Chiman Kwan

A Complete Image Compression Scheme Based on Overlapped Block Transform with Post-Processing

A complete system was built for high-performance image compression based on overlapped block transform. Extensive simulations and comparative studies were carried out for still image compression including benchmark images (Lena and Barbara), synthetic aperture radar (SAR) images, and color images. We have achieved consistently better results than three commercial products in the market (a Summus wavelet codec, a baseline JPEG codec, and a JPEG-2000 codec) for most images that we used in this study. Included in the system are two post-processing techniques based on morphological and median filters for enhancing the perceptual quality of the reconstructed images. The proposed system also supports the enhancement of a small region of interest within an image, which is of interest in various applications such as target recognition and medical diagnosis

An intelligent hierarchical approach to actuator fault diagnosis and accommodation

This paper presents a novel intelligent hierarchical approach to automatically detecting, isolating, and accommodating faults in flight control systems. The proposed architecture has three main components. First, a new nonlinear fault diagnosis scheme is used to detect the occurrence of any faults and to determine the particular component that has failed. Second, a controller module consists of a primary nominal controller and a secondary adaptive fault-tolerant controller. While the nominal controller can be any existing conventional flight control system, the secondary neural network (NN) based nonlinear adaptive controller is designed to maintain acceptable control performance after the detection of fault occurrence. Third, a reconfiguration supervisor makes decision regarding controller reconfiguration and control reallocation by using on-line diagnostic information. Following failures of primary aerodynamic actuators, flight safety can be maintained by utilizing alternative actuation systems for critical stability and control augmentation tasks. The effectiveness of the proposed integrated fault diagnosis and accommodation approach has been illustrated by using the research civil aircraft model (RCAM) developed by the group for aeronautical research and technology in Europe (GARTEUR). Extensive simulation studies have clearly shown the benefits of the proposed adaptive fault-tolerant control scheme using on-line diagnostic information

Fault tolerant formation flight control of UAVs

In this paper, we summarise our recent results in fault tolerant formation control of Unmanned Air Vehicles (UAV). A fault tolerant control scheme to deal with both GPS sensor failure and wireless communication packet losses is presented. Moreover, some extensions to the formation control algorithms developed by UC Berkeley are made to support time-varying heading and curved flight trajectories. The effectiveness of the presented fault tolerant control scheme is illustrated by real-time formation flight simulations conducted in a wireless network environment. Both rotary and fixed wing UAVs, mesh and triangular formations, and straight and curved trajectories are considered in our real-time simulations.

Real-time adaptive on-line traffic incident detection

Abstract A new approach to traffic incident detection is proposed in this paper. The method consists of two stages. First, a real-time adaptive on-line procedure is used to extract the significant components of traffic states, namely, average velocity and density of moving vehicles. Second, we apply a new neural network called Fuzzy CMAC (Cerebellar Arithmetic Computer) to identify traffic incidents. Fuzzy CMAC is an ideal candidate for this purpose for the following reasons. First, the Fuzzy CMAC learning structure is a creative use of fuzzy logic and CMAC based neural networks. Expert knowledge in terms of linguistic rules can be incorporated into the design. Second, the learning process is well suited for real-time application since the training process is an order of magnitude faster than conventional neural nets. Third, the Fuzzy CMAC can be implemented in high speed, highly parallel hardware. The importance of this research is three-fold. One is that a good traffic incident detection system will help drivers to select an optimum route. The second one is that the system will be able to provide information for efficient dispatching of emergency services. Lastly, it will provide accurate knowledge of existing traffic conditions in order to guide effective on-line traffic controls.

Fault Detection and Identification in Aircraft Hydraulic Pumps Using MCA

Abstract Early detection of aircraft hydraulic pump failures is critical for safety of flights. Hydraulic pump failures are usually indicated by increasing noise-to-signal ratio in the case drain flow. In this paper, we present a robust scheme for detecting and identifying pump failures using minor component analysis. First, a residual model is generated off-line using sensor data collected under normal system operation conditions. Then the residual generation model can be used on-line to process new sensor data and detect any abnormal pump behaviors. Moreover, a novel Cault identification algorithm is derived to estimate the Cault size after Cault detection, which could be very useful for component remaining life prediction and fault isolation.

