Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Mechanical measurement system
Reexamination Certificate
2001-07-05
2003-07-15
Assouad, Patrick (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Mechanical measurement system
C700S167000, C700S171000, C700S110000, C702S084000
Reexamination Certificate
active
06594590
ABSTRACT:
FIELD OF THE INVENTION
This invention relates to a method and apparatus for improved inspection and classification of attributes of a workpiece, and in particular to automated high speed defect assembly and generation of a workpiece model for lumber grading.
BACKGROUND OF THE INVENTION
It has become a serious consideration in the lumber industry to improve grading of lumber and therefore improve secondary breakdown decisions. By optimizing the recovery of “good wood” against a slate of desired products, the value of the lumber may be increased. “Good wood” refers to wood which meets a prescribed criteria. For different uses, what is considered “good wood” may vary. For example, for fine furniture, it may not be acceptable to have any knots in the wood. However, for furniture intended to have a more rustic appearance, a certain number of knots may in fact be desirable. In general though it is desirable to identify certain “defects” in the lumber, and to locate them with respect to a spatial reference system. One method of doing this is to have a human visually inspect each piece of lumber prior to it being cut into secondary boards. This is slow and prone to error. Further, even if the defect is identified, the information must still somehow be communicated to a saw operator in a meaningful manner to allow the defect to be isolated, yet allow wood recovery to be optimized against a desired product slate.
There have been some improvements in the area of grading lumber, for example Lumber Optimizer (U.S. Pat. No. 4,879,753 to Aune et al), Method of Estimating the Strength of Wood (U.S. Pat. No. 4,941,357 to Schajer), Dielectric Sensor Apparatus (U.S. Pat. No. 5,654,643 to Bechtel et al), Detector for Heterogeneous Materials (U.S. Pat. No. 5,585,732 to Steele et al), and Flaw Detection System Using Microwaves (U.S. Pat. No. 4,514,680 to Heikkilä et al) which uses microwaves to measure lumber flaws.
Defects comprise such features as knots, rot, splits, sap, skips, holes, cracks, wane, stain and the like. Defects may be further subclassified, for example a knot may be a sound knot or an unsound knot. Most defects have some attribute which allows them to be detected by automated scanning. For example, reflective inspection (laser or gray-scale video) can detect stain and sap in wood. Transmissive inspection techniques (such as x-ray) can detect density variations, and thus knots and rot and the like. As indicated, a variety of automatic inspection techniques exist for determining the presence of such defects. Most of these methods give only an indication of the probability of a defect, and do not guarantee that the object identified by the inspection technique is actually a defect. However, by combining the different results of automatic inspection into a single model, defects can be verified and the probability that an identified object is in fact a defect are increased. Further, combining inspection results allows further characterization of a defect. For example, a dark area identified by a visual scan can either indicate rot, stain, or a knot. However, verification of the visual scan with an x-ray scan can reveal the object to be rot if the x-ray scan indicates it is an area of low density, or a knot if the x-ray scan indicates it is an area of high density.
It is desirable if all of the results of inspection can be combined to produce a board model, which in the digital realm might be more appropriately termed a “virtual board.” The board model can then be analyzed for optimum yield against a product slate. Further, automated handling machines such as conveyors, and automated process machines such as saws, can control the handling and processing of the physical board on which the board model is based.
It is further desirable to have a system which is flexible and can easily accommodate the addition or subtraction of additional components, such as additional inspection subsystems, user interfaces, computer controlled machines (saws, etc.), and additional technology as it becomes available.
For any such system to be effective, it is desirable that the system be able to determine the precise location of the board at various points throughout the system. Various prior art tracking systems such encoder wheels can become inaccurate due to slippage, and can cause undesirable marking of the product in the event of a failure. It is therefore desirable to provide a tracking system which is accurate and reliable.
SUMMARY OF THE INVENTION
An apparatus for detecting the probable existence, location, and type of defects in a workpiece is disclosed. The apparatus has a signal processor having a computer readable memory, a control subsystem, and a sensor subsystem. The sensor subsystem is configured to sense a first section of the workpiece and produce signals corresponding to at least one physical characteristic of the section of the workpiece and store the signals in the computer readable memory. The processor is configured to read the signals from the computer readable memory, to verify the signals, to generate defect types by comparing the signals to a rule set, and to generate a data model of the workpiece section. The control system is configured to generate a workpiece section identifier to specifically identify a workpiece section being sensed and provide the workpiece section identifier to the processor. The processor is further configured to receive the signals for the first workpiece section to a first workpiece processing thread after receiving the associated workpiece section identifier, and to generate a second workpiece processing thread for receiving signals from a second workpiece section. The signals in the first workpiece processing thread are processed to generate the data model of the first workpiece section prior to processing of the signals in the second workpiece processing thread.
The invention further includes an apparatus for detecting the probable existence, location, and type of defects in a workpiece wherein the apparatus includes a sensor subsystem as described above, a defect assembler, an optimizer, and a computer system. The defect assembler is configured to generate defect assembler data, subscription requests, to receive the signals produced by the sensor subsystem, and to generate a workpiece data model based on the signals. The optimizer is configured to generate workpiece segmentation recommendations based on the workpiece data model, and generate optimizer data subscription requests. The computer system further includes a processor and a computer readable memory. The computer system is configured to receive signals form the sensor subsystem and store them in the computer readable memory. The processor is configured with a first producer thread program which, in response to the receipt of a first set of signals by the computer system, receives one of the data subscription requests and transmits the first set of signals from the computer readable memory to the generator of the data subscription request. The processor is further configured to generate a second producer thread in response to a storage of a second set of signals in the computer readable memory, the second producer thread being configured to receive one of the data subscription requests and selectively send the second set of signals to the generator of the data subscription request.
The invention further includes an apparatus for characterizing a workpiece, the apparatus including an interface controller, a plurality of producer units, and a plurality of consumer units. The producer units are configured to produce data relevant to characterization of the workpiece. The producer units are selected from the group consisting of sensor subsystems, a defect assembler, an optimizer, and a data controller. The sensor subsystems are configured to sense features of the workpiece and generate signals in response thereto. The defect assembler is configured to generate a workpiece data model. The optimizer is configured to produce a refined workpiece data model and generate workpiece segmentation recommen
Johnson Emeric
McGuire Michael
Ogloff Harry
Skocic Zvonimr
Woods Steve C.
Assouad Patrick
Coe Newnes McGehee ULC
Reid John S.
Reidlaw, L.L.C.
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