CENTRAL LEARNING OBJECTIVE
● The central learning objective is to understand the full range of signal processing techniques used to improve measurement quality in electrical and instrumentation systems.
MEASUREMENT SYSTEM OBJECTIVES
● A measurement system always aims to extract the maximum possible quality of information from a sensor.
● Filtering, shielding, compensation, correction, feedback, modulation, and correlation are the main strategies used.
● Each technique addresses specific limitations of accuracy, precision, or stability 📡.
ACCURACY, PRECISION, AND STABILITY
● Accuracy refers to the closeness of the measured value to the true value.
● Precision refers to the repeatability of measurements under unchanged conditions.
● Stability refers to the ability to maintain consistent performance over time 📊.
SIGNAL PROCESSING CATEGORIES
● Add-on techniques include pre-filtering, post-filtering, correlation, and correction.
● Built-in techniques include compensation, feedback, and modulation.
● Both categories contribute to reduced noise and improved measurement robustness ⚙️.
FILTERING TECHNIQUES
● Filtering reduces additive errors and thermal noise in a defined frequency band.
● Pre-filtering mitigates electrically induced signals via shielding, inductive interference via loop area reduction, and thermal effects via isolation.
● Mechanical shocks and unwanted optical inputs are reduced using dampers and optical filters 🛡️.
POST-FILTERING METHODS
● Post-filtering is applied in the electrical domain after signal transduction.
● Filter types include low-pass, high-pass, band-pass, and matched filtering.
● Digital and analog designs can be used, including Butterworth and Bessel characteristics 🎛️.
CORRECTION METHODS
● Correction can be model-based after calibration or via extra sensors for cross-sensitivity.
● Additive errors are corrected with auto-zeroing or correlated double sampling.
● Multiplicative errors are addressed with linearization or the three-signal method 🔧.
COMPENSATION METHODS
● Pre-compensation is integrated into system design, while post-compensation uses signal correction models.
● Balancing reduces common additive errors using elements such as dummy sensors or temperature sensors.
● Bridge compensation improves dynamic range and can use adjustable resistors ⚖️.
RATIOMETRIC MEASUREMENTS
● Ratiometric designs use the same reference voltage for both the ADC (analog-to-digital converter) and the measurement bridge.
● This approach eliminates reference voltage errors from the digital output.
● It is effective in maintaining consistent accuracy 🖥️.
DIFFERENTIAL MEASUREMENTS
● Differential systems use two sensors with opposite sensitivity to interference.
● A differential capacitive displacement sensor measures position changes with high immunity to noise.
● Interface circuits can include resistors to reduce drift while adding some noise ⚡.
FEEDBACK SYSTEMS
● Feedback reduces multiplicative errors and improves dynamic behavior.
● Effective feedback requires high forward-path gain and a stable feedback path.
● Applications include accelerometers with electrostatic actuators and thermal wind sensors 🌬️.
MODULATION TECHNIQUES
● Modulation shifts information to quieter frequency bands to reduce offset and low-frequency noise.
● Amplitude modulation includes chopping and synchronous detection.
● Pulse-width modulation and frequency modulation improve robustness to amplitude variations 📶.
THERMAL MANAGEMENT CHALLENGES
● Modern integrated systems contain multiple hot spots that require temperature monitoring.
● Thermal diffusivity sensing measures the delay in heat propagation between a heater and a temperature sensor.
● CMOS (complementary metal–oxide–semiconductor) technology allows precise on-chip spacing and accurate delay measurements 🌡️.
PHASE DIGITIZATION IN THERMAL SENSORS
● Phase digitizers measure small phase shifts in noisy thermal signals.
● Oversampling with sigma-delta modulation achieves high resolution at low bandwidth.
● Synchronous detection aligns reference phases for accurate measurement 📏.
PERFORMANCE OF THERMAL DIFFUSIVITY SENSORS
● High-precision CMOS layouts can achieve ±0.2 °C resolution without trimming.
● Untrimmed spread is mainly limited by lithographic accuracy.
● These sensors are scalable and robust 🔍.
REVIEW OF TECHNIQUES
● Measurement systems integrate pre-filtering, post-filtering, correction, compensation, feedback, and modulation.
● Each block targets specific sources of error.
● Combining these methods achieves high accuracy and stability 🛠️.
ASSIGNMENTS AND PROBLEMS
● Analytical problems include calculating bridge arm resistance in ratiometric systems.
● Determining ADC resolution requirements ensures that thermal noise dominates over quantization error.
● Thermal diffusivity problems involve phase shift calculations across extreme temperature ranges 📐.
My Diary - Leonardo Cardillo 