Mitigation of Chatter Instabilities in Milling by Active Structural Control

This report documents how active structural control was used to significantly enhance the metal removal rate of a milling machine. An active structural control system integrates actuators, sensors, a control law and a processor into a structure for the purpose of improving the dynamic characteristics of the structure. Sensors measure motion, and the control law, implemented in the processor, relates this motion to actuator forces. Closed-loop dynamics can be enhanced by proper control law design. Actuators and sensors were imbedded within a milling machine for the purpose of modifying dynamics in such a way that mechanical energy, produced during cutting, was absorbed. This limited the on-set of instabilities and allowed for greater depths of cut. Up to an order of magnitude improvement in metal removal rate was achieved using this system. Although demonstrations were very successful, the development of an industrial prototype awaits improvements in the technology. In particular, simpler system designs that assure controllability and observability and control algorithms that allow for adaptability need to be developed.

Early fire detection using acoustic emissions

Abstract Early detection of fire is important in many applications such as aircraft and warehouses. The use of acoustic emissions to detect fire has some distinct advantage such as fast response and wide coverage area. Here we present two methods to extract fire signatures from acoustic emission signals. The method based on Minor Component Analysis looks very promising. Experimental verification is included.

Actuator Fault Diagnosis and Accommodation for Flight Safety

This paper presents an adaptive fault diagnosis and accommodation scheme for aerodynamic actuators. The fault-tolerant control architecture consists of three main components: an online nonlinear fault detection and isolation scheme, a controller suite, and a reconfiguration supervisor which performs controller reconfiguration and control reallocation using online diagnostic information. The proposed scheme provides a unified architecture for fault detection, isolation and accommodation of actuator failures. Simulation studies using a nonlinear Beaver aircraft model have shown the effectiveness of the proposed scheme

ATR performance improvement using images with corrupted or missing pixels

Surveillance images downlinked from unmanned air vehicles (UAVs) may have corrupted pixels due to channel interferences from the adversary’s jammer. Moreover, the images may be deliberately downsampled in order to conserve the scarce bandwidth in UAVs. As a result, the automatic target recognition (ATR) performance may degrade significantly because of poor image quality due to corrupted and missing pixels. In this paper, we present some preliminary results of a novel approach to automatic target recognition based on corrupted images. First, we present a new matrix completion algorithm to reconstruct missing pixels in electro-optical (EO) images. Second, we extensively evaluated our algorithm using many EO images with different missing rates. It was observed that recovering performance in terms of peak signal-to-noise ratio (PSNR) is very good. Third, we compared with a state-of-the-art algorithm and found that our performance is superior. Finally, experiments using an ATR algorithm showed that the target detection performance (precision and recall) has been improved after applying our algorithm, as compared to those results generated by using interpolated images.

On the generation of high-spatial and high-spectral resolution images using THEMIS and TES for Mars exploration

In the 2015 NASA ROSES solicitation, NASA has expressed strong interest in improving the accuracy of Mars surface characterization using satellite images. Thermal Emission Imaging System (THEMIS), an imager with a spatial resolution of 100 meters, has 10 infrared bands between 6 and 15 micrometers. Thermal Emission Spectrometer (TES), an imager with a spatial resolution of 3 km, has 143 bands between 5 and 50 micrometers. While both imagers have a variety of applications, it would be ideal to generate high-spatial and high-spectral resolution data products by fusing their respective outputs. We present a novel approach to fusing THEMIS and TES satellite images, aiming to improve orbital characterization of Mars’ surface. First, the THEMIS bands must undergo atmospheric compensation (AC) due to the presence of dust, ice, carbon dioxide, etc. A systematic AC procedure using elevation information and spectrally uniform pixels has been developed and implemented. Second, a set of proven pan-sharpening algorithms has been applied to fuse the two sets of images. The pan-sharpened images have the spatial resolution of THEMIS images and the spectral resolution of TES images. The results of extensive experiments using THEMIS and TES data collected near the Syrtis Major region (one of the final 3 candidate landing sites for the Mars 2020 rover) clearly demonstrate the feasibility of the proposed approach.