Visual inspectionThe system uses machines to replace human eyes in performing measurements and making judgments. Specifically, machine vision products—image acquisition devices, which come in two types: CMOS and CCD—convert the captured target into an image signal, which is then transmitted to a dedicated image-processing system. Based on information such as pixel distribution, brightness, and color, the system transforms these signals into digital data. The image-processing system then performs various computations on these digital signals to extract the target’s key features, and subsequently controls the actions of on-site equipment according to the results of its analysis. This technology represents a valuable mechanism for production, assembly, or packaging processes. It holds immeasurable value in detecting defects and preventing defective products from being delivered to consumers. However, visual inspection machines are susceptible to instability due to factors such as cameras, lenses, and lighting conditions. Thus, ensuring maximum machine stability has become a major concern for many companies.

Instability factors

Industrial camera

The selection of industrial cameras primarily considers theirSensor type, resolution, and frame rate, where the sensors are dividedCCDWithCMOSThere are two types: CMOS image sensors have high integration, with components and circuits located very close to each other, resulting in significant interference and high imaging noise. In contrast, CCD sensor cameras boast higher sensitivity, lower noise, and faster response speeds compared to CMOS cameras. In terms of stability, CCD cameras also exhibit stronger resistance to shock and vibration. Generally speaking, CCD sensor cameras outperform CMOS cameras in both imaging quality and stability.

Industrial lens

Another important factor affecting camera image quality is the camera lens. In addition to selecting appropriate basic parameters such as focal length, aperture, and other specifications based on actual working conditions, an important factor influencing the accuracy of network detection is:The geometric distortion error in the image cannot be eliminated.Only embedding is possible. Many industrial cameras employ various methods to compensate for the distortion caused by wide-angle lenses.However, in the high-precision inspection industry, geometric shapes can affect detection accuracy.

Light source

The light source enhances image features and defects while reducing the influence of interference and background images, thereby quickly affecting the quality of the input data. Since there are no readily available lighting devices, the design of the light source represents a key challenge in machine vision technology. In most cases, it is not only necessary to select the appropriate type of light source for each specific application but also to configure the light source according to the actual natural environment. It has been observed that the estimated light-source illumination methods often fall short of achieving optimal practical performance. The stability of the light source varies depending on its type.Common invisible light sources include LED lights, LED light sources, solar lamps, and sodium lamps.The biggest drawback of invisible light is that the light energy emitted by solar lamps and similar devices cannot be continuously and stably output. Within 100 hours, the light energy decreases by about 15%. As the duration of use increases, the output of light energy continues to decline. Therefore, differences in the selection of light sources also contribute to the instability of visual inspection equipment.

Software detection

Testing software stability is a critical factor that affects the results of machine vision inspections. Ultimately, the vision system uses software running on a computer to perform a series of image-processing operations—such as image filtering, edge detection, and edge extraction—using targeted algorithms. Different image-processing and analysis techniques, as well as various inspection methods and computational formulas, can all introduce different types of errors.The quality of the algorithm determines the accuracy of the measurement.

External environment

Environmental factors affecting the visual system include:Ambient temperature, illuminance, power supply voltage, dust, humidity, and electromagnetic interference, among others.A favorable operating environment is essential for the proper functioning of a vision system. External illumination can affect the illuminance on the object being inspected, increasing noise in the image data output. Variations in power supply voltage can also cause instability in the light source, leading to time-varying noise. Temperature fluctuations can similarly impact camera performance; cameras are typically marked with a specified operating temperature range when they leave the factory. Electromagnetic interference is an unavoidable disturbance in industrial inspection environments, and it particularly affects sensitive electronic circuits such as camera circuitry and data signal transmission circuits.

Solution

Industrial camera

If the enterprise has no special requirements,CCD sensor cameras are the primary choice for ensuring image quality and stability.Among these factors, the camera’s resolution and frame rate are primarily selected based on detection accuracy and detection speed. The appropriate resolution is determined by calculating the field of view of the detected object relative to the distance between the camera and the object being measured. Meanwhile, the camera’s frame rate is chosen considering both the motion speed of the object being measured and the required detection accuracy.

Industrial lens

You need to select the corresponding lens resolution based on the camera's maximum resolution. Select...Greater than the camera's maximum resolutionAny camera will do; however, you’ll also need to calculate the lens’s focal length based on the working distance and field of view, and select an appropriate depth of field according to changes in the distance between the object being measured and the camera. In high-precision measurements, in addition to correctly selecting the above parameters, you can opt for a telecentric lens, which exhibits significantly lower geometric distortion compared to conventional lenses. Not only does a telecentric lens have reduced geometric distortion, but it also minimizes errors caused by variations in the object’s distance from the camera.

Light source

Unless otherwise specified, visible light sources should be given priority.LED light sourceIn terms of light source uniformity— a factor that decisively affects the quality of captured images—LED light sources significantly outperform other light sources such as halogen lamps and fluorescent lamps. Moreover, LED lights offer advantages including low power consumption, long service life, and zero environmental pollution. To minimize the impact of external light on the stability of the visual system, one can also shield external light sources by adding a light-shielding enclosure.

Algorithm

The raw images acquired by the hardware ultimately need to go through algorithms such as image filtering and edge detection before they can complete the detection function and produce detection results. Among these, image filtering can suppress noise present in the acquired images, reduce issues caused by unstable light sources and grayscale values, and improve the signal-to-noise ratio. Essentially, image filtering uses algorithms to ensure that the minimum variance among pixels on the image is minimized. For high-precision measurement systems, coarse boundary pixel-level accuracy often fails to meet the requirements. Subpixel-edge localization technology, which combines subdivision algorithms with fitting methods at the pixel level, can achieve subpixel-level edge positioning accuracy down to 0.1 or even 0.01 pixels, thereby guaranteeing the system's overall detection accuracy.

External environment

Minimize interference from the external environment and strictly adhere to the machine vision inspection equipment’s usage guidelines. For example, cameras are typically marked at the factory with a specified operating temperature range; factories should ensure that machines operate within these normal temperature limits. Use qualified vision products—such products undergo rigorous anti-interference testing before leaving the factory, significantly reducing the impact of external electromagnetic interference on the hardware circuitry. In general, the design of a machine vision system requires consideration of multiple factors. In addition to selecting equipment based on standard specifications tailored to specific requirements, it is also necessary to take into account factors such as the stability of the light source, camera distortion errors, and the relative motion between the object being inspected and the camera—all of which can introduce stability disturbances and measurement errors into the inspection system. Only by comprehensively considering these factors and optimizing the vision system design can we establish a stable and compliant machine vision inspection system.