Electronics Guide

Accuracy and Precision

Accuracy describes how close a measurement result is to the true value of the quantity being measured. Precision describes the repeatability of measurements, or how close repeated measurements are to each other. A measurement system can be precise without being accurate (consistently wrong), or accurate on average while imprecise (scattered around the true value). Ideal measurements are both accurate and precise.

Sources of measurement error include systematic errors that consistently bias results in one direction and random errors that cause scatter around the mean. Systematic errors can often be corrected through calibration, while random errors are managed through statistical techniques including averaging multiple measurements. Understanding error sources helps engineers design measurement procedures that minimize uncertainty.

Resolution and Sensitivity

Resolution refers to the smallest change in a quantity that a measurement system can detect. For digital instruments, resolution is often determined by the number of bits in the analog-to-digital converter. Sensitivity describes the ratio of the change in output to the change in input, indicating how responsive the measurement system is to changes in the measured quantity.

High resolution does not guarantee high accuracy; a system can resolve very small changes while still having significant offset or gain errors. Similarly, high sensitivity must be accompanied by low noise to be useful, as high sensitivity to the signal of interest often implies high sensitivity to noise as well.

Loading Effects

Every measurement disturbs the quantity being measured to some degree. Voltage measurements draw current from the circuit, potentially changing the voltage. Current measurements insert resistance into the circuit, affecting current flow. Understanding loading effects helps engineers select instruments and measurement points that minimize measurement disturbance.

Input impedance specifications indicate how much a measurement instrument will load the circuit being measured. High input impedance for voltage measurements and low input impedance for current measurements minimize loading effects. For accurate measurements, the instrument's input impedance should be appropriate for the source impedance of the circuit being measured.

Bandwidth and Rise Time

Measurement system bandwidth limits the frequencies that can be accurately measured. Signals beyond the bandwidth are attenuated and phase-shifted, producing erroneous results. Rise time, related to bandwidth by the approximation rise_time x bandwidth approximately equals 0.35, limits how fast transients can be accurately captured.

Measuring fast signals requires instruments with bandwidth significantly exceeding the highest frequency component of the signal. A common guideline suggests five times the fundamental frequency for accurate measurement of repetitive waveforms, or rise time at least five times faster than the signal rise time for transients.

SI Units and Fundamental Standards

The International System of Units (SI) defines the fundamental units used in measurement. Recent revisions to the SI have redefined base units in terms of fundamental physical constants, improving long-term stability and reproducibility. For electrical measurements, the ampere is now defined in terms of the elementary charge, while the volt and ohm derive from the Josephson effect and quantum Hall effect respectively.

National metrology institutes maintain primary standards that realize the SI definitions with the highest possible accuracy. These institutions provide calibration services and reference materials that form the top of the traceability chain for measurements throughout their respective countries.

Calibration and Traceability

Calibration establishes the relationship between an instrument's reading and the true value of the quantity being measured. Regular calibration compensates for drift and aging, maintaining measurement accuracy over time. Calibration should be performed at intervals appropriate for the instrument type and usage conditions.

Traceability provides an unbroken chain of comparisons linking a measurement result to national or international standards. Each step in the chain adds uncertainty, so the measurement uncertainty of the calibration standard must be significantly smaller than the required measurement uncertainty. Documentation of the traceability chain supports quality systems and regulatory compliance.

Sources of Uncertainty

Measurement uncertainty arises from numerous sources including instrument accuracy, calibration uncertainty, environmental effects, loading effects, and operator technique. Type A uncertainties are evaluated statistically from repeated measurements, while Type B uncertainties are estimated from other information such as instrument specifications and calibration certificates.

Combining uncertainties requires understanding how errors propagate through measurement calculations. For independent error sources, uncertainties typically combine as root-sum-of-squares. Correlated errors may add directly or partially cancel depending on the correlation coefficient.

Expressing Uncertainty

Standard uncertainty expresses measurement uncertainty as an equivalent standard deviation, providing approximately 68% confidence that the true value lies within the stated range. Expanded uncertainty, typically with coverage factor k=2, provides approximately 95% confidence. Measurement results should include both the measured value and its associated uncertainty.

The Guide to the Expression of Uncertainty in Measurement (GUM) provides internationally accepted methods for evaluating and expressing measurement uncertainty. Following GUM methodology ensures consistent uncertainty estimates that can be meaningfully compared across laboratories and applications.

Research and Development

Research applications often require pushing measurement capabilities to their limits, characterizing new phenomena or verifying subtle theoretical predictions. Flexibility and detailed understanding of measurement principles often matter more than ease of use. Custom measurement setups may be required for unique measurement challenges.

Design Verification

Product development requires measurements to verify that designs meet specifications and perform as intended. Prototype testing identifies design issues before production commitment. Margin testing verifies that designs work across the full range of specified conditions with adequate safety margin.

Production Testing

Manufacturing requires fast, reliable measurements to verify product quality while maintaining production throughput. Automated test equipment performs programmed test sequences, comparing results against pass/fail limits. Statistical process control uses measurement data to monitor production processes and detect trends before they cause quality problems.

Field Service and Diagnostics

Field service requires portable, rugged instruments that can diagnose problems in operational equipment. Measurement techniques must work in less-than-ideal conditions while providing sufficient accuracy for troubleshooting. Safety considerations are paramount when measuring equipment in the field.