scholarly journals An IMM-GLR Approach for Marine Gas Turbine Gas Path Fault Diagnosis

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Qingcai Yang ◽  
Shuying Li ◽  
Yunpeng Cao
Keyword(s):  
Gas Turbine ◽  
Estimation Algorithm ◽  
Health Condition ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Multiple Faults ◽  
Fault Severity ◽  
Model Set ◽  
Gas Path Fault ◽  
Update Strategy

An IMM-GLR approach based on interacting multiple model (IMM) and generalized likelihood ratio (GLR) estimation was developed to detect, isolate, and estimate gas turbine gas path fault (including abrupt fault and multiple faults) in the underdetermine estimation conditions. In this approach, a model set representing gas turbine health condition and different fault condition was established, and a corresponding bank of filters was designed. An IMM-based FDI algorithm based on these filters is applied to detect and isolate fault, and a GLR estimation algorithm is used to estimate the fault severity. Then a model set update strategy based on the diagnosed fault was proposed to enable the diagnosis of multiple faults. Several simulation case studies on a marine gas turbine were conducted, and the results show that the IMM-GLR approach not only accurately diagnoses the abrupt gas path fault and multiple gas path faults but also accurately estimates the severity of the detected fault in the underdetermine estimation conditions.

Polynomial Model Set and its Interacting Multiple Model Algorithms

2012 ◽  
Vol 562-564 ◽  
pp. 2038-2044
Author(s):  
Jin Xiao Zhao ◽  
Jian Qiu Zhang ◽  
Dong Ming Zhou
Keyword(s):  
Sampling Interval ◽  
Polynomial Model ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Geometrical Properties ◽  
Filter Performance ◽  
Maneuvering Target ◽  
Polynomial Curve ◽  
Motion Modes ◽  
Model Set

From the maneuvering target orbit on the geometrical properties, according to different motion modes track corresponding to different order number polynomial curve, using the least squares fitting structure, this paper gives out a group of various motion modes matching the mathematical model—polynomial model set (PMS), and gives distinct mathematical process. PMS covers all the motion modes theoretically, easy to choose according to the practical situation and expand, especially suitable for single model can not accurately describe the complex sports scene. The model need not consider sampling interval, without lowering the filter performance at the same time, reduced prior knowledge dependence. Finally, simulation results indicate that the correctness and validity and practicality.

scholarly journals Multi-Fault Diagnosis Approach Based on Updated Interacting Multiple Model for Aviation Hydraulic Actuator

Information ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 410
Author(s):  
Xiaozhe Sun ◽  
Xingjian Wang ◽  
Siru Lin
Keyword(s):  
Fault Diagnosis ◽  
Flight Control ◽  
Failure Modes ◽  
Physical Parameters ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Hydraulic Actuator ◽  
Multiple Faults ◽  
Actuation System ◽  
Diagnosis Method

The aviation hydraulic actuator (HA) is a key component of the flight control system in an aircraft. It is necessary to consider the occurrence of multiple faults under harsh conditions during a flight. This study designs a multi-fault diagnosis method based on the updated interacting multiple model (UIMM). The correspondence between the failure modes and the key physical parameters of HA is found by analyzing the fault mode and mechanism. The key physical parameters of HA can be estimated by employing a series of extended Kalman filters (EKF) related to the different modes of HA. The models in UIMM are updated once the fault is determined. UIMM can reduce the number of fault models and avoid combinatorial explosion in the case of multiple faults. Simulation results indicate that the multi-fault diagnosis method based on UIMM is effective for multi-fault diagnosis of electro-hydraulic servo actuation system.

scholarly journals Roll Angle Estimation Algorithm of Geomagnetic/Gyro Combination Based on an Interacting Multiple-Model Kalman Filter

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jian-li Su ◽  
Hua Wang
Keyword(s):  
Kalman Filter ◽  
Measurement Accuracy ◽  
Angular Rate ◽  
Estimation Algorithm ◽  
Roll Angle ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Calculation Results ◽  
Gyroscope Sensor ◽  
And Control

