Extensive experience with sensors and sensing systems in dozens of different products. Hardware design of the sensor, signal conditioning chain, ADC, and processor including component selection, schematic development, and PCB layout. With software architecture to match the chosen hardware, including the digital conditioning of the sensor data by selecting appropriate sampling frequencies, implementing digital filters, and applying any necessary corrections using calibration data, with the resultant data then used in real-time feedback systems and state machines to make control decisions; or displayed in the engineering units to display on an end-user GUI (as appropriate). Experience with multiple calibration techniques including linear and polynomial fits, use of manual and factory-provided calibration data, and more. Deep understanding of trade-offs associated with power consumption and sample rate, algorithm complexity and latency, conversion resolution and dynamic range, reference voltage power consumption and accuracy vs temperature, sensor size vs system performance, and all of the complex trade-offs in between.
- Summary
- System architect on dozens of designs which involved sensing systems, including all aspects of hardware and software design
- Deep understanding of design trade-offs between sensor size and performance, culminating in several products that are the world’s smallest RF and transducer systems.
- Vast experience with firmware use of sensor data including use in real-time system state machines, control loops, Kalman filtering, and calibration techniques
- Experience with managing end-user expectations of sensor data, including using appropriate engineering units and providing data in useful formats
- Sensor Types
- Inertial Sensors – gyroscopes and accelerometers
- Magnetic Sensors – reed switches, hall effect sensors, magnetometers
- Electric Sensors – current, voltage, resistance, capacitive
- Temperature Sensors – temperature ICs, thermocouples, thermistors
- Pressure Sensors – fluid and gas, absolute and gauge
- Flow Sensors – air flow, water flow, fuel flow
- Optical Sensors
- RF Power Sensors and other RF receivers
- Instrumentation Techniques
- Signal Conditioning – use of op amps and instrumentation amplifiers for active filtering and level-shifting, use of discrete capacitor/inductor/resistor networks for passive filtering and level-shifting
- Appropriate filter designs that minimize out-of-band (typically high frequency) noise that also satisfy the Nyquist sampling theorem, maintaining original signal integrity to the extent possible once converted into the digital domain
- Designs that are ratiometric to power supply voltage and designs that are absolute
- Analog Output Sensors – Wheatstone bridges, variable resistance, and voltage output
- Digital Output Sensors – including use of integrated filtering, variable sampling frequencies, multiplexers, and factory-loaded calibration coefficients common to many of today’s sensors
- Design of various PC-based PCI, USB, and GPIB data acquisition systems using MATLAB, LabVIEW, and custom MS Visual Studio GUIs, typically used for development, environmental testing, or production
- Firmware
- Deep understanding of appropriate data type usage (e.g. int vs float vs double) and algorithm reduction techniques to maximize hardware resource availability (DSPs and hardware multipliers, as available) and minimize processor load
- Automated calculation of calibration coefficients in firmware
- Storage of calibration coefficients in nonvolatile memory, including memory integrity checking techniques
- Appropriate use of digital filters and weights to complement analog signal conditioning
- Use of sensor data in state machines in order to inform system actions in control loops or state machines
- Methods to condition sensor data for appropriate display to an end-user (development engineer, production engineer, or the general public)
- Calibration
- Experience with multiple calibration techniques, both performed both in device firmware real-time and externally using MATLAB GUIs and Microsoft Excel Visual Basic Macros
- Experience with multiple calibration fit types, including linear, polynomial, and piece-wise fit techniques
- Experience with use of unit-specific calibration coefficients provided by the manufacturer for some digital sensors
- Experience with generating calibration coefficients based upon datasheet histogram data provided by the manufacturer
Projects and Applications
Below is a list of completed projects of full system designs–that involved both software and hardware–using sensors and sensing systems.
- Tilt Sensor – tilt sensors that used a 3-axis accelerometer and a 3-axis gyroscope to provide a low latency solution of device tilt with respect to earth gravity.
- Compass – magnetic compass using 3-axis accelerometer, gyroscope, and magnetometer to provide heading solution with respect to magnetic north. Accelerometers and gyroscopes were used for quick-response outputs while the magnetometer provided a long-term correction (Kalman filter). Augmented compass design upgraded to include an integrated GPS module. With the use of present latitude and longitude and a magnetic declination look-up table, provided a heading solution with respect to true north.
- Acceleration Sensor – system using a 3-axis accelerometer to determine instantaneous acceleration vector, used to characterize launch and capture events.
- Rotation Sensor – system using a single-axis gyroscope to determine instantaneous rotational acceleration with respect to a fixed rotational axis.
- Shock Detector – single-axis accelerometer fixed to a pendulum used for electronics shock detection for an environmental test system.
- Vibration Sensor – system using a 3-axis accelerometer used to characterize mechanical vibration with intensity vs. frequency output. Used in a variety of applications including air frame resonant frequency characterization and an environmental test setup.
- Attitude-Heading Reference System (AHRS) – system using 3-axis accelerometer, 3-axis gyroscope, and 3-axis magnetometer (9 Degree-of-Freedom (9-DOF)) that provided magnetic heading and present air vehicle tilt in 3 dimensions (roll/pitch/yaw).
- Air Vehicle Control – system that used 3-axis accelerometers, gyroscopes, and magnetometers as inputs to a Kalman filter with multiple states, output with full authority over air vehicle flight surfaces.
- Full Authority Digital Engine Control (FADEC) – system that monitored rotational engine speed (using hall effect sensors) and engine temperature (using thermocouples) to commanded a throttle servo position in order to maintain a user-defined engine speed (in RPMs). System monitored cylinder head temperature (CHT) in order to provide an over-temperature safety shut-off. System purpose was to perform break-in and fuel map of a two-stroke carburetor engine. Fuel mapping data was used later in flight by software to provide an estimate of fuel remaining in tank.
- Fuel Injection System – system that accepted user throttle input to command solenoids controlling air/fuel mixture while monitoring engine temperature, air intake, and engine speed.
- Over Temperature Circuit Protection Circuits – system that used a simple IC temperature sensor and provide a thermal shutdown to avoid catastrophic failure of sensitive electronics. Included hysteresis of turn off and turn on functions. Used in miniature high-power radio designs to prevent damage.
- RPM Counters – system used multiple hall effect sensors in conjunction with magnets mounted on a rotating propeller shaft to determine present propeller RPM for display via GUI to the user.
- Electric Motor Position Sensor – system used a multiple hall effect sensors surrounding a rotating electric motor shaft with a magnet to determine present motor position used to command an H-bridge bi-directional electric motor control system to manipulate parafoil geometry for air vehicle control during flight.
- RF Power Meter – system which used a logarithmic amplifier (log detector) at the output of a superheterodyne RF receiver to display received in-band RF power (with units in dBm or W).
- Specific Fuel Consumption Calculating System – system that used a fuel flow meter and an RPM meter to characterize fuel consumption against RPM in an effort to maximize engine efficiency, with characterization data used in a fuel level estimating system.
- Machine Vision – use of optical camera and machine vision library to determine presence of air vehicle above the horizon (against a blue sky).
- Fuel Level Sensing – system that detected change in capacitance (based upon different relative dielectric of fuel and air) to determine fuel remaining in tank.
- Ambient Light Detection – system that used an optical light sensor to determine presence of bright light in order to switch display between day (display turned bright) and night (display turned dim) modes.
- Electrical Power Meter – system that measured current and voltage to determine electrical power (in W) consumed by load for display to user.
