 |
Unmanned
Aerial Systems |
Complex
Systems Engineering and Analysis |
Smart
Sensors as a Standalone System |
| SYSTEM
MODEL |
•Dynamic Models
•Noise Measurement and Modeling
• Failure Characterization (Navigation Sensors and Subsystems)
• Prognostics based on Complex System Modeling
• Diagnostics with High Performance Real Time Artificial
Neural Networks (ONGFE and Collaborative Learning Engine).
• Incremental Learning based on Collaborative Learning
Engine and Artificial Neural Networks
|
•Failure Evolution Characterization
• Incremental Learning based on Collaborative Learning
Engine and Artificial Neural Networks
•Automated Analysis by Health Monitoring
• Stochastic Modeling and Analysis
•Operational Conditions Emulation by high-level Control
and Hierarchical System Models.
•Data-Driven Models by the ONGFE
•Custom Physics based Modeling for UAVs, UGVs, and Tactical
Systems (Kinematics, Dynamics, and Control)
|
• Sensor Design for Optimized
Size, Weight, and Power (< 100µA for Wired Communication).
• Power Consumption Models
• Layered Model based upon IEEE 1451.0 (with Optional
Full Compliance)
• Small Footprint Data-Driven Diagnostics and Prognostics
with High Performance Real Time Artificial Neural Networks (ONGFE
and Collaborative Learning Engine). |
| RELATED
TECHNOLOGIES |
• Autonomous
Learning
• Sensor and System Design for Optimized Size, Weight,
and Power
• Regression by ANNs
• Pattern Recognition by supervised, unsupervised, and
hybrid schemes
• Fast Embedded Learning
• Automated Feature Selection
• Man Machine Interfaces (On-Ground)
and Visualization
• Real Time Processing and on-board Computing
• FMEA |
• Autonomous Learning
•Regression by ANNs
•Bayesian Learning
•Stochastic Expert Systems
•Pattern Recognition by supervised, unsupervised, and
hybrid schemes
•Fast Embedded Learning
•Automated Feature Selection
•System Modeling and Automated Analysis
•Man Machine Interfaces and Visualization
•Real Time Processing
•Software Integration (COTS and Open Source)
•Testbeds for V&V |
• Ruggedized Hand-Held Devices
Design
• Energy Harvesting
• Sensor and System Design for Optimized Size, Weight,
and Power
• Regression by ANNs
• Pattern Recognition by supervised, unsupervised, and
hybrid schemes
• Fast Embedded Learning
• Real Time Processing
• Incremental Learning
• Automated Feature Selection
• Man Machine Interfaces and Visualization
• MIL-STD-810G |
| PATENTS |
•ONGFE: US Patent
2011/0167024 A1
•eCLE: US Provisional Application #61/633,374
•CRE-SSN: U.S. Provisional Application #61/849,108
|
•ONGFE: US Patent 2011/0167024
A1
•eCLE: US Provisional Application #61/633,374
•CRE-SSN: U.S. Provisional Application #61/849,108 |
•ONGFE: US Patent 2011/0167024
A1
•eCLE: US Provisional Application #61/633,374
•CRE-SSN: U.S. Provisional Application #61/849,108 |
| COMMUNICATIONS |
•Zigbee (IEEE
802.15.4)
•Bluetooth
•Wired Communications
•High Speed Wireless Data Links
• IEEE 1451.0 (Optional)
|
•Client-Server Enterprise
Technologies
•Cellular Networks
•Smart Mobile Devices (smart phone, tablets)
|
•Wired Communication (I2C,
SPI, and UART)
Options
•Thru-Metal Communication (Ultrasound)
•Wireless Communication |
| HARDWARE |
• CRE-SSN (Smart
Sensor Node)
•MicroElectroMechanical Systems
•Ultra-low Power Processors (microcontroller, microprocessors,
and DSP)
•PC104, PC104-Plus, Single Board Computer, Smart Devices
(android, iPhone, and tablets), Power PC, ruggedized mobile
computers
•ASIC-Analog/Mixed-mode
•Electromechanical Design
•CNC Machines
•PCB Layout
•Circuit Simulation/ Analysis
•EMI
•Firmware (FPGA) Development |
•LAN/WAN
•Smart Devices Integration (android, iPhone, and tablets)
and Power PC.
Ruggedized Mobile Computers |
•CRE-SSN Baseline (Customizable)
•Ultra-low Power Processors (microcontroller, microprocessors,
and DSP)
•Access to Hand-Held Ruggedized Devices with MIL-STD-810G
Compliance |
| SOFTWARE |
•Optimized Neuro
Genetic Fast Estimator (ONGFE)
• Machine Evolutionary Behavior by Embedded Collaborative
Learning Engine (eCLE).
• Automated Feature Selection Toolbox
•Unsupervised clustering toolbox
•Proprietary Collaborative Learning Toolbox
•Real Time Interface Software
•Windows CE
•Unix
•Embedded OS |
•
coremicro® Real-Time Structure Health Monitoring Kernel
(RTSHM-Kernel)
•Optimized Neuro Genetic Fast Estimator (ONGFE)
• Machine Evolutionary Behavior by Embedded Collaborative
Learning Engine (eCLE).
• Automated Feature Selection Toolbox
•Unsupervised clustering toolbox
•Proprietary Collaborative Learning Toolbox
•Real Time Interface Software
•Windows CE
•Unix
•Embedded OS |
•Optimized
Neuro Genetic Fast Estimator (ONGFE)
• coremicro® Real-Time Structure Health Monitoring
Kernel (RTSHM-Kernel)
• Machine Evolutionary Behavior by Embedded Collaborative
Learning Engine (eCLE).
• Automated Feature Selection Toolbox
•Unsupervised clustering toolbox
•Proprietary Collaborative Learning Toolbox
•Real Time Interface Software
•Windows CE
•Unix
•Embedded OS |
| SENSOR
SUITE |
•Strain Gages
•PZT sensors
•Accelerometers
•Inertial Measurement Unit
•MEMS Sensors
•GPS
|
•Strain Gages
•PZT sensors
•Accelerometers
•MEMS sensors
|
•Pressure
•Flow
•Accelerometers
•PZT sensors
•Temperature
•MEMS sensors |