The knowledge of the geomagnetic and gyro information that can be used for projectile roll angle is decisive to apply trajectory correction and control law. In order to improve the measurement accuracy of projectile roll angle, an interacting multiple-model Kalman filter (IMMKF) algorithm using gyro angular rate information to geomagnetic sensor information is proposed. Firstly, the data acquisition module of the geomagnetic sensor and the gyroscope sensor is designed, and the test data of the sensors are obtained through the semiphysical experiments. Furthermore, according to the measurement accuracy of each sensor, the algorithm performs the IMMKF process on the geomagnetic/gyro information to get the roll angle. It can be proven by experiments and calculation results that the error of the roll angle obtained after processing by the IMMKF algorithm is close to 2°, which is better than the 5° calculated by adopting the Kalman filter directly with geomagnetic information.

Federated IMM-UKF Algorithm for Multi-Sensor Data Fusion

2013 ◽  
Vol 753-755 ◽  
pp. 2117-2120 ◽  
Author(s):  
Tian Lai Xu
Keyword(s):  
Data Fusion ◽  
Nonlinear Filtering ◽  
Adaptive Estimation ◽  
Estimation Method ◽  
Cost Effective ◽  
Estimation Algorithm ◽  
Sensor Data ◽  
Interacting Multiple Model ◽  
Integrated Navigation ◽  
Multiple Model

The accuracy of multi-sensor navigational data fusion by federated Kalman filter will be reduced in condition that the systems dynamics model is nonlinear and the noise statistical properties are unknown. To address this problem, a federated Interacting Multiple Model-Unscented Kalman Filteing (IMM-UKF) algorithm is presented. The UKF is a nonlinear estimation method which can achieve the accuracy at least to the second-order. The IMM estimation algorithm is one of the cost-effective adaptive estimation algorithm for systems involving parametric changes. The combination of IMM with UKF could deal with the problem of nonlinear filtering with uncertain noise. Simulation results show that the method can improve the accuracy of INS/GPS/odometer integrated navigation.

Variable-structure interacting multiple-model estimation for group targets tracking with random matrices

2017 ◽  
Vol 232 (7) ◽  
pp. 1201-1211
Author(s):  
Zhen-Xing Li ◽  
Yun Wang ◽  
Jin-Mang Liu ◽  
Ni Peng ◽  
Lin-Hai Gan
Keyword(s):  
Variable Structure ◽  
Weight Coefficient ◽  
Extended Model ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Weighting Method ◽  
Basic Model ◽  
Fixed Parameter ◽  
Model Set ◽  
Ema Method

In order to improve the estimation performance of interacting multiple model tracking algorithm for group targets, the expected-mode augmentation variable-structure interacting multiple model (EMA-VSIMM) and the best model augmentation variable-structure interacting multiple model (BMA-VSIMM) tracking algorithms are presented in this paper. First, by using the EMA method, a more proper expected-mode set has been chosen from the basic model set of group targets, which can make the selected tracking models better match up to the true mode. The BMA algorithm uses a fixed parameter model of different structures to constitute a candidate model set and selects a minimum difference model from target state as the present extended model from the set of candidates at real time. Second, in the filtering process of VSIMM, the fusion estimation of extension state is implemented by the scalar coefficients weighting method, where weight coefficient is calculated by the trace of the corresponding covariance matrix of extension state. The performances of the proposed EMA-VSIMM and BMA-VSIMM algorithms are evaluated via simulation of a generic group targets maneuvering tracking problem.

scholarly journals Adaptive Tracking Method for Non-Cooperative Continuously Thrusting Spacecraft

