Ultrasonic vs. IR- Optimizing Industrial Sensor Selection

This article will focus on the following three key aspects:

• Physical Mechanisms and Operating Principles: Detailing the fundamental differences between ultrasonic and infrared sensing technologies in terms of signal sources, detection logic, propagation media, and response characteristics.
• Environmental Adaptability and Robustness: Deeply exploring the stability performance and compensation strategies of both sensing solutions in complex industrial environments, with particular emphasis on the significant advantages of ultrasonic technology in challenging media.
• Typical Application Scenarios and System Design Essentials: Analyzing critical design considerations, precise calibration strategies, and multi-sensor fusion practices in specific industrial applications.

• Basic Principle: Ultrasonic sensors utilize the piezoelectric effect to convert electrical energy into high-frequency sound waves, which are then emitted towards a target. By receiving the reflected echoes and precisely measuring the round-trip time, the distance to the target is determined. The speed of sound is significantly affected by the physical properties of the medium (especially temperature), requiring compensation.
• Distance Formula: Distance d = (v · t) / 2, where v is the speed of sound, approximately 343 m/s in air at 20°C,, and can be approximated by v ≈ 331.4 + 0.6 · T (where T is in Celsius).
• Beam Characteristics and Coupling: Ultrasonic sensors emit sound waves with specific beam angles and directivity. Effective acoustic coupling to the medium is crucial. Echo quality is influenced by the target material’s acoustic impedance, surface roughness, and environmental scatterers.
• Performance and Limitations:
  • Advantages: Ultrasonic sensors are insensitive to optical interference and can effectively penetrate environments containing particles such as steam, fog, and dust, ensuring stable operation in harsh conditions. Their dependence on target color, transparency, or material is low, making them particularly suitable for medium to long-range distance measurement, liquid/material level monitoring, and general obstacle avoidance, demonstrating exceptional robustness.
  • Limitations: Resolution is typically lower than IR sensors, and response time is relatively slower. The speed of sound is affected by medium temperature, humidity, and density, requiring calibration. They have a “dead zone” or “near-field effect,” and echoes may attenuate significantly or suffer from multipath interference with soft, sound-absorbing materials or complex surface structures.

• Basic Principle: IR sensors emit specific wavelengths of near-infrared light beams and analyze the reflected light signal from the target surface to determine the target’s presence, distance, or surface characteristics.
• Distance Measurement Modes:
  • Triangulation: Precisely measures the angular relationship between the emitter, receiver, and reflected light to calculate target distance, suitable for close-range, high-precision detection.
  • Time-of-Flight (TOF): Measures the time taken for IR light to travel to the target and back to the receiver. Distance d ≈ c * t / 2, requiring high-precision timing and ambient light suppression.
• Performance and Limitations:
  • Advantages: IR sensors generally offer high spatial resolution, fast response times, compact structures, and relatively low costs. They excel in close-range object detection, edge recognition, and specific color/texture identification.
  • Limitations: Performance is susceptible to ambient light intensity, target surface reflectivity (e.g., specular reflections, highly absorbent, or highly transparent materials), and medium transparency (e.g., steam, dust, fog), leading to reduced measurement stability and reliability.

For industrial applications, the following comparative dimensions help engineers quickly assess suitability:

• Distance and Resolution:
  • Ultrasonic: Suitable for medium to long-range measurements. Resolution is limited by frequency and design, but it’s highly immune to ambient light interference, with signal-to-noise ratio being critical.
  • IR: Offers high resolution and fast response at close range but is susceptible to optical conditions.
• Environmental Robustness:
  • Ultrasonic: Insensitive to optical interference (e.g., strong light, smoke, dust). It exhibits excellent stability in extreme temperatures, humidity fluctuations, medium changes, and when obstacles are present in the sound path.
  • IR: Highly sensitive to light intensity, color, and surface. Reliability decreases significantly in environments with steam, dust, or transparent materials.
• Medium and Surface Dependence:
  • Ultrasonic: Depends on the target material’s acoustic reflection and coupling characteristics. It is insensitive to target color and optical transparency.
  • IR: Highly dependent on the target surface’s optical reflection characteristics.
• Cost, Size, and Integration Complexity:
  • Ultrasonic: Manageable size and cost, but requires attention to acoustic coupling, transducer packaging, and temperature compensation. Integration can be slightly more complex, but its reliability in harsh environments often yields higher overall benefits.
  • IR: Generally lower cost, compact, easy to integrate, suitable for large-scale, low-cost deployment.

