The industry is using machine vision for replacing manual examination, assessment, and human decision-making. For this, they are using video hardware supplemented with software systems. The technology is highly effective for inspection, quality control, wire bonding, robotics, and down-the-hole applications. Machine vision systems obtain their information by analyzing the images of specific processes or activities.
Apart from inspection systems, the industry also uses machine vision for the sophisticated detection of objects and for recognizing them. Machine vision is irreplaceable in collision avoidance systems that the next generation of autonomous vehicles, robotics, and drones are using. Recently, scientists are using machine vision in many machine learning and artificial intelligence systems, such as facial recognition.
However, for all the above to be successful, the first requirement is the machine vision must be capable of capturing images of high quality. For this, machine vision systems employ image sensors and cameras that are temperature sensitive. They require active cooling for delivering optimal image resolutions that are independent of the operating environment.
Typically, machine vision applications make use of two types of sensors—CCD or charge-coupled devices, and CMOS or complementary metal-oxide semiconductor sensors. For both, the basic functionality is to convert photons to electrons that are necessary for digital processing. Both types of sensors are sensitive to temperature, as thermal noise affects their image resolution, and thermal noise increases with the rising temperature of the sensor assembly. This depends on environmental conditions or the heat generated by the surrounding electronics, which can raise the temperature of the sensor beyond its maximum operating specification.
By rough estimation, the dark current of a sensor doubles for every 6 °C rise in temperature. By dropping the temperature by 20 °C, it is possible to reduce the noise floor by 10 dB, effectively improving the dynamic range by the same figure. When operating outdoors, the effect is more pronounced, as the temperature can easily exceed 40 °C. Solid-state Peltier coolers can prevent image quality deterioration, by reducing and maintaining the temperature of the sensor to below its maximum operating temperature, thereby helping to obtain high image resolution.
However, it is a challenge to spot cool CCD and CMOS sensors in machine vision system applications. Adding a Peltier cooling device increases the size, cost, and weight. It also adds to the complexity of the imaging system. Cooling of imaging sensors can lead to condensation on surfaces exposed to temperatures below the dew point. That is why vision systems are mainly contained within a vacuum environment that has insulated surfaces on the exterior. This prevents the build-up of condensation over time.
The temperature in the 50-60 °C range primarily affects the image quality of CCD and CMOS sensors. However, this depends on the quality of the sensor as well. For sensors in indoor applications just above ambient, a free convection heat sink with good airflow may be adequate to cool a CMOS sensor. However, this passive thermal solution may not suffice for outdoor applications. Active cooling with a Peltier cooling solution is the only option here.
