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Morrell, F. R.

Publications and source records attributed to Morrell, F. R..

Flight test results of failure detection and isolation algorithms for a redundant strapdown inertial measurement unit

Flight test results for two sensor fault-tolerant algorithms developed for a redundant strapdown inertial measurement unit are presented. The inertial measurement unit (IMU) consists of four two-degrees-of-freedom gyros and accelerometers mounted on the faces of a semi-octahedron. Fault tolerance is provided by edge vector test and generalized likelihood test algorithms, each of which can provide dual fail-operational capability for the IMU. To detect the wide range of failure magnitudes in inertial sensors, which provide flight crucial information for flight control and navigation, failure detection and isolation are developed in terms of a multi level structure. Threshold compensation techniques, developed to enhance the sensitivity of the failure detection process to navigation level failures, are presented. Four flight tests were conducted in a commercial transport-type environment to compare and determine the performance of the failure detection and isolation methods. Dual flight processors enabled concurrent tests for the algorithms. Failure signals such as hard-over, null, or bias shift, were added to the sensor outputs as simple or multiple failures during the flights. Both algorithms provided timely detection and isolation of flight control level failures. The generalized likelihood test algorithm provided more timely detection of low-level sensor failures, but it produced one false isolation. Both algorithms demonstrated the capability to provide dual fail-operational performance for the skewed array of inertial sensors.

Morrell, F. R.

Flight demonstration of redundancy management algorithms for a skewed array of inertial sensors

Flight test results for two fault-tolerance algorithms developed for a redundant strapdown inertial measurement unit consisting of four 2-DOF gyros and accelerometers mounted on the faces of a semioctahedron are presented. Although both algorithms provided timely detection and isolation of flight control level failures, the generalized likelihood test algorithm provided more timely detection and isolation of low-level sensor failures than the edge vector test algorithm. The generalized likelihood test produced a false isolation for the case of a dual low-level failure applied to the sensitive axes of an accelerometer. Both of the algorithms were shown to provide dual fail-operational performance for the skewed array of inertial sensors.

Morrell, F. R.

Flight test results of a vector-based failure detection and isolation algorithm for a redundant strapdown inertial measurement unit

Flight test results of a vector-based fault-tolerant algorithm for a redundant strapdown inertial measurement unit are presented. Because the inertial sensors provide flight-critical information for flight control and navigation, failure detection and isolation is developed in terms of a multi-level structure. Threshold compensation techniques for gyros and accelerometers, developed to enhance the sensitivity of the failure detection process to low-level failures, are presented. Four flight tests, conducted in a commercial transport type environment, were used to determine the ability of the failure detection and isolation algorithm to detect failure signals, such a hard-over, null, or bias shifts. The algorithm provided timely detection and correct isolation of flight control- and low-level failures. The flight tests of the vector-based algorithm demonstrated its capability to provide false alarm free dual fail-operational performance for the skewed array of inertial sensors.

Morrell, F. R.

Evaluation of a dual processor implementation for a fault inferring nonlinear detection system

The design of a modified fault inferring nonlinear detection system (FINDS) algorithm for a dual-processor configured flight computer is described. The algorithm was changed in order to divide it into its translational dynamics and rotational kinematics and to use it for parallel execution on the flight computer. The FINDS consists of: (1) a no-fail filter (NFF), (2) a set of test-of-mean detection tests, (3) a bank of first order filters to estimate failure levels in individual sensors, and (4) a decision function. NFF filter performance using flight recorded sensor data is analyzed using a filter autoinitialization routine. The failure detection and isolation capability of the partitioned algorithm is evaluated. A multirate implementation for the bias-free and bias filter gain and covariance matrices is discussed.

Godiwala, P. M.

Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

The modifications to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance are summarized. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of gain update frequency, are also presented.

Caglayan, A. K.

Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

This paper summarizes the modifications made to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of an update frequency, are also presented.

Caglayan, A. K.

