11-06-2014, 03:04 PM
3D MACHINE VISION SYSTEMS SEMINAR REPORT
3D MACHINE VISION SYSTEMS SEMINAR REPORT.doc (Size: 83.5 KB / Downloads: 16)
ABSTRACT
Machine vision refers to applications in which the PC automatically makes a decision based on visual input from a camera. Machine vision is a term typically used in industrial manufacturing, where applications range from culling blemished oranges from a conveyor belt to saving lives by inspecting to ensure that the correct drug capsule has been placed in the package before the product is shipped to the pharmacy. Three dimensional vision based measurement systems have made their presence into production metrology applications, notably in the electronics field. However, in the more traditional fields of durable goods now dominated by hard gauges and CMMs, 3D optical systems has been hindered by perceptions and real limitations. This paper will review where 3D vision is today, and what advances have been made to enable more quantitative, shop floor metrology applications. The field of 3D machine vision is a less established field, but one that is actively growing today. Three dimensional vision based measurements have come a long way in the past few years, moving from purely visualization tools that generate attractive color pictures, to serious measurement tools. These 3D systems include laser scanning, structured light, stereo viewing, and laser radar just to name a few
INTRODUCTION
Modern day durable goods manufacturing have begun to embrace the concepts of digitization as a means to improve productivity and quality. Moving away from expensive hard gages made for specific parts; manufacturers are seeking the means to measure parts in a flexible manner, and capture the resulting measurements by digital means. For higher volume parts, such as from forging or fast machining operations, speed of gauging is still an issue.
This is the area where machine vision based tools start to excel. Machine vision in general has been used for everything from guiding the insertion of electronic chips on circuit boards to inspecting bottles at several per second in bottling lines. A natural extension of machine vision inspection is to provide programmable measurements for machined parts. In many applications, these measurements can be made in two dimensions for which there is an established based of machine vision tools working in the sub-thousandth of an inch range at multiple measurements per second. Each of these methods has their strong points and weak points for a given application.
The key performance parameters needed for durable good manufacturing include:
• Resolution in the mil, and sub-mil range
• Speeds sufficient to complete all measurements in a few seconds
• Ability to look at a wide range of surface types and finishes
This last point, the ability to look at a wide range of surface finishes has perhaps been the biggest limitation of 3D machine vision technology. In many cases, the surface needs to be diffuse to permit reflected light to be easily seen to achieve a good signal to noise ratio.
Three dimensional optical sensors can perhaps be broken into a few basic types:-
Point scanning sensors measure only the specific points of interest, typically in a serial fashion,
Line sensors provide a single line of points in the form of a cross section of the contour of interest,
DISCUSSION OF TECHNOLOGIES
There are currently three basic approaches to three-dimensional machine vision:
• range finding including structured lighting
• stereo or binocular vision,
• gray scale or range finding methods.
TRIANGULATION
The most popular commercial versions of range finding use the triangulation method where a beam of light is projected onto the object's surface at some angle and the image of this spot or line of light is viewed at some other angle (see Figure 1). As the object distance changes a spot of light on the surface will move along the surface by
opaque, rough surface, the micro-structure of the surface can act as though it is made of a range of small mirrors, pointing in numerous directions. These micro-mirrors may reflect the light off in a particular direction, as generally machine marks do, or may direct the light along the surface of the part. Depending on how random or directional the pointing of these micro-mirrors may be, the apparent spot seen on the surface will not be a direct representation of the light beam as incident on the part surface. The effects that may be seen from a laser beam reflecting off a rough surface include:
• directional reflection due to surface ridges
• skewing of the apparent light distribution due to highlights
• expansion of the incident laser spot due to micro surface piping
The result of this type of laser reflection or "speckle" is a noisy signal from some surfaces. In like manner, there can be a problem with translucent surfaces, as the laser light will scatter through the medium and produce a false return signal. For a laser based sensor, a smooth, non-mirror like, opaque surface produces the best results. An active variation of restricting the view uses synchronized scanning. In the synchronized scanning approach (see figure 2), both the laser beam and viewing point is scanned across the field. In this manner, the detector only looks at where the laser is going.
The detector now has the advantage that it can resolve the distribution of light seen along that particular angle, and potentially decide on which signals are the correct ones. Reflections that do not go along the view axis are not seen at all. The limitations of this approach can be more time consumed in seeking each point, and low light collection to maintain high angle separate. If as opposed to a single spot of light, a line is projected onto the surface by imaging or by scanning a beam, as shown in Figure 1, the line will deform as it moves across a contoured surface as each point of the line move as described above. The effect is to provide an image of a single profile of the part (see figure 4). In applications requiring only a profile measurement, these techniques offer good speed of measurement
APPLICATION TESTING
As has already been stated, the key operational parameters needed for production machine vision include speed, resolution, and robustness especially to changing part surface conditions. Many systems that provide the best resolution are not the fastest, so a tradeoff must be made. Just as with touch probes, there are certain types of features or surfaces that optical 3D methods can be expected to work good on, and others where there may be problems. If has been pointed out that shiny, but not specular surfaces have offered one of the biggest challenges. In like manner, when a surface changes from a shiny area to a dull, many sensors may generate a bias error. In the simple case of triangulation, the measurement is based upon finding the centroid of a light spot of some finite size. If half that spot is on an area that reflects back to the sensor well, and the other half is not, the center of brightness of the spot will not be the geometric center, but rather weighted toward the brighter region. Testing the sensor on edge and surface transition features is a valuable first test to consider (such as in Figure 6)
CONCLUSION
As with any technology of this nature, the performance changes with the component technology. The primary advance that has made machine vision systems feasible for shop floor gauging applications has been the speed up in computing power. This has brought the processing times from 15 or 20 minutes on an expensive workstation to seconds on a standard PC. The other technologies that are influencing performance today include lower cost, digital cameras than provide better light range and pixel resolution with lower noise, and better light sources such as higher power laser diodes well as higher brightness and resolution LCD projectors. The consumer market largely influences all of these technologies, which is currently a much bigger driver than any manufacturing support system. However, as system prices decrease and performance improves, there is a wide range of new markets these systems will likely address ranging from dentistry to home 3D pictures.