Claims:We Claim:
1. A machine for the detection of abnormalities in wood-based products(100), having: a table assembly having an inlet(I), a conveyor belt(B), a main controller board(MCB) of python raspberry pi operating system(MC) connected with micro-controllers(IC1, IC2, IC3, IC4, IC5), at least one ECHO sensor(E) connected to each said micro-controller(IC1, IC2, IC3, IC4), a motor driver(D) and a motor(M) connected to said micro-controller(IC5), part sensors(PS1, PS2, PS3, PS4) connected to said micro-controller(IC5), a Human-Machine Interface(HMI) connected to said micro-controller(MC), an output control board(OCB), switched mode power supply(SMPS1, SMPS2, SMPS3) connected to 220 volt AC supply,
wherein on receiving signals from sensor(PS1) connected to IC5, said main controller board (MCB) sends a signal to said motor(M) to start said conveyor belt(B), moving along with it said wood-based product fed to it through said inlet(I);
wherein on receiving signals from sensor(PS2) connected to IC5, said main controller board(MCB) sends a signal to said micro-controllers(IC1, IC2, IC3, IC4) to initiate scanning of said wood-based product by said ECHO sensors(E1, E2, E3, E4, E5, E6, E7, E8, E9, E10, E11, E12, E13, E14, E15, E16, E17, E18, E19, E20) and on receiving signals from sensor(PS3) connected to IC5, said main controller board(MCB) sends a signal to said micro-controllers(IC1, IC2, IC3, IC4) to stops the scanning of said wood-based product;
wherein data so collected by said ECHO sensors are processed by said main controller board(MCB), characterized in that, said main controller board(OCB) segregates said input wood-based product into three categories based on any abnormalities found;
wherein data so processed are sent to said output controller board(OCB) and displayed with visual and audio components,
wherein on receiving signals from sensor(PS4) connected to IC5, said main controller board(MCB) sends a signal to said motor(M) to stop said conveyor belt(B).
2. The machine for the detection of abnormalities in wood-based products (100) as claimed in claim 1, wherein ATMEGA 328P is used as the micro-controller for IC1 or IC2 or IC3 or IC4 or IC5 or any combination of these.
3. The machine for the detection of abnormalities in wood-based products(100) as claimed in claim 1, wherein ECHO sensor(E) connected to IC1 may vary anywhere between one to five.
4. The machine for the detection of abnormalities in wood-based products(100) as claimed in claim 1, wherein ECHO sensor(E) connected to IC2 may vary anywhere between one to five.
5. The machine for the detection of abnormalities in wood-based products(100) as claimed in claim 1, wherein ECHO sensor(E) connected to IC3 may vary anywhere between one to five.
6. The machine for the detection of abnormalities in wood-based products(100) as claimed in claim 1, wherein ECHO sensor(E) connected to IC4 may vary anywhere between one to five.
7. The machine for the detection of abnormalities in wood-based products(100) as claimed in claim 1, wherein python based raspberry pi is used as the operating system for Micro-controller(MC).
8. The machine for the detection of abnormalities in wood-based products(100) as claimed in claim 1, wherein ATTINY 8 is used as the controller for output controller board(OCB).

, Description:FIELD OF THE INVENTION
The present invention relates to a device particularly designed to detect abnormalities in wood-based products. More specifically, the present invention relates to the machine for detecting abnormalities such as core gap and steam pockets in processed wood products such as plywood.
BACKGROUND OF THE INVENTION
Performance, quality, and durability are important factors in determining the life of any wood-based product. Most of the wood-based products are dependent on the quality of wood, such as lumber core, composite core, etc., but there are several other factors that are equally important and may not be traced back to the quality of the original wood, such as the moisture content, the alignment of cores, etc. Some of the regularly encountered problems with wood-based products are “steam pockets” and “core gap.” Steam pockets are the development of bubbles by virtue of the creation of water vapor when the heat treatment is given to a wood-based product. It generally happens when either the core moisture is high, or the moisture content of the adhesive/glue affixed to the wood-based product is beyond a specific range. Steam pockets of bigger sizes are visible through naked eyes (traceable), but small pockets are absolutely untraceable. Another such problem is “core gaps.” A wood-based product such as plywood is manufactured by assembling the cores along and across the grains. Due to an error, a gap may be spared along with the assembly. If plywood is cut open, the gaps are specifically visible. But the detection of a core gap by cutting open the wood-based product is labor-intensive, time-consuming as well as loss-making (is not possible with every ply as it is not only time consuming but also affects the delivery). Moreover, detection of steam pockets of minimal sizes is not possible without the intervention of external help such as a machine.
An object of the present invention is to provide the machine for the detection of abnormalities in wood-based products.
Another object of the present invention is to provide the machine for the detection of “steam pockets” in wood-based products, and thereby detection of pockets of moisture content beyond a certain specified range, which is deemed harmful for wood-based products.
Yet another object of the present invention is to provide the machine for the detection of “core gaps” in wood-based products and thereby detect any misalignment with the assembling of core and grains in such products.
Still another object of the present invention is to provide the machine capable of automating the detection of abnormalities in wood-based products, with minimal intervention from operators/humans, and thereby reducing the chances of human error to the minimal.
Another object of the present invention is to provide the machine capable of segregating wood-based products based on any abnormality found in them and notifying the operator with visual as well as audio signs.
