Xavier Olive

Diagnosability Analysis Based on Component-Supported Analytical Redundancy Relations

It is commonly accepted that the requirements for maintenance and diagnosis should be considered at the earliest stages of design. For this reason, methods for analyzing the diagnosability of a system and determining which sensors are needed to achieve the desired degree of diagnosability are highly valued. This paper clarifies the different diagnosability properties of a system and proposes a model-based method for: 1) assessing the level of discriminability of a system, i.e., given a set of sensors, the number of faults that can be discriminated, and its degree of diagnosability, i.e., the discriminability level related to the total number of anticipated faults; and 2) characterizing and determining the minimal additional sensors that guarantee a specified degree of diagnosability. The method takes advantage of the concept of component-supported analytical redundancy relation, which considers recent results crossing over the fault detection and isolation and diagnosis communities. It uses a model of the system to analyze in an exhaustive manner the analytical redundancies associated with the availability of sensors and performs from that a full diagnosability assessment. The method is applied to an industrial smart actuator that was used as a benchmark in the Development and Application of Methods for Actuator Diagnosis in Industrial Control Systems European project

Hybrid Systems Diagnosis by Coupling Continuous and Discrete Event Techniques

Abstract This paper deals with the problem of diagnosing systems that exhibit both continuous and discrete event dynamics. The proposed approach combines techniques from both continuous and discrete event diagnosis fields. On the on hand, an extension of the parity space approach is used to associate signatures to every operational mode of the system. On the other hand, signature switches arising from the transition from one mode to another are abstracted in the form of a set of events that capture the continuous dynamics. These events are merged into the original discrete dynamic model of the system, allowing us to apply the well-known discrete-event-systems diagnoser approach. This is illustrated on an example that shows the diagnosability improvement of the hybrid approach.

Minimal Structurally Overdetermined Sets for Residual Generation: A Comparison of Alternative Approaches

The issue of residual generation using structural analysis has been studied by several authors. Structural analysis does not permit to generate the analytical expressions of residuals since the model of the system is abstracted by its structure. However, it determines the set of constraints from which residuals can be generated and it provides the computation sequence to be used. This paper presents and compares four recently proposed algorithms that solve this problem.

FDIR for satellites

FDI(R) for satellites: How to deal with high availability and robustness in the space domain? The European leader for satellite systems and at the forefront of orbital infrastructures, Thales Alenia Space, is a joint venture between Thales (67%) and Finmeccanica (33%) and forms with Telespazio a Space Alliance. Thales Alenia Space is a worldwide reference in telecoms, radar and optical Earth observation, defence and security, navigation and science. It has 11 industrial sites in 4 European countries (France, Italy, Spain and Belgium) with over 7200 employees worldwide. Satellite evolution and the wish to design more autonomous missions imply the enhancement of the satellite architecture and special attention paid to fault management (i.e., Fault Detection, Isolation and Recovery, or FDIR, in space). Nevertheless, the constraints on FDIR techniques and strategies remain the same as for standard missions: robustness, reactive detection, quick isolation/identification and validation. This paper gives an introduction to Fault Tolerance (FT) in the space domain and some principles for the coming FT architectures. The current context of FDIR is presented by describing the approach implemented on telecommunication satellites and, more precisely, on one of the most FDIR sensible subsystems: the AOCS (Attitude and Orbit Control System). Following the current state of FDIR in the space domain, some perspectives are given such as a centralized distributed FDIR strategy for the next generation of autonomous satellites as well as some research tracks and hybrid diagnosis.

The PEGASE project: precise and scalable temporal analysis for aerospace communication systems with network calculus

With the increase of critical data exchanges in embedded real-time systems, the computation of tight upper bounds on network traversal times is becoming a crucial industrial need especially in safety critical systems. To address this need, the French project PEGASE grouping academics and industrial partners from the aerospace field has been undertaken to improve some key aspects of the Network Calculus and its implementation.

