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Autonomous Power Expert (APEX) computer program is prototype expert-system program detecting faults in electrical-power-distribution system. Assists human operators in diagnosing faults and deciding what adjustments or repairs needed for immediate recovery from faults or for maintenance to correct initially nonthreatening conditions that could develop into faults. Written in Lisp.
A fault-tolerant power distribution system which includes a plurality of power sources and a plurality of nodes responsive thereto for supplying power to one or more loads associated with each node. Each node includes a plurality of switching circuits, each of which preferably uses a power field effect transistor which provides a diode operation when power is first applied to the nodes and which thereafter provides bi-directional current flow through the switching circuit in a manner such that a low voltage drop is produced in each direction. Each switching circuit includes circuitry for disabling the power field effect transistor when the current in the switching circuit exceeds a preselected value.
There is a trend in current spacecraft design to achieve greater fault tolerance through the implemenation of on-board software dedicated to detecting and isolating failures. A combination of hardware and software is utilized in the Galileo power system for autonomous fault recovery. Galileo is a dual-spun spacecraft designed to carry a number of scientific instruments into a series of orbits around the planet Jupiter. In addition to its self-contained scientific payload, it will also carry a probe system which will be separated from the spacecraft some 150 days prior to Jupiter encounter. The Galileo spacecraft is scheduled to be launched in 1985. Attention is given to the power system, the fault protection requirements, and the power fault recovery implementation.
Alternative methods for power flow and fault analysis of single-phase distribution systems are presented. The algorithms for both power flow and fault analysis utilize a generalized approach to network modeling. The generalized admittance matrix, formed using elements of linear graph theory, is an accurate network model for all possible single-phase network configurations. Unlike the standard nodal admittance matrix formulation algorithms, the generalized approach uses generalized component models for the transmission line and transformer. The standard assumption of a common node voltage reference point is not required to construct the generalized admittance matrix. Therefore, truly accurate simulation results can be obtained for networks that cannot be modeled using traditional techniques.
Power Distribution; Cabling, fault protection and switches to turn power on/off to spacecraft loads; Isolate loads from bus noise and regulate power to load against disturbances from the load and the bus; Protect the power distribution system from load failures.
Future space explorations will require long term human presence in space. Space environments that provide working and living quarters for manned missions are becoming increasingly larger and more sophisticated. Monitor and control of the space environment subsystems by expert system software, which emulate human reasoning processes, could maintain the health of the subsystems and help reduce the human workload. The autonomous power expert (APEX) system was developed to emulate a human expert's reasoning processes used to diagnose fault conditions in the domain of space power distribution. APEX is a fault detection, isolation, and recovery (FDIR) system, capable of autonomous monitoring and control of the power distribution system. APEX consists of a knowledge base, a data base, an inference engine, and various support and interface software. APEX provides the user with an easy-to-use interactive interface. When a fault is detected, APEX will inform the user of the detection. The user can direct APEX to isolate the probable cause of the fault. Once a fault has been isolated, the user can ask APEX to justify its fault isolation and to recommend actions to correct the fault. APEX implementation and capabilities are discussed.
The objective of this research is to conduct various fault simulation studies for diagnosing the type and location of faults in the power distribution system. Different types of faults are simulated at different locations within the distribution system and the faulted waveforms are monitored at measurable nodes such as at the output of the DDCU's. These fault signatures are processed using feature extractors such as FFT and wavelet transforms. The extracted features are fed to a clustering based neural network for training and subsequent testing using previously unseen data. Different load models consisting of constant impedance and constant power are used for the loads. Open circuit faults and short circuit faults are studied. It is concluded from present studies that using features extracted from wavelet transforms give better success rates during ANN testing. The trained ANN's are capable of diagnosing fault types and approximate locations in the solar dynamic power distribution system.