Aerospace ◽  
2021 ◽  
Vol 8 (9) ◽  
pp. 244
Author(s):  
Juqi Yin ◽  
Zhen Yang ◽  
Yazhong Luo
Keyword(s):  
Kalman Filter ◽  
Estimation Accuracy ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Tracking Method ◽  
Adaptive Tracking ◽  
Convergence Performance ◽  
Model Set ◽  
Traditional Approaches ◽  
A Current

Performance of the traditional Kalman filter and its variants can seriously degrade when they are used to track a non-cooperative continuously thrusting spacecraft. To overcome this shortcoming, an adaptive tracking method for relative state estimation of a non-cooperative target is proposed based on the interacting multiple model (IMM) algorithm. First, built upon a current statistical jerk (CSJerk) model, a robust CSJerk filtering (RCSJF) algorithm is developed, which can address the issue of low estimation accuracy and instability of traditional approaches at the moments when the spacecraft starts and ends thrusting. Second, the developed RCSJF algorithm is further used to form the model set of the IMM by incorporating different maximum jerk values, based on which an adaptive tracking method is presented that can track a non-cooperative target with different maneuvering levels. Simulation results show that the proposed method can effectively track the target across all thrusts levels under the conditions considered, and the convergence performance of the proposed method is improved in comparison to the CSJerk-based extended Kalman filter, especially at the start and end time of the maneuver.

scholarly journals An Interacting Multiple Model Approach for Target Intent Estimation at Urban Intersection for Application to Automated Driving Vehicle

2020 ◽  
Vol 10 (6) ◽  
pp. 2138 ◽  
Author(s):  
Donghoon Shin ◽  
Subin Yi ◽  
Kang-moon Park ◽  
Manbok Park
Keyword(s):  
Traffic Accidents ◽  
Estimation Algorithm ◽  
Driver Model ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Assistance Systems ◽  
Model Approach

Research shows that urban intersections are a hotspot for traffic accidents which cause major human injuries. Predicting turning, passing, and stop maneuvers against surrounding vehicles is considered to be fundamental for advanced driver assistance systems (ADAS), or automated driving systems in urban intersections. In order to estimate the target intent in such situations, an interacting multiple model (IMM)-based intersection-target-intent estimation algorithm is proposed. A driver model is developed to represent the driver’s maneuvering on the intersection using an IMM-based target intent classification algorithm. The performance of the intersection-target-intent estimation algorithm is examined through simulation studies. It is demonstrated that the intention of a target vehicle is successfully predicted based on observations at an individual intersection by proposed algorithms.

scholarly journals A Gas Path Fault Contribution Matrix for Marine Gas Turbine Diagnosis Based on a Multiple Model Fault Detection and Isolation Approach

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3316 ◽  
Author(s):  
Qingcai Yang ◽  
Shuying Li ◽  
Yunpeng Cao ◽  
Fengshou Gu ◽  
Ann Smith
Keyword(s):  
Fault Detection ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Fault Detection And Isolation ◽  
Multiple Model ◽  
Efficient Operation ◽  
Model Sets ◽  
Wide Range ◽  
Model Set

To ensure reliable and efficient operation of gas turbines, multiple model (MM) approaches have been extensively studied for online fault detection and isolation (FDI). However, current MM-FDI approaches are difficult to directly apply to gas path FDI, which is one of the common faults in gas turbines and is understood to mainly be due to the high complexity and computation in updating hypothetical gas path faults for online applications. In this paper, a fault contribution matrix (FCM) based MM-FDI approach is proposed to implement gas path FDI over a wide operating range. As the FCM is realized via an additive term of the healthy model set, the hypothetical models for various gas path faults can be easily established and updated online. In addition, a gap metric analysis method for operating points selection is also proposed, which yields the healthy model set from the equal intervals linearized models to approximate the nonlinearity of the gas turbine over a wide range of operating conditions with specified accuracy and computational efficiency. Simulation case studies conducted on a two-shaft marine gas turbine demonstrated the proposed approach is capable of adaptively updating hypothetical model sets to accurately differentiate both single and multiple faults of various gas path faults.

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