Active Diagnosis of Hybrid Systems Guided by Diagnosability Properties

Abstract On-line diagnosis must accommodate the existing sensoring capabilities of a system, which often results in limited diagnosability. However, in the context of hybrid systems, although faults may not be always discriminable, there are generally operating modes of the system in which they are. Active diagnosis relies on applying specific inputs to the system so as to exhibit additional symptoms that help refining the diagnosis. The idea of this paper is to use hybrid systems diagnosability analysis to drive the system towards modes with increased diagnosability with respect to safety considerations. The active diagnosis problem is formulated as a conditional planning problem. From an ambiguous state returned by the diagnoser, the plan defines how to find a controllable paths leading to a non ambiguous state. The decision about the active diagnosis actions is guided by the observable response of the system.

System-Software Co-Engineering: Dependability and Safety Perspective

The need for an integrated system-software co-engineering framework to support the design of modern space systems is pressing. The current tools and formalisms tend to be tailored to specific analysis techniques and are not amenable for the full spectrum of required system aspects such as safety, dependability and performability. Additionally, they cannot handle the intertwining of hardware and software interaction. As such, the current practices lack integration and coherence. We recently developed a coherent and multidisciplinary approach towards developing space systems at architectural design level, linking all of the aforementioned aspects, and assessed it with several industrial evaluations. This paper reports on the approach, the evaluations and our perspective on current and future developments.

On-line analytic redundancy relations instantiation guided by component discrete-dynamics for a class of non-linear hybrid systems

This paper addresses the diagnosis of hybrid systems switching between operating modes that undergo saturation behaviors. It proposes to generate non-linear parameterized ARRs, and to account for all regions of linear behavior, i.e. nominal, faulty and saturation regions, with automata representing the transitions between them at the level of each component. The parameters appearing in the ARRs are then provided by the states of the synchronized component automata and the ARRs needed to track the system mode are instantiated and checked on the fly, then reducing dramatically the required memory space and computation time. The proposed mode tracking algorithm has been tested on the Attitude Control System (ACS) of an industrial telecommunication satellite.

Optimizing ground station networks for free space optical communications: Maximizing the data transfer

Free space optical communications are becoming a mature technology to cope with the needs of high data rate pay-loads for future low-earth orbiting observation satellites. However, they are strongly impacted by clouds. In this paper , we aim to nd a network of optical ground stations maximizing the percentage of data acquired by a low-earth orbiting satellite that can be transferred to the Earth, taking into consideration cloud information. This problem can be separated in two parts and solved hierarchically: the selection of a network of optical ground stations and the assignment of downloads to visibility windows of the stations. We present theoretical and practical results regarding the complexity of the latter subproblem and propose a dynamic programming algorithm to solve it. We combine this algorithm with two methods for the enumeration of the stations , and compare them with a Mixed Integer Linear Program (MILP). Results show that even if the MILP can solve scenarios over small horizons, the hierarchical approaches outperform it in term of computation time while still achieving optimality for larger instances.

A hierarchical approach for the selection of optical ground stations maximizing the data transfer from low-earth observation satellites

For space industries, free-space optical communications are becoming a mature technology, but the impact of their use to download observations from spatial imagery systems has still to be evaluated. Unlike current radio-frequency technology, freespace optical communications are strongly impacted by weather conditions, and most notably by clouds. In order to cope with the later, it is necessary to achieve ground station diversity, i.e. having a network of optical ground stations able to receive data from satellites. In this paper, we aim to find a subset of a given number of ground stations maximizing the amount of data that can be downloaded from a low-earth orbiting satellite to the Earth during its missions. We present a Mixed Integer Linear Program model and a hierarchical method based on an exhaustive enumeration of the sets of stations and on a dynamic programming algorithm to solve it. The efficiency of this method is evaluated on several instances based on real ground station networks and on cloud cover throughout the last twenty years.