Fig 1 - uploaded by Marino Sánchez Parra
Content may be subject to copyright.
Source publication
A fault detection analysis is presented focused on redundant information of a gas turbine in a CCCP model. The study using the structural analysis allows to determine the GT’s monitoring and detection capacities with conventional sensors. From this analysis it is concluded the existence of a non-detectable fault subsystem. To eliminate such subsyst...
Contexts in source publication
Context 1
... bipartite graph is given in Fig. 1 where a shadowed circle denotes a constraint. The respective description incidence matrix, IM, is shown in Table ...
Context 2
... as operators from a set of known variables to others where the path is determined by a concatenation process following an oriented graph. The concatenation algorithm for linear constraints is reduced to the Mason's method (Mason, 1956) and there are diverse ways to select the ARRs from the paths of a graph. For the particular graph G given in Fig. 1, the Dulmage-Medelsohn decomposition identifies the condition G + = G with 4 constraints, 3 unknown variables and the pair (u,y) as known nodes. Since the paths from y to u o viceversa pass by all constraints (c3, c2,d, c1), all faults associated to sensors, actuator and constraints are generic detectable. Thus, the path of Table 2 is ...
Context 3
... the particular graph G given in Fig. 1, the Dulmage-Medelsohn decomposition identifies the condition G + = G with 4 constraints, 3 unknown variables and the pair (u,y) as known nodes. Since the paths from y to u o viceversa pass by all constraints (c3, c2,d, c1), all faults associated to sensors, actuator and constraints are generic detectable. Thus, the path of Table 2 is a base to generate the ARRs for the model (c1,c2,c3), Eq. 7 is a particular analytical redundant relation. ...
Similar publications
The sparse decomposition based on matching pursuit is an adaptive sparse expression of the signals. An adaptive matching pursuit algorithm that uses an impulse dictionary is introduced in this article for rolling bearing vibration signal processing and fault diagnosis. First, a new dictionary model is established according to the characteristics an...
This paper exhibits a sensorless speed control method based on full-order-sliding-modeobserver applied to a fault-tolerant permanent-magnet-synchronous motor (PMSM) drivesystem. So, this paper proposes a rapid method of fault switch detection in the powerconverters aiming to make sure of the continuity of service despite the fault presence ofan ope...
![Fig. 2 Mathematical modeling of radiation faults [18]](profile/J-F-Boland/publication/272357699/figure/fig1/AS:391889791537153@1470445215285/Mathematical-modeling-of-radiation-faults-18_Q320.jpg)
Historically, actuators’ redundancy was used to deal with faults occurring suddenly in flight systems. This technique was generally expensive, time consuming and involves increased weight and space in the system. Therefore, nowadays, the on-line fault diagnosis of actuators and accommodation plays a major role in the design of avionic systems. Thes...
This paper presents different techniques on fault diagnosis in static converters used to supply and control induction heating systems. These techniques allow the detection and the location of the failed semiconductor switches. After an overview of the device with its main features in healthy state, we have afterwards focused on the fault detection...
The application of traditional feature extraction methods in subway mechanical fault diagnosis has attracted the attention of researchers. Based on the 5G intelligent sensor network signal processing theory, this paper constructs a fault diagnosis model for subway machinery and equipment and analyzes the effectiveness of the information redundancy...
Citations
Health monitoring of current complex systems significantly impacts the total cost of the system. Centralized fault diagnosis architectures are sometimes prohibitive for large-scale interconnected systems, such as distribution systems, telecommunication networks, water distribution networks, or fluid power systems. Confidentiality constraints are also an issue. This article presents a decentralized fault diagnosis method that only requires the knowledge of local models and limited knowledge of their neighboring subsystems. The method, implemented in the decentralized diagnoser design (D³) algorithm, is based on structural analysis and can advantageously be applied to high-dimensional systems, linear or nonlinear. Using the concept of isolation on request, a hierarchy is built according to diagnostic objectives. The resulting diagnoser is based on analytical redundancy relations (ARRs) generated along the hierarchy. Their number is optimized via binary integer linear programming (BILP) while still guaranteeing maximal diagnosability at each level. D³ proves of lower time complexity than its centralized equivalent. It is successfully applied to a nonlinear combined cycle gas-turbine power plant.
This chapter attempts to outline the pipeline failures and their impact on safety and environmental risks besides causing blockages and leaks in pipe networks. Furthermore, non-destructive testing techniques for detecting leakage and blockage are studied. They are visual detection approach, fluid odorant approach, mass balance approach, real-time transient model-based approach, pressure deviation approach, supervisory control and data acquisition system based on leakage identification approaches, pipeline hydrotest approach, magnetic and ultrasonic pipe detection approaches, acoustic emission inspection and monitoring system, wave warning system, pulse-echo flaw detector approach and acoustic wave reflectometry. Eventually, the stationary wavelet transform method is presented for structural health monitoring.
In this chapter, a new technique is proposed in order to detect, locate, as well as approximate the fluid leaks in a straight pipeline (without branching) by taking into consideration the pressure and flow evaluations at the ends of pipeline on the basis of data fusion from two methods: a steady-state approximation and Second-order Extended Kalman Filter (SEKF). The SEKF is on the basis of the second-order Taylor expansion of a nonlinear system unlike to the more popular First-order Extended Kalman Filter (FEKF). The suggested technique in this paper deals with just pressure head and flow rate evaluations at the ends of pipeline that has intrinsic sensor as well as process noise. A simulation example is given for demonstrating the validity of the proposed technique. It shows that the extended Kalman particle filter algorithm on the basis of the second-order Taylor expansion is effective and performs well in decreasing systematic deviations as well as running time.
This paper deals with issues of actuator fault tolerant PID controllers. It is studied, how residual generation based on a linear model is affected by the robust properties of a PID used in feedback. To get the sensitivity of the residual with respect to faults and to keep the robustness of the controller, a scheme is proposed with a non linear residual generator and a family of PIDs interconnected in such a way that the stability is held even with actuator faults. The conditions reported by Bhattacharyya for a family of stabilizing PID controllers are used to select the fault tolerant PID parameters considering actuator faults. Using the benchmark of the three tank system with two pumps, simulations and experimental results show the advantages of the fault tolerant PID scheme.
This work deals with the issue of faults classification on line for non linear Hessenberg systems whose faults are not isolable in steady state conditions. A stepwise procedure is proposed. The first step consists of the parameters estimation associated with one fault model when abnormal conditions are detected. As second step, a residual is calculated considering the identified model together with an auxiliary input to the system. The auxiliary signal added to the system allows the discrimination of two faults scenarios via features of the residual. Periodic auxiliary signal simplifies the features selection for classes of faults. Then, the novel procedure allows: (1) the identification of the fault parameters, if only one occurs and (2) the evaluation of some boundaries for the faults parameters, if two faults occurs simultaneously. To show the viability of the method, the leaks diagnosis in pipeline is considered as example.