Performance analysis of a fault inferring nonlinear detection system algorithm with integrated avionics flight data

This paper presents the performance analysis results of a fault inferring nonlinear detection system (FINDS) using integrated avionics sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. First, an overview of the FINDS algorithm structure is given. Then, aircraft state estimate time histories and statistics for the flight data sensors are discussed. This is followed by an explanation of modifications made to the detection and decision functions in FINDS to improve false alarm and failure detection performance. Next, the failure detection and false alarm performance of the FINDS algorithm are analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minutes of flight data. Results indicate that the detection speed, failure level estimation, and false alarm performance show a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed is faster for filter measurement sensors such as MLS than for filter input sensors such as flight control accelerometers. Finally, the progress in modifications of the FINDS algorithm design to accommodate flight computer constraints is discussed.

Caglayan, A. K.

Flight test configuration for verifying inertial sensor redundancy management techniques

The Redundant Strapdown Inertial Measurement Unit presently tested in flight configuration consists of a semioctahedral array of four dynamically tuned, two-degree-of-freedom (TDOF) gyros and four TDOF accelerometers which can provide dual, fail-operational performance for integrated avionics systems. Attention is given to the multilevel algorithm used for the detection and isolation of three ranges of sensor failure in an integrated avionics context. A technique for the generation of accelerometer and gyro error thresholds which is sensitive to dynamic sensor errors and separation effects is presented, together with simulation results. Emphasis is placed on the ensuring of highly reliable data for flight control/navigation functions, while minimizing false or missed alarms.

Bryant, W. H.

Unified analysis methods for a fault tolerant redundant strapdown inertial measurement unit

The use of a redundant strapdown inertial measurement unit (RSDIMU) has been considered as a source of sensor information for future aircraft. It is pointed out that failure detection and isolation (FDI) should be accomplished at the sensor level to ensure the accurate transfer of information to elements of the integrated avionics system. The present investigation is concerned with the impact of the FDI algorithm on system reliability and vice versa. A description is given of a technique to identify and assess critical areas of reliability requirements for the RSDIMU. Attention is given to the development of an FDI algorithm to meet these requirements.

Morrell, F. R.

Description of a dual fail operational redundant strapdown inertial measurement unit for integrated avionics systems research

An experimental redundant strapdown inertial measurement unit (RSDIMU) is developed as a link to satisfy safety and reliability considerations in the integrated avionics concept. The unit includes four two degree-of-freedom tuned rotor gyros, and four accelerometers in a skewed and separable semioctahedral array. These sensors are coupled to four microprocessors which compensate sensor errors. These microprocessors are interfaced with two flight computers which process failure detection, isolation, redundancy management, and general flight control/navigation algorithms. Since the RSDIMU is a developmental unit, it is imperative that the flight computers provide special visibility and facility in algorithm modification.

Bryant, W. H.

Description of a dual fail-operational redundant strapdown inertial measurement unit for integrated avionics systems research

Attention is given to a redundant strapdown inertial measurement unit for integrated avionics. The system consists of four two-degree-of-freedom turned rotor gyros and four two-degree-of-freedom accelerometers in a skewed and separable semi-octahedral array. The unit is coupled through instrument electronics to two flight computers which compensate sensor errors. The flight computers are interfaced to the microprocessors and process failure detection, isolation, redundancy management and flight control/navigation algorithms. The unit provides dual fail-operational performance and has data processing frequencies consistent with integrated avionics concepts presently planned.

Bryant, W. H.

Design of a developmental dual fail operational redundant strapped down inertial measurement unit

An experimental redundant strap-down inertial measurement unit (RSDIMU) is being developed at NASA-Langley as a link to satisfy safety and reliability considerations in the integrated avionics concept. The unit consists of four two-degrees-of-freedom (TDOF) tuned-rotor gyros, and four TDOF pendulous accelerometers in a skewed and separable semi-octahedron array. The system will be used to examine failure detection and isolation techniques, redundancy management rules, and optimal threshold levels for various flight configurations. The major characteristics of the RSDIMU hardware and software design, and its use as a research tool are described.

Morrell, F. R.

A laboratory simulation of a single-axis dual-level precision pointing system

The laboratory simulation of a scaled single-axis dual-level control system for a large space telescope is demonstrated. The dual-level control system consists of a coarse-body-pointing system and a fine-pointing system, which uses an image motion compensator, an image dissector tube, and digital electronics. The results of the simulation indicate that the dual-level system can be used to provide tracking capability within one-tenth of a diffraction-limited image diameter of a 3-meter f/100 telescope for stars up to a +12.3 visual magnitude.

Bullock, G. F.