SUMMARY OF THE INVENTION
As illustrated in Figure 2, a detailed component level view of the machine for the detection of abnormalities in wood-based products (100), in accordance with the present invention, is disclosed. The machine includes a table assembly having an inlet(I), a guide(G), a guide bearing(BG), a set of rollers(R), a conveyor belt(B), a leg support(LS), ECHO(E1, E2, E3, E4, E5, E6, E7, E8, E9, E10, E11, E12, E13, E14, E15, E16, E17, E18, E19, E20) sensors attached to the micro-controllers(IC1, IC2, IC3, IC4), a main controller board(MCB) attached to the machine(100), a motor driver(D) and a motor(M) attached to the main controller board(MCB), micro-controllers(MC) attached to the main controller board(MCB), photo-electric sensors(PS1, PS2, PS3, PS4) attached to the micro-controller(IC5), an output controller board(OCB) attached to the main controller board(MCB) and a Human-Machine Interface(HMI) connected to the main controller board(MCB). In one embodiment of the present invention, multiple numbers of rollers(R) are used and can range anywhere between one to seven such rollers(R). A switched-mode power supply(SMPS) is used to provide power to the different components of the machine(100). The main controller board(MCB) is connected to SMPS1, which in turn is directly connected to 220v AC supply. The motor driver(D) is connected to SMPS2, which in turn is directly connected to 220v AC supply. The output controller board(OCB) is connected to SMPS3, which in turn is directly connected to 220v AC supply.
The present invention makes use of a python-based raspberry pi controller board(MC). The main controller board(MCB) includes at least five micro-controllers(IC1, IC2, IC3, IC4 & IC5). At least one micro-controller (IC5) is connected to a motor driver(D), which in turn is connected to a DC motor(M). The main function of the motor driver(D) is to control the speed of the motor(M) in terms of Pulse with Modulation(PWM) signal. This signal is generated by the python-based raspberry pi microcontroller(MC). The main function of this DC motor(M) is to give motion to the rollers(R) on the machine(100) so that the conveyor belt(B) can move. At least four of such micro-controllers(IC1, IC2, IC3 & IC4) are connected to ECHO sensors(E1, E2, E3, E4, E5, E6, E7, E8, E9, E10, E11, E12, E13, E14, E15, E16, E17, E18, E19, E20) which perform the basic operations on the wood-based product to detect any abnormality in it. The sensor(PS1) connected to IC5 detects the input wood-based product available to be fed to the machine through the inlet(I) space and sends a signal to the main controller board(MCB). The main controller board(MCB) in turn sends a signal (START CONV.) to the motor(M) to start the conveyor belt(B). As a result of this, the conveyor belt(B) starts and feeds the wood-based product to the machine(100). As the wood-based product reaches the contact point of the sensor(PS2) connected to IC5, the sensor sends a signal to the main controller board(MCB). The main controller board(MCB) in turn sends a signal (START SCANNING) to the ECHO sensors via micro-controllers(IC1, IC2, IC3, IC4) to start the scanning of the wood-based product. As a result of this, the ECHO sensors start scanning the wood-based product to detect abnormalities. The ECHO sensors used here are ultrasonic ECHO sensors, the main function of which is to check the wood-based products for any abnormality in terms of the presence or absence of electrical signals. At least one such ECHO sensor is to be used with the machine(100). The present invention has been worked with several such sensors and can vary in number anywhere in between one to twenty. In the meantime, the wood-based product continues to move further on the conveyor belt(B). As the wood-based product reaches the contact point of the sensor(PS3) attached to IC5, the sensor sends a signal to the main controller board(MCB). The main controller board(MCB) in turn sends a signal(STOP SCANNING) to the ECHO sensors via micro-controllers(IC1, IC2, IC3, IC4) to stop the scanning of the wood-based product. In the meantime, the wood-based product continues to move further on the conveyor belt(B). As the wood-based product reaches the contact point of sensor(PS4) connected to IC5, the sensor sends a signal to the main controller board(MCB). The main controller board(MCB) in turn sends a signal(STOP CONV.) to the motor(M) to stop the conveyor belt(B). As a result of this, the conveyor belt(B) stops completely. In another variation of the present invention, ATMEGA 328P microcontrollers are used as IC1, IC2, IC3, IC4 & IC5.
From the point in time when the ECHO sensors start to the point in time when the ECHO sensors stop, the ECHO sensors send the data so received, i.e., electrical signals to the main controller board(MCB). The main controller board(MCB) processes the data so received based on pre-defined processes and technical standards and would segregate the wood-based product based on any abnormalities found, and then would send results to the output controller board(OCB). The output controller board(OCB) uses an ATTINY 8 micro-controller and connects and receives signals from the python-based raspberry pi microcontroller(MC). The output controller board(OCB), displays the result with a visual and an audio component. The combination of such visual and audio components that can be displayed are: in the case of detection of steam pockets, “a red light” as the visual output and “Steam Pocket” as the audio output ; in the case of detection of core gap, “a yellow light” as the visual output and “Core Gap” as the audio output and in the case of detection of no abnormalities, “a green light” as the visual output and “Good product” as the audio output.
At least one ECHO sensor is to be attached to each micro-controller i.e. IC1, IC2, IC3 & IC4. The present invention has been worked with several different combinations of number of sensors attached to each such micro-controller, and can vary from a minimum of one to five such sensors attached to each of micro-controller. The number of sensors can vary on each such micro-controller irrespective of the number of sensors attached on the other micro-controller.
BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 illustrates an isometric view of a machine for the detection of abnormalities in wood based products (100) in accordance with the present invention.
Figure 2 illustrates a detailed component level view of a machine for the detection of abnormalities in wood based products (100) in accordance with the present invention having a main controller board(MCB) connected with micro-controllers(IC1, IC2, IC3, IC4, IC5), ECHO sensors connected to micro-controllers(IC1, IC2, IC3, IC4), a motor driver(D) and a motor(M) connected to micro-controller(IC5), part sensors(PS1, PS2, PS3, PS4) connected to micro-controller(IC