Gas Sensors

Image Part Number Description / PDF Quantity Rfq
968-003

968-003

Spec Sensors

SENSOR HYD SULF ANALOG VLTG MOD

32

968-034

968-034

Spec Sensors

DGS-CO DIGITAL GAS SENSOR MODULE

62

110-901

110-901

Spec Sensors

SENS GAS AIR QUAL ANALG CUR MOD

141

110-202

110-202

Spec Sensors

SENSOR GAS ALCOHOL ANALG CUR MOD

101

110-407

110-407

Spec Sensors

SENSOR GAS O3 SMT

863

968-028

968-028

Spec Sensors

SENSOR CO ANALOG VOLTAGE MOD

0

110-402

110-402

Spec Sensors

SENSOR GAS OZONE ANALOG CUR MOD

0

968-036

968-036

Spec Sensors

DGS-H2S DIGITAL GAS SENSOR MODUL

46

110-601

110-601

Spec Sensors

SENS GAS SULF DIOX ANALG CUR MOD

124

110-406

110-406

Spec Sensors

SENSOR GAS O3 THRU HOLE

1160

968-038

968-038

Spec Sensors

DGS-SO2 DIGITAL GAS SENSOR MODUL

68

110-507

110-507

Spec Sensors

SENSOR GAS NO2 THRU HOLE

121

110-802

110-802

Spec Sensors

SENS GAS AIR QUAL ANALG CUR MOD

0

968-047

968-047

Spec Sensors

SENSOR NITR DIOX ANALOG VLTG MOD

46

968-043

968-043

Spec Sensors

DIGITAL GAS SENSOR NO2 MODULE

38

968-009

968-009

Spec Sensors

SENSOR AIR QUAL ANALOG VLTG MOD

10

968-006

968-006

Spec Sensors

SENSOR SULF DIOX ANALOG VLTG MOD

30

110-508

110-508

Spec Sensors

SENSOR GAS NO2 SMT

135

110-902

110-902

Spec Sensors

SENS GAS AIR QUAL ANALG CUR MOD

0

110-602

110-602

Spec Sensors

SENS GAS SULF DIOX ANALG CUR MOD

90

Gas Sensors

1. Overview

Gas sensors are detection devices that identify and measure gas concentrations in the environment. They convert chemical interactions with gas molecules into electrical signals for quantitative analysis. These sensors play a critical role in industrial safety, environmental monitoring, healthcare, and smart home systems by preventing gas leaks, ensuring air quality, and enabling process control.

2. Major Types and Functional Classification

TypeFunctional FeaturesApplication Examples
ElectrochemicalHigh accuracy, stable baseline, requires oxygenCO detectors, O2 monitors
SemiconductorLow cost, broad detection range, temperature-dependentIndoor air quality sensors
Catalytic CombustionExplosive gas detection, requires periodic calibrationIndustrial methane detectors
Infrared (IR)Non-contact measurement, high selectivityCO2 HVAC monitoring
Photoionization (PID)VOC detection at ppm levels, UV lamp requiredEnvironmental pollution monitoring

3. Structure and Components

A typical gas sensor consists of: - Sensing element (metal oxide/electrolyte membrane) - Signal conditioning circuit (amplifier, ADC) - Housing with gas inlet ports - Temperature/humidity compensation module - Communication interface (UART/I2C)

4. Key Technical Specifications

ParameterDescription
Detection RangeMeasurable gas concentration span (ppm to %LEL)
SensitivitySignal change per gas concentration unit (mV/ppm)
Response TimeT90 response speed (3-300 seconds)
AccuracyMeasurement error margin ( 2-10%)
Operating TemperatureFunctional range (-20 C to +50 C typical)
Long-term StabilityDrift specification (5-15% per year)

5. Application Fields

  • Industrial safety: Fixed gas detection systems
  • Environmental monitoring: Urban air quality stations
  • Healthcare: Medical breath analyzers
  • Smart homes: Combustible gas alarms
  • Automotive: Cabin air quality management

6. Leading Manufacturers and Products

ManufacturerProduct SeriesKey Features
HoneywellXNX Universal TransmitterDual-sensor redundancy
Figaro EngineeringTGS2600Low-power VOC detection
MembraporToxic Gas SensorsEletrochemical cells for Cl2
SenseairK-30 CO2 ModuleNDIR technology, 30ppm accuracy
AMS (Austria)ENS160 MOX SensorAI-based gas discrimination

7. Selection Guidelines

Key consideration factors:

  1. Target gas chemical properties
  2. Environmental conditions (temperature/humidity range)
  3. Required detection threshold and repeatability
  4. Power consumption budget
  5. Maintenance accessibility for calibration
  6. Cost vs. lifetime trade-offs

Industry Trends Analysis

Emerging development trends include: - Miniaturization through MEMS technology - Multi-gas detection using AI pattern recognition - Wireless self-powered IoT sensor nodes - Enhanced selectivity via nanomaterial coatings - Reduced cross-sensitivity through hybrid sensing methods

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