Precision Analog & Signal Conditioning

Precision Analog & Signal Conditioning: Noise in Analog Circuits, Distortion, Linearity & Dynamic Range, Signal Conditioning & Sensor Excitation, Temperature Measurement: RTD, Thermocouple, Thermistor & IR, Instrumentation Amplifiers, Error Budgets & Calibration.

• Noise in Analog Circuits — The fundamental limit on small signals. Learn noise as a random signal (RMS, spectral density, bandwidth, peak-to-peak ≈ 6.6 × RMS), thermal (Johnson) noise, shot noise, flicker (1/f) noise and popcorn noise, kT/C noise in sampled circuits, op-amp e_n and i_n models, adding uncorrelated sources in RSS, input-referred noise, noise bandwidth of filters, noise figure and SNR, choosing low-noise parts for a given source impedance, and reduction by filtering, averaging and chopping — with Python building a full noise budget for an op-amp stage and integrating 1/f noise.
• Distortion, Linearity & Dynamic Range — How nonlinearity corrupts signals. Learn linear vs nonlinear transfer functions, harmonic distortion (HD2, HD3, THD, THD+N), intermodulation distortion (IMD, IP3), sources of distortion (exponential V_BE, square-law MOSFETs, clipping, slew limiting, crossover, capacitor voltage coefficient, thermal), even vs odd harmonics and differential cancellation, dynamic range, SINAD, SFDR and ENOB, and techniques to improve linearity (degeneration, feedback, differential circuits, predistortion, better components) — with Python computing harmonics of a BJT stage and a differential pair by DFT.
• Signal Conditioning & Sensor Excitation — Getting sensor signals into an ADC accurately. Learn the signal chain (excitation, protection, amplification, filtering, level shifting, ADC driving), sensor types and their electrical outputs, Wheatstone bridges (quarter, half, full) and their nonlinearity, voltage and current excitation, ratiometric measurement, RTDs (2/3/4-wire) and self-heating, thermocouples and cold-junction compensation, thermistors and linearisation, 4–20 mA current loops, gain and offset scaling to the ADC range, isolation, and input protection — with Python computing bridge outputs, RTD values and lead errors, 4–20 mA scaling and gain/offset mapping.
• Temperature Measurement: RTD, Thermocouple, Thermistor & IR — Temperature is the most measured variable in industry. Learn RTDs (Pt100, Callendar–Van Dusen, 2/3/4-wire), thermocouples (Seebeck effect, types, cold-junction compensation, extension wires), thermistors, semiconductor sensors, infrared pyrometers and emissivity, thermowells and response time — with Python for Pt100 conversion, lead-wire error and CJC.
• Instrumentation Amplifiers, Error Budgets & Calibration — Proving a measurement system meets its accuracy specification. Learn instrumentation-amplifier error sources (gain error and drift, offset and drift, CMRR, nonlinearity, bias current, noise, input range), accuracy vs precision vs resolution, systematic vs random errors, building an error budget in ppm of full scale, worst-case vs RSS summation, what calibration can and cannot remove, one-point, two-point and multi-point calibration, temperature compensation, traceability and recalibration intervals — with Python summing a pressure-chain budget and deriving two-point calibration coefficients.