Static Characteristics of Measuring Instruments
📌 Static characteristics apply to instruments measuring quantities that are constant or vary very slowly over time, not changing with respect to time.
⚙️ Key static characteristics discussed include range (span), sensitivity, linearity, hysteresis, accuracy, precision, reproducibility, and drift.

Defining Static Characteristics
📏 Range or Span is the maximum and minimum values of the quantity the instrument is designed to measure (e.g., $100^{\circ}\text{C}$ to $500^{\circ}\text{C}$ for a thermometer).
👂 Sensitivity is defined as the change in instrument output resulting from a change in input, often expressed as a ratio (e.g., $25 \text{ mm per kilogram}$ for a spring balance).
🌡️ Sensitivity Drift occurs when sensitivity changes with factors like temperature (e.g., $25 \text{ mm/kg}$ at $20^{\circ}\text{C}$ vs. $27 \text{ mm/kg}$ at $30^{\circ}\text{C}$).

Instrument Behavior & Error Analysis
〰️ Linearity measures the instrument's ability to produce a linear output, defined by the maximum deviation of calibration points from the ideal straight line, expressed as a percentage of the full-scale output.
🔁 Hysteresis is the phenomenon showing different output effects during loading (increasing input) versus unloading (decreasing input) due to internal friction or damping.
🎯 Accuracy describes how closely an instrument reading approaches the true value of the quantity being measured.
🔬 Precision indicates the repeatability or reproducibility of an instrument's readings.

Accuracy vs. Precision Example
⚙️ If several manufactured components have diameters close to each other (e.g., $25.5 \text{ mm}$) but far from the target true value ($25 \text{ mm}$), they are precise but not accurate.
📉 If readings are scattered but centered closer to the true value, the instrument is more accurate but less precise.

Reproducibility and Drift
🕰️ Reproducibility is the degree of closeness a given value can be repeatedly measured over a period of time, signifying no variation with time.
➡️ Drift is the gradual shift in indication over time when the input variable remains unchanged, often caused by environmental factors like thermal or electrical influences.
📉 Drift is further classified into zero drift, span drift (sensitivity drift), and zonal drift.

Analog vs. Digital Quantities
➡️ Analog quantities have continuous values (e.g., time, temperature showing a smooth curve).
🔢 Digital quantities have a discrete set of values (e.g., sampling temperature hourly converts the continuous analog quantity into discrete points that can be digitized, like $20^{\circ}\text{C} \rightarrow 10100_2$).
👍 Digital advantages include more effective/reliable processing and transmission, more compact storage, greater accuracy in reproduction, and less susceptibility to noise (unwanted voltage fluctuations).

Key Points & Insights
➡️ Static characteristics are measured when the input signal is constant or changing very slowly.
➡️ Sensitivity drift can be mitigated by using instruments in controlled temperature environments or applying input temperature compensation schemes.
➡️ To quantify linearity, measure the maximum deviation from the ideal straight line as a percentage of the full-scale output.
➡️ Understand that precision relates to repeatability over a short time (repeatability) or long time (reproducibility), while accuracy relates to closeness to the true value.

📸 Video summarized with SummaryTube.com on Oct 05, 2025, 05:01 UTC