Sensor & Measurement System Fundamentals

Posted on Apr 26, 2025 in Visual Arts and Dance

Classification of Measurement Errors & Analysis

Types of Errors

  • Systematic Errors: Predictable and consistent errors caused by factors such as calibration, environmental conditions, or instrument limitations.
    • Examples: Zero errors, scale errors, and environmental effects.
  • Random Errors: Unpredictable errors caused by unknown or uncontrollable factors.
    • Examples: Noise and fluctuations in the measurement process.
  • Gross Errors: Human mistakes during measurement or data recording.

Error Analysis

  • Absolute Error: The difference between the measured value and the true value. Absolute Error = |Measured Value – True Value|
  • Relative Error: Ratio of absolute error to the true value. Relative Error = Absolute Error / True Value
  • Percentage Error: Relative error expressed as a percentage.
  • Standard Deviation: A measure of the dispersion of a set of values.

Transducer & Sensor Characteristics

Static Characteristics

  • Accuracy: Closeness of the measured value to the true value.
  • Precision: Repeatability or consistency of measurements.
  • Resolution: The smallest change in input that can be detected.
  • Sensitivity: The ratio of output change to input change.
  • Linearity: Deviation of the output from a straight line over the input range.
  • Hysteresis: Difference in output when input is increasing versus decreasing.
  • Drift: Slow variation in the output over time without input change.

Dynamic Characteristics

  • Response Time: Time taken for the sensor to reach a stable output after input changes.
  • Bandwidth: The frequency range over which the sensor accurately responds.
  • Damping: The extent to which oscillations in the output are reduced.
  • Rise Time: Time required for the output to rise from 10% to 90% of the final value.

Sensor Classification Methods

Based on Measurement Principle

  • Resistive Sensors: e.g., strain gauges, potentiometers.
  • Capacitive Sensors: e.g., proximity sensors, level sensors.
  • Inductive Sensors: e.g., LVDTs, eddy current sensors.
  • Optical Sensors: e.g., photodiodes, fiber-optic sensors.
  • Thermal Sensors: e.g., thermocouples, RTDs.
  • Piezoelectric Sensors: e.g., vibration, pressure sensors.

Based on Output

  • Analog Sensors: Provide continuous output (e.g., thermistors).
  • Digital Sensors: Provide discrete output (e.g., proximity switches).

Based on Application

  • Temperature Sensors: e.g., thermistors, thermocouples.
  • Pressure Sensors: e.g., piezoelectric pressure sensors.
  • Position Sensors: e.g., potentiometers, encoders.

Sensor Calibration Techniques

  • Direct Calibration:
    • Comparing the sensor output with a standard reference under controlled conditions.
    • Example: Using a standard weight to calibrate a load cell.
  • Indirect Calibration:
    • Calibrating based on derived parameters rather than direct measurement.
  • Static Calibration:
    • Performed under steady-state conditions.
  • Dynamic Calibration:
    • Involves applying known dynamic inputs to measure the sensor’s response.
  • Multi-point Calibration:
    • Performing calibration at several points across the sensor’s range.
  • Zero and Span Adjustment:
    • Adjusting the baseline (zero) and range (span) of the sensor.

Choosing the Right Transducer

  • Nature of Measurement: Type of physical quantity (e.g., temperature, pressure, displacement).
  • Accuracy and Precision: Required accuracy and resolution for the application.
  • Environmental Conditions: Temperature, humidity, and corrosive environments.
  • Range of Measurement: Operating range of the transducer.
  • Sensitivity: Ability to detect small changes in input.
  • Response Time: Speed required for the application.
  • Cost and Availability: Budget constraints and ease of procurement.
  • Interference and Noise: Ability to withstand or filter out environmental noise.
  • Durability and Maintenance: Life span and ease of maintenance.

Amplification in Measurement Systems

Types of Amplifiers

  • Operational Amplifiers (Op-Amps):
    • High-gain, differential amplifiers.
    • Configurations: Inverting, non-inverting, differential, integrators, and differentiators.
  • Power Amplifiers: Used to drive high-power devices like speakers.
  • Instrumentation Amplifiers: High-precision amplifiers used for low-level signals.

Key Parameters

  • Gain: Ratio of output to input signal. Gain (A) = Vout / Vin
  • Bandwidth: Frequency range over which the amplifier operates effectively.
  • Slew Rate: Maximum rate of change of output voltage per unit time.

Data Acquisition Systems (DAQ)

Single-Channel DAQ

  • Acquires data from one sensor or signal source.
  • Simpler and lower cost.

Multi-Channel DAQ

  • Acquires data from multiple sensors or signal sources simultaneously or sequentially.
  • Types:
    • Simultaneous Sampling: Each channel has its own ADC.
    • Multiplexed Sampling: Uses a single ADC and a multiplexer to switch between channels.

Components of a DAQ System

  • Sensors: Convert physical phenomena to electrical signals.
  • Signal Conditioning: Amplification, filtering, etc.
  • ADC: Converts analog signals to digital data.
  • Data Processing: Performed by a microcontroller or computer.

Common Sensor Types & Principles

  • LVDT (Linear Variable Differential Transformer): Measures linear displacement by detecting changes in the output voltage of a transformer core. Known for high accuracy and wide measurement range.
  • RVDT (Rotary Variable Differential Transformer): Similar to LVDT but measures angular displacement.
  • Laser Range Sensor (LIDAR): Employs laser light to measure distance by measuring the time of flight of the laser pulse.
    • Applications: Self-driving cars, robotics, mapping, 3D scanning.
  • GPS (Global Positioning System): Utilizes a network of satellites to determine location (latitude, longitude, altitude). Widely used in navigation, mapping, and location-based services.
  • RF Beacons: Transmit and receive radio frequency signals to determine distance.
  • Reflective Beacons: Use infrared or visible light to measure distance by detecting the reflection from a target.
  • Load Cell:
    • Principle: Converts force into an electrical signal, typically using a strain gauge.
    • Types: Hydraulic, Pneumatic, Strain Gauge, Capacitive.
    • Advantages: Precise, reliable, and measures tension/compression forces.
    • Applications: Weighing scales, industrial machinery.
  • Magnetic Sensors:
    • Types: Magnetoresistive, Hall Effect, Current Sensors.
    • Principle: Detect changes in magnetic fields or induced currents.
    • Advantages: Non-contact sensing, durable, wide application range.
    • Applications: Speed sensing, current measurement.
  • Fiber Optic Sensors:
    • Principle: Detects changes in light properties traveling through optical fibers.
    • Applications: Pressure, temperature.
    • Advantages: Immune to electromagnetic interference.
  • Photo Sensors:
    • Principle: Changes electrical resistance when exposed to light.
    • Applications: Light meters, smoke detectors, and cameras.
  • Tactile Sensors:
    • Definition: Detects touch, force, or pressure through physical contact.
    • Applications: Robotics (grip force control), medical devices (prosthetics), touchscreens.
    • Advantages: High resolution and compact.
  • Radiation Sensors:
    • Principle: Detect radiation (e.g., ionizing, infrared, ultraviolet) using semiconductors or scintillators.
    • Applications: Medical imaging, environmental monitoring, nuclear plants.
    • Advantages: High sensitivity and reliable detection.
  • Smart Sensors:
    • Definition: Integrate sensing, processing, and communication capabilities.
    • Examples: Film sensors, Nano Sensors, Laser.
  • Photoresistive Cell (LDR): Changes electrical resistance when exposed to light.