This study presents a methodology for fault diagnosis using a Two-Stage Artificial Neural Network Clustering Algorithm. Previously, SPICE models of a 5-bus DC power distribution system with assumed constant output power during contingencies from the DDCU were used to evaluate the ANN's fault diagnosis capabilities. This on-going study uses EMTP models of the components (distribution lines, SPDU, TPDU, loads) and power sources (DDCU) of Space Station Alpha's electrical Power Distribution System as a basis for the ANN fault diagnostic tool. The results from the two studies are contrasted. In the event of a major fault, ground controllers need the ability to identify the type of fault, isolate the fault to the orbital replaceable unit level and provide the necessary information for the power management expert system to optimally determine a degraded-mode load schedule. To accomplish these goals, the electrical power distribution system's architecture can be subdivided into three major classes: DC-DC converter to loads, DC Switching Unit (DCSU) to Main bus Switching Unit (MBSU), and Power Sources to DCSU. Each class which has its own electrical characteristics and operations, requires a unique fault analysis philosophy. This study identifies these philosophies as Riddles 1, 2 and 3 respectively. The results of the on-going study addresses Riddle-1. It is concluded in this study that the combination of the EMTP models of the DDCU, distribution cables and electrical loads yields a more accurate model of the behavior and in addition yielded more accurate fault diagnosis using ANN versus the results obtained with the SPICE models.
Power field-effect transistors reduce energy waste and simplify interconnections. Current switch containing power field-effect transistor (PFET) placed in series with each load in fault-tolerant power-distribution system. If system includes several loads and supplies, switches placed in series with adjacent loads and supplies. System of switches protects against overloads and losses of individual power sources.
Three Auxiliary Power Units (APU) on the Space Shuttle Orbiter each provide 145 hp shaft power to a hydraulic pump which outputs 3000 psi hydraulic fluid to 41 hydraulic actuators. A hydrazine fuel powered APU utilized throughout the Shuttle program has undergone many improvements, but concerns remain with flight safety, operational cost, critical failure modes, and hydrazine related hazards. The advanced hydraulic power system (AHPS), also known as the electric APU, is being evaluated as an upgrade to replace the hydrazine APU. The AHPS replaces the high-speed turbine and hydrazine fuel supply system with a battery power supply and electric motor/pump that converts 300 volt electrical power to 3000 psi hydraulic power. AHPS upgrade benefits include elimination of toxic hydrazine propellant to improve flight safety, reduction in hazardous ground processing operations, and improved reliability. Development of this upgrade provides many interesting challenges and includes development of four hardware elements that comprise the AHPS system: Battery - The battery provides a high voltage supply of power using lithium ion cells. This is a large battery that must provide 28 kilowatt hours of energy over 99 minutes of operation at 300 volts with a peak power of 130 kilowatts for three seconds. High Voltage Power Distribution and Control (PD&C) - The PD&C distributes electric power from the battery to the EHDU. This 300 volt system includes wiring and components necessary to distribute power and provide fault current protection. Electro-Hydraulic Drive Unit (EHDU) - The EHDU converts electric input power to hydraulic output power. The EHDU must provide over 90 kilowatts of stable, output hydraulic power at 3000 psi with high efficiency and rapid response time. Cooling System - The cooling system provides thermal control of the Orbiter hydraulic fluid and EHDU electronic components. Symposium presentation will provide an overview of the AHPS upgrade, descriptions of the four hardware elements, and a summary of development results to date.
The NASA Glenn Research Center, partner universities, and defense contractors are working to develop intelligent power management and distribution (PMAD) technologies for future spacecraft and launch vehicles. The goals are to provide higher performance (efficiency, transient response, and stability), higher fault tolerance, and higher reliability through the application of digital control and communication technologies. It is also expected that these technologies will eventually reduce the design, development, manufacturing, and integration costs for large, electrical power systems for space vehicles. The main focus of this research has been to incorporate digital control, communications, and intelligent algorithms into power electronic devices such as direct-current to direct-current (dc-dc) converters and protective switchgear. These technologies, in turn, will enable revolutionary changes in the way electrical power systems are designed, developed, configured, and integrated in aerospace vehicles and satellites. Initial successes in integrating modern, digital controllers have proven that transient response performance can be improved using advanced nonlinear control algorithms. One technology being developed includes the detection of "soft faults," those not typically covered by current systems in use today. Soft faults include arcing faults, corona discharge faults, and undetected leakage currents. Using digital control and advanced signal analysis algorithms, we have shown that it is possible to reliably detect arcing faults in high-voltage dc power distribution systems (see the preceding photograph). Another research effort has shown that low-level leakage faults and cable degradation can be detected by analyzing power system parameters over time. This additional fault detection capability will result in higher reliability for long-lived power systems such as reusable launch vehicles and space exploration missions.