Ensuring reliable sensor operation in complex industrial environments requires critical system-level design considerations:

• Temperature and Environmental Compensation:
  • Ultrasonic: Real-time temperature sensing and compensation algorithms are essential to correct for temperature’s effect on sound speed. In liquid/gas media, sound speed correction based on density and composition changes is also necessary.
  • IR: Requires considering light source stability, ambient light suppression strategies, and dynamic threshold adjustment for varying surface reflectivity.
• Signal Processing and Calibration:
  • Ultrasonic: Requires advanced filtering techniques (e.g., Kalman filter), precise echo peak detection algorithms, time-gating to differentiate valid echoes, and suppression of multipath interference. Signal fusion in multi-probe arrays can also be implemented.
  • IR: Involves optimizing brightness thresholds, effective noise suppression, continuous adaptive calibration of surface reflection models, and improving robustness in complex conditions through multi-point or multi-angle measurements.
• Multi-Sensor Fusion: In extremely complex industrial scenarios, a single sensing technology often cannot meet all requirements. Intelligently fusing outputs from ultrasonic and IR sensors can build more robust, redundant, and comprehensive sensing systems, particularly leveraging ultrasonic’s strong environmental adaptability.
• Safety and Reliability: Long-term stability, ease of maintenance, and convenient on-site calibration should be core considerations from the design outset.

Engineers often fall into the following pitfalls during sensor selection and application:

• Pitfall 1: Focusing solely on a single technical specification (e.g., maximum range or highest resolution) while neglecting the complexity of the actual operating environment, long-term maintenance costs, and overall system stability.
  • Strategy: Adopt a holistic evaluation approach, considering environmental adaptability, MTBF (Mean Time Between Failures), calibration cycles, and maintenance complexity.
• Pitfall 2: Underestimating the impact of environmental factors like temperature, humidity, and medium composition on actual sensor performance, leading to significant deviations from calibrated values.
  • Strategy: Conduct a comprehensive environmental condition assessment during the design phase and ensure the selected sensor has appropriate compensation mechanisms or use industrial-grade products capable of extreme conditions. For ultrasonic sensors, temperature compensation is indispensable. On-site small-scale testing is advisable to verify performance.
• Pitfall 3: Treating optical or acoustic sensor physical parameters in isolation, failing to recognize the synergistic effect of system components like drive circuits, signal processing units, mechanical packaging, and mounting methods on final performance.
  • Strategy: From a systems engineering perspective, view the sensor as one link in the entire sensing chain. Optimization should cover the complete path from signal acquisition to data output, ensuring high coordination and matching among components.

• Environment and Medium Conditions:
  • When ambient light is complex, targets are highly reflective, transparent materials are present, or steam, fog, and dust cause optical interference, ultrasonic technology is a more reliable choice due to its superior acoustic principles.
• Distance and Resolution Requirements:
  • For medium to long-range measurements, low dependence on optical properties, stable distance estimation, or the ability to penetrate interfering environments, ultrasonic solutions offer stronger performance.
  • For close-range, high-resolution detail detection with very fast update rates, IR sensors generally offer advantages in resolution and response speed.
• Target Surface and Medium Dependence:
  • If the acoustic properties of the target medium have little impact on measurements, or if optical conditions in the operating environment cannot be effectively controlled, then acoustic/ultrasonic solutions generally exhibit higher robustness as they do not rely on visual features of the target.
  • If target surface color, texture, gloss, or coating significantly affects optical signal reflection and absorption, special attention must be paid to the sensor’s dependence on superficial characteristics.
• System Integration and Maintenance Costs:
  • Ultrasonic solutions excel in environmental robustness. While they may require more system-level integration (e.g., acoustic coupling optimization, temperature/medium compensation algorithms), their long-term stability in harsh environments often results in higher total lifecycle benefits.
  • IR sensors are typically compact, lower cost, and easier to deploy, making them suitable for large-scale, low-maintenance applications.

