scholarly journals Model-Based Fault Detection and Diagnosis for Spacecraft with an Application for the SONATE Triple Cube Nano-Satellite

Aerospace ◽  
2019 ◽  
Vol 6 (10) ◽  
pp. 105 ◽  
Author(s):  
Kirill Djebko ◽  
Frank Puppe ◽  
Hakan Kayal
Keyword(s):  
Fault Detection ◽  
Detection System ◽  
Fault Detection And Diagnosis ◽  
Generic Model ◽  
Diagnosis System ◽  
Counter Measures ◽  
Model Based ◽  
Human Operators ◽  
Detection And Diagnosis ◽  
Mission Operation

The correct behavior of spacecraft components is the foundation of unhindered mission operation. However, no technical system is free of wear and degradation. A malfunction of one single component might significantly alter the behavior of the whole spacecraft and may even lead to a complete mission failure. Therefore, abnormal component behavior must be detected early in order to be able to perform counter measures. A dedicated fault detection system can be employed, as opposed to classical health monitoring, performed by human operators, to decrease the response time to a malfunction. In this paper, we present a generic model-based diagnosis system, which detects faults by analyzing the spacecraft’s housekeeping data. The observed behavior of the spacecraft components, given by the housekeeping data is compared to their expected behavior, obtained through simulation. Each discrepancy between the observed and the expected behavior of a component generates a so-called symptom. Given the symptoms, the diagnoses are derived by computing sets of components whose malfunction might cause the observed discrepancies. We demonstrate the applicability of the diagnosis system by using modified housekeeping data of the qualification model of an actual spacecraft and outline the advantages and drawbacks of our approach.

The Fault Detection and Diagnosis System of Hydraulic Excavator Based on PXI Interface Technology

2012 ◽  
Vol 268-270 ◽  
pp. 1440-1443
Author(s):  
Liang Mi ◽  
Keng Feng ◽  
Huan Liang Li ◽  
Li Fu Shao
Keyword(s):  
Fault Detection ◽  
Data Storage ◽  
Detection System ◽  
Management Control ◽  
Fault Detection And Diagnosis ◽  
Circuit Board ◽  
Hydraulic Excavator ◽  
Electrical System ◽  
Diagnosis System ◽  
Detection And Diagnosis

The fault detection and diagnosis system, which uses dedicated interface adapter unit and PXI interface modules to perform signal excitation and parameter testing, is introduced in this paper. Its firmware consists of PXI-bus control computer, display control unit, dedicated interface adapter unit, connection cable and power supply unit. The dedicated interface adapter unit (IAU) is the core of hardware platform, and is composed of chassis, I2C-bus data acquisition board, adapter and military aviation sockets. It carries out analog to digital, digital to analog, digital I/O transformation as well as serial communication and CAN-bus communication. The software of the fault detection system is of hierarchical modular structure with integration of system management control, fault detection and circuit hardware driver modules together with repair and diagnosis database. The software provides functions of human-machine interaction, equipment fault detection, fault diagnosis and analysis, repair guidance and data storage. Therefore, this system can implement fault detection of hydraulic excavator on replaceable circuit board and block of the hydraulic system or electrical system. And it can help equipment repairmen and operator perform quick repairs and maintenance to the electrical system and hydraulic circuit of the excavator.

Model-based fault detection and diagnosis for hydraulic braking systems

2003 ◽  
Vol 36 (5) ◽  
pp. 307-312 ◽  
Author(s):  
Harald Straky ◽  
Marco Muenchhof ◽  
Rolf Isermann
Keyword(s):  
Fault Detection ◽  
Fault Detection And Diagnosis ◽  
Model Based ◽  
Detection And Diagnosis

Fault Diagnosis System of Engineering Equipment's Electrical System Using Dedicated Interface Adapter Unit

2013 ◽  
Vol 567 ◽  
pp. 155-160
Author(s):  
Yan Xi Ren ◽  
Xiao Qiang Yang ◽  
Qing Xia Li ◽  
Jun Da Chen
Keyword(s):  
Fault Detection ◽  
Fault Detection And Diagnosis ◽  
Object Oriented Programming ◽  
Circuit Board ◽  
Electrical System ◽  
Software Module ◽  
Master Program ◽  
Diagnosis System ◽  
Detection And Diagnosis ◽  
Signal Interface