The autonomous power expert (APEX) system is being developed at Lewis Research Center to function as a fault diagnosis advisor for a space power distribution test bed. APEX is a rule-based system capable of detecting faults and isolating the probable causes. APEX also has a justification facility to provide natural language explanations about conclusions reached during fault isolation. To help maintain the health of the power distribution system, additional capabilities were added to APEX. These capabilities allow detection and isolation of incipient faults and enable the expert system to recommend actions/procedure to correct the suspected fault conditions. New capabilities for incipient fault detection consist of storage and analysis of historical data and new user interface displays. After the cause of a fault is determined, appropriate recommended actions are selected by rule-based inferencing which provides corrective/extended test procedures. Color graphics displays and improved mouse-selectable menus were also added to provide a friendlier user interface. A discussion of APEX in general and a more detailed description of the incipient detection, recommended actions, and user interface developments during the last year are presented.
Outer planet spacecraft have unique requirements that differentiate them from inner planet and Earth orbiter spacecraft. To meet these requirements, the Voyager and Galileo Power Management And Distribution (PMAD) architectures employed shunt regulation and carried on the Mariner tradition of AC power distribution to many of the user loads. Also, autonomous fault recovery was achieved by automatic responses in hardware and software recovery routines. Finally, power distribution switching was expanded to allow for removal of the most trivial load element as the nuclear source depleted itself. The design cycle has begun for a third generation spacecraft set named Comet Rendezvous Asteroid Flyby (CRAF) and Cassini (a saturn orbiter). In their power systems, AC power distribution, relay/fuse load switching, and fault protection will give way to the advantages of DC power and solid state load switches.
We describe a diagnosis algorithm entered into the Second International Diagnostic Competition. We focus on the first diagnostic problem of the industrial track of the competition in which a diagnosis algorithm must detect, isolate, and identify faults in an electrical power distribution testbed and provide corresponding recovery recommendations. The diagnosis algorithm embodies a model-based approach, centered around qualitative event-based fault isolation. Faults produce deviations in measured values from model-predicted values. The sequence of these deviations is matched to those predicted by the model in order to isolate faults. We augment this approach with model-based fault identification, which determines fault parameters and helps to further isolate faults. We describe the diagnosis approach, provide diagnosis results from running the algorithm on provided example scenarios, and discuss the issues faced, and lessons learned, from implementing the approach
Major objectives, milestones, key contacts, technology issues, accomplishments, and candidate programs are outlined. Topics addressed include: advanced avionics systems architectures; advanced information processing; avionics concepts; integrated Global Positioning System/guidance, navigation, and command concepts; advanced communication and telemetry; display and control concepts; advanced sensors and instrumentation; fault detection and fault management; advanced electric power, distribution, and control; EMA/power systems; and in-flight crew training. This presentation is represented by viewgraphs only.
A summary of findings of the Flight Elements Subpanel is given in viewgraph form. Topics covered include advanced avionics architecture; processors; integrated Global Positioning System and guidance, navigation and control; displays and controls; telemetry; sensors and instrumentation; fault detection and management; electrical power distribution and control; spacecraft power supplies; and in-flight crew training.
A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base.
The space station uses precision rotary gimbals to provide for sun tracking of its photoelectric arrays. Electrical power, command signals and data are transferred across the gimbals by roll rings. Roll rings have been shown to be capable of highly efficient electrical transmission and long life, through tests conducted at the NASA Lewis Research Center and Honeywell's Satellite and Space Systems Division in Phoenix, AZ. Large potential fault currents inherent to the power system's DC distribution architecture, have brought about the need to evaluate the effects of large transient fault currents on roll rings. A test recently conducted at Lewis subjected a roll ring to a simulated worst case space station electrical fault. The system model used to obtain the fault profile is described, along with details of the reduced order circuit that was used to simulate the fault. Test results comparing roll ring performance before and after the fault are also presented.