION ELECTROMECHANICAL DEVICES

2019 ◽  
Vol 1 (7) ◽  
pp. 42-45
Author(s):  
V. A. Golubkov ◽  
V. F. Shishlakov ◽  
A. G. Fedorenko ◽  
E. Yu. Vataeva
Keyword(s):  
Technical Condition ◽  
Rotor System ◽  
Vibration Measurement ◽  
Random Errors ◽  
Mass Ratio ◽  
Signal Flow Graph ◽  
Bond Graphs ◽  
Rotor Systems ◽  
Electromechanical Devices ◽  
Main Components

Electromechanical devices consist mainly of rotor systems. Vibration is the result of the interaction of the elements of the rotor system and is largely determined by the accuracy of manufacturing elements at the production stage and defects arising in the process of operation. The main components of the rotor systems that affect vibration are bearings. To determine the technical condition of the bearings and the service life of the rotor system, it is necessary to accurately measure the unobservable vibrations of the rotor. The article describes the model of the channel for measuring the vibration of an electromechanical system, built using the apparatus of bond graphs. The transfer function is obtained by analyzing the signal flow graph. The systematic and random errors of vibration measurement are analyzed depending on the mass ratio between the system case and the vibration transducer for various sensor masses and attachment rigidity.

scholarly journals An Efficient Neural Network-Based Method for Diagnosing Faults of PV Array

2021 ◽  
Vol 13 (11) ◽  
pp. 6194
Author(s):  
Selma Tchoketch_Kebir ◽  
Nawal Cheggaga ◽  
Adrian Ilinca ◽  
Sabri Boulouma
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Modeling Process ◽  
Photovoltaic Arrays ◽  
Mode Of Operation ◽  
Different Types ◽  
The Neural Networks ◽  
Operational Modes ◽  
Types Of Faults ◽  
Electrical Data

This paper presents an efficient neural network-based method for fault diagnosis in photovoltaic arrays. The proposed method was elaborated on three main steps: the data-feeding step, the fault-modeling step, and the decision step. The first step consists of feeding the real meteorological and electrical data to the neural networks, namely solar irradiance, panel temperature, photovoltaic-current, and photovoltaic-voltage. The second step consists of modeling a healthy mode of operation and five additional faulty operational modes; the modeling process is carried out using two networks of artificial neural networks. From this step, six classes are obtained, where each class corresponds to a predefined model, namely, the faultless scenario and five faulty scenarios. The third step involves the diagnosis decision about the system’s state. Based on the results from the above step, two probabilistic neural networks will classify each generated data according to the six classes. The obtained results show that the developed method can effectively detect different types of faults and classify them. Besides, this method still achieves high performances even in the presence of noises. It provides a diagnosis even in the presence of data injected at reduced real-time, which proves its robustness.

Scale-dependent merging of baroclinic vortices

1994 ◽  
Vol 264 ◽  
pp. 81-106 ◽  
Author(s):  
J. Verron ◽  
S. Valcke
Keyword(s):  
Numerical Simulations ◽  
Critical Point ◽  
Lower Layer ◽  
Interaction Mechanism ◽  
Competitive Effects ◽  
Different Types ◽  
Shape Effects ◽  
Baroclinic Vortices ◽  
The Relationship ◽  
Stratified Model

The influence of stratification on the merging of like-sign vortices of equal intensity and shape is investigated by numerical simulations in a quasi-geostrophic, two-layer stratified model. Two different types of vortices are considered: vortices defined as circular patches of uniform potential vorticity in the upper layer but no PV anomaly in the lower layer (referred to as PVI vortices), and vortices defined as circular patches of uniform relative vorticity in the upper layer but no motion in the lower layer (referred to as RVI vortices). In particular, it is found that, in the RVI case, the merging behaviour depends strongly on the magnitude of the stratification (i.e. the ratio of internal Rossby radius and vortex radius). The critical point here appears to be whether or not the initial eddies have a deep flow signature in terms of PV.The specific phenomenon of scale-dependent merging observed is interpreted in terms of the competitive effects of hetonic interaction and vortex shape. In the case of weaker stratification, the baroclinic structure of the eddies can be seen as dominated by a mechanism of hetonic interaction in which bottom flow appears to counteract the tendency of surface eddies to merge. In the case of larger stratification, the eddy interaction mechanism is shown to be barotropically dominated, although interface deformation still determines the actual eddy vorticity profile during the initialization stage. Repulsion (hetonic) effect therefore oppose attraction (barotropic shape) effects in a competitive process dependent on the relationship between the original eddy lengthscale and the first internal Rossby radius.A concluding discussion considers the implications of such analysis for real situations, in the ocean or in the laboratory.

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