• Scenario A: Liquid/Material Level Measurement, Boundary Detection, or operation in environments with high steam, fog, or dust.
  • Selection Tendency: Ultrasonic preferred. Insensitive to optical interference, capable of penetrating or effectively bypassing particulates and moisture, offering significantly stronger robustness.
• Scenario B: Distance measurement requiring penetration or ignoring surface color/texture, with a relatively long target distance.
  • Selection Tendency: Ultrasonic more suitable. Provides stable distance estimation unaffected by the target surface’s optical properties.
• Scenario C: Close-range, high-resolution edge detection with good lighting conditions and minimal environmental interference.
  • Selection Tendency: IR more advantageous. Offers high resolution, fast response, and is cost- and size-friendly.
• Scenario D: Strong visual contrast, clean surfaces, and very high demand for rapid situational awareness.
  • Selection Tendency: IR can be used for rapid detection and high-resolution positioning. However, potential impacts of optical interference and surface condition changes on measurement stability must be considered.
• Scenario E: Complex conditions requiring multi-sensor fusion (e.g., navigation + boundary identification + environmental monitoring).
  • Selection Tendency: Combined strategy preferred. Prioritize assessing efficient signal processing and fusion schemes, then determine the proportion and combination of individual sensing technologies based on specific needs.

• Temperature and Medium Compensation:
  • Ultrasonic: Real-time monitoring and compensation for the significant effects of temperature, humidity, and medium density on sound speed are mandatory.
  • IR: Dynamic adjustment of light intensity, surface reflection thresholds.
• Signal Processing and Calibration:
  • Ultrasonic: Utilizes advanced filtering, precise echo peak detection, and time-gating to suppress multipath interference.
  • IR: Optimizes brightness thresholds, noise suppression, and dynamic adaptive calibration.
• Maintenance and Reliability:
  • Ultrasonic: Long-term stability of the acoustic coupling interface, durability of encapsulation in different media, and simplification of field calibration are crucial.
  • IR: Cleanliness of optical components and potential changes in target surface reflectivity are key maintenance points.
• Cost and Deployment Speed:
  • Ultrasonic: While initial design and integration costs may be slightly higher, its total lifecycle cost-effectiveness is often superior in industrial applications requiring high robustness and strong environmental tolerance.
  • IR: Lower initial cost and faster deployment.

• Prioritize Ultrasonic when:
  • The working environment has optical interference like steam, fog, dust, or smoke.
  • Measurement needs to penetrate opaque media, or is insensitive to target color/transparency.
  • Measurement distance is long, requiring stable and reliable distance information.
  • Medium characteristics (e.g., temperature, humidity) can be effectively compensated, or the sensor itself has strong environmental adaptability.
• Prioritize IR when:
  • Ambient light conditions are good or controllable, and target surface reflectivity is stable.
  • Close-range, high-precision, and high-response speed are required.
  • Highly cost-sensitive, seeking fast and simple deployment.
  • The primary task is to identify color, texture, patterns, or tiny objects.
• Prioritize Multi-Sensor Fusion when:
  • Application demands involve multiple complex tasks like navigation, boundary identification, and environmental monitoring.
  • A single sensor cannot meet all performance or robustness requirements.
  • Seeking extremely high system reliability and fault tolerance.
• Core Principle: For distance measurement independent of material/medium characteristics, or when operating in complex, harsh media, ultrasonic offers unparalleled advantages. For high-resolution, close-range positioning with controlled surface conditions, IR is often preferred.

• Ultrasonic is suitable for: Environments with significant optical interference (e.g., steam, fog, dust), requiring penetration of opaque media, long measurement distances, or strong robustness against changes in medium characteristics.
• IR is suitable for: Close-range, high-resolution applications with stable optical conditions, cost-sensitive, and focused on optical feature recognition.