The development of fault detection and diagnosis system is accomplished with the application of PXI interface technology, modular instrument and signal processing technology. The total technical scheme of host computer, portable test platform, signal adapter unit, test interface and cable together with peripheral components is introduced in the presented system. Consequently, the hardware includes master computer (fault test and diagnosis platform), PXI-bus data acquisition system, signal interface adapter, power supply system, interface unit, connection cable and peripheral dedicated test equipments. And the software is developed by C and LabWindows/CVI based on Win32 operating system. In addition, the modular and object-oriented programming are adopted in the software development. The software consists of three parts: the master program running on test and diagnosis platform, the client software module on signal adapter unit as well as the remote interface software module. It can implement fault detection of electrical system on replaceable circuit board and block of the hydraulic system or electrical system. So it can help equipment repairmen and operator perform quick repairs and maintenance to the electrical system for engineering equipment.

scholarly journals Fault Diagnosis in a Centrifugal Pump Using Active Magnetic Bearings

2004 ◽  
Vol 10 (3) ◽  
pp. 183-191 ◽  
Author(s):  
Rainer Nordmann ◽  
Martin Aenis
Keyword(s):  
Fault Detection ◽  
Centrifugal Pump ◽  
Fault Detection And Diagnosis ◽  
Magnetic Bearings ◽  
Diagnostic Tools ◽  
Contactless Measurement ◽  
Active Magnetic Bearings ◽  
Model Based ◽  
Detection And Diagnosis ◽  
Conventional Systems

The number of rotors running in active magnetic bearings (AMBs) has increased over the last few years. These systems offer a great variety of advantages compared to conventional systems. The aim of this article is to use the AMBs together with a developed built-in software for identification, fault detection, and diagnosis in a centrifugal pump. A single-stage pump representing the turbomachines is investigated. During full operation of the pump, the AMBs are used as actuators to generate defined motions respectively forces as well as very precise sensor elements for the contactless measurement of the responding displacements and forces. In the linear case, meaning small motions around an operating point, it is possible to derive compliance frequency response functions from the acquired data. Based on these functions, a model-based fault detection and diagnosis is developed which facilitates the detection of faults compared to state-of-the-art diagnostic tools which are only based on the measurement of the systems outputs, i.e., displacements. In this article, the different steps of the model-based diagnosis, which are modeling, generation of significant features, respectively symptoms, fault detection, and the diagnosis procedure itself are presented and in particular, it is shown how an exemplary fault is detected and identified.

Towards the Integration of Mobile Augmented Reality within an Aluminium Process Fault Detection and Diagnosis System

2013 ◽  
Vol 845 ◽  
pp. 703-707 ◽  
Author(s):  
Abd Majid Nazatul Aini ◽  
Haslina Arshad
Keyword(s):  
Augmented Reality ◽  
Fault Detection ◽  
Fault Detection And Diagnosis ◽  
Industrial Plant ◽  
Mobile Augmented Reality ◽  
Design Quality ◽  
Diagnosis System ◽  
Aluminium Smelting ◽  
Detection And Diagnosis ◽  
Mobile Ar

Mobile Augmented Reality (AR), which mixes the real world and the virtual world on hand-held devices, is a growing area of the manufacturing industry. Since mobile AR can be used to augment a users view of an industry plant, it provides alternative solutions for design, quality control, monitoring and control, service, and maintenance in complex process industries, such as the aluminium smelting industry. The objective of this paper is to discuss the integration of mobile AR within an aluminium industrial plant, in order to achieve effective fault detection and diagnosis. The possible integration of mobile AR within an aluminium fault detection and diagnosis system is shown with regard to four main functions, namely (1) plant information system, (2) fault history, (3) interactive troubleshooting, and (4) statistical analysis results. This paper opens up possible future works, where the potential use of mobile AR can be explored as an additional user interface component, for increasing the effectiveness of process monitoring within the aluminium smelting process.

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