• Scenario: Tank and silo level monitoring often faces challenges like steam, foam, oil stains, corrosive media, and temperature fluctuations.
• Comparison: Ultrasonic technology does not rely on optical transmission and can effectively penetrate steam, foam, and turbid media, providing stable and reliable distance information. Optical/IR sensors show significantly reduced stability under such conditions.
• Conclusion: Sensori a ultrasuoni are the preferred choice for liquid/material level monitoring due to their excellent environmental robustness and medium penetration capabilities.

• Scenario: AGVs perform obstacle avoidance and navigation in open warehouses, production lines, etc., susceptible to dust, ground reflections, damp conditions, and changing ambient light.
• Comparison: Ultrasonic sensors are more robust against ground reflections, environmental dust, and damp conditions, providing more stable distance judgments, and are especially good at detecting black or transparent obstacles. IR sensors are prone to false readings or failures in unstable lighting or with transparent objects.
• Conclusion: Sensori a ultrasuoni are dominant in this scenario; their reliability in complex and dynamic AGV operating environments is superior to purely optical solutions.

• Scenario: In industrial production lines, such as film, paper, and textile processing, high-precision edge recognition is required. Transparent or patterned materials significantly increase the difficulty of optical detection.
• Comparison: Ultrasonic sensors, being unaffected by optical properties, demonstrate higher robustness in detecting the edges of transparent films, patterned, or contaminated materials, providing more consistent distance information. IR sensors offer high resolution when surfaces are clean and optical conditions are stable.
• Conclusion: In conditions of surface contamination, light fluctuations, or when handling transparent/patterned materials, ultrasuoni sensors are more robust. IR sensors have advantages when surfaces are clean and optical conditions are controllable.

• Scenario: In printing, packaging, and metal processing, accurately distinguishing single from double sheets is crucial. Transparent materials, varying thicknesses, and surface characteristics affect signal attenuation.
• Comparison: Ultrasonic sensors are insensitive to medium differences (single vs. double sheet) and optical interference. They can stably distinguish different material thicknesses, unaffected by color, transparency, or print patterns. IR sensors are prone to fluctuations with optical interference.
• Conclusion: Sensori a ultrasuoni are the leading technology in this scenario due to their excellent robustness in handling diverse materials and complex optical environments.

• Scenario: Continuous measurement of roll diameters (e.g., paper, film, cables) is critical for stable production and precise tension control. Changes in roll material color, gloss, or surface coating significantly affect optical measurements.
• Comparison: Ultrasonic sensors are insensitive to the target’s appearance (color, gloss, coating) and provide stable and reliable distance measurements for precise roll diameter calculation. IR sensors struggle to maintain measurement stability when facing significant changes in roll surface color or gloss.
• Conclusion: Sensori a ultrasuoni demonstrate higher robustness in roll diameter and distance detection, especially in strong light or complex-appearance roll scenarios, where their performance is significantly superior to IR sensors.

• Scenario: By emitting sound waves and analyzing the reflected waves from the object under test, calculating the energy absorbed and attenuated within the material allows for accurate inference of its composition, density, porosity, or internal structure. This is crucial for material identification, quality control, or performance evaluation.
• Comparison: Ultrasonic sensors effectively differentiate various materials and quantify their internal properties (e.g., identifying types of plastics, detecting resin content in composites, or assessing concrete density) by analyzing sound wave propagation speed, attenuation rates, and energy absorption patterns within different materials. They also exhibit strong immunity to material surface optical conditions. Optical signals (IR) are primarily used for surface feature detection and have limited capability in acquiring internal absorption and attenuation information.
• Conclusion: Sensori a ultrasuoni are the dominant technology for material characterization and identification due to their excellent penetration capability and sensitivity to internal acoustic absorption and attenuation characteristics, ensuring more reliable and in-depth non-destructive analysis.

• Scenario: Industrial environments often present severe conditions such as dust, smoke, humidity, strong light, and extreme temperatures, making optical sensors (including IR) difficult to operate stably.
• Comparison: Sound waves have strong penetration capabilities, allowing ultrasonic sensors to perform well in harsh environments filled with particulates or strong light, without being directly interfered with by the medium. Optical solutions like IR are highly susceptible to these environmental factors, leading to performance degradation or failure.
• Conclusion: In harsh industrial environments, ultrasonic sensing systems are prioritized to maintain high robustness, reliability, and continuous operational capability.

• Scenario: Detecting extremely small, fast-moving objects, such as fine wires, needles, or micro-electronic components, is often required in industries like electronic assembly and medical packaging.
• Comparison: IR photoelectric sensors achieve micron-level object detection accuracy and extremely fast response times over short distances due to their very narrow light beam and high switching frequency. The wavelength and minimum dead zone of ultrasonic sound waves limit their ability to detect extremely small targets.
• Conclusion: This scenario is better suited for IR sensing technology for high-precision small object detection.

• Scenario: Rapid detection of objects or people over a large area at automated equipment, robot workstations, or entrances/exits is necessary to ensure operator safety.
• Comparison: IR safety light curtains or photoelectric switches form a protective zone using multiple IR light beams, providing fast and reliable obstacle detection. They are cost-effective and relatively simple to install. Implementing large-area coverage with ultrasonic sensors increases cost and wiring complexity.
• Conclusion: This scenario is better suited for IR safety light curtains as the primary solution.

Q1: What are key considerations when using ultrasonic sensors for liquid measurement?

A1: Key considerations include:

1. Temperature Compensation: Liquid sound speed changes significantly with temperature; real-time compensation is essential.
2. Liquid Surface Condition: Foam or ripples affect echoes; use high-frequency, narrow-beam sensors, signal processing, or stilling tubes.
3. Liquid Properties: High viscosity or suspended solids can increase sound attenuation.
4. Corrosion Resistance: Sensor materials must withstand liquid corrosion for longevity.
5. Mounting Position: Avoid dead zones and ensure clear sound paths.

Q2: What is the fundamental difference in how dust and fog affect ultrasonic versus IR sensors?

A2: The impact differs fundamentally:

• Ultrasonic Sensors: Sound waves, with longer wavelengths, penetrate or bypass particles more effectively, so they are less affected. The main challenge is temperature’s effect on sound speed, not the particles themselves.
• IR Sensors: Light is scattered, absorbed, and refracted, causing significant signal energy attenuation, often leading to failure or errors.

Conclusion: Ultrasonic sensors are generally more robust than IR sensors in dusty or foggy environments.

Q3: How should the appropriate sensor beam angle or detection area be selected?

A3:

• Ultrasonic (Beam Angle): Narrow beams (e.g., <5°) offer strong directivity for high-precision focusing; wide beams (e.g., >10°) provide broad coverage for general obstacle avoidance.
• IR (Detection Area): Focused/narrow spot is for high-precision detection of small objects; wide detection area/diffuse reflection is for general obstacle detection.

Selection Strategy: Based on target characteristics, environment, mounting precision, and interference rejection needs.

Q4: Can IR sensors detect transparent objects?

A4: IR sensors face challenges with transparent objects as most IR light passes through, yielding weak reflections. Performance depends on material, thickness, and angle. Solutions include angled mounting, background suppression, or retro-reflective plates. For high reliability or complex environments, ultrasonic sensors are often preferred.

Q5: What specific material and protection class requirements apply to ultrasonic and IR sensors in the food and pharmaceutical industries?

A5: Strict hygiene and safety standards demand:

1. Materials: All contact parts must be food/medical-grade (e.g., 304L/316L stainless steel, PTFE), with mirror-polished surfaces and no harmful substance leaching.
2. Protection Class: At least IP67 or IP68, to withstand frequent high-pressure washing and sterilization.
3. Ultrasonic Specifics: Transducer front-end encapsulation material must be food-grade.
4. IR Specifics: Optical window materials must be easy to clean, corrosion-resistant, and maintain optical transparency.

Summary: Beyond function, material hygiene compliance, corrosion resistance, and highest protection class are paramount. Products with relevant certifications (e.g., EHEDG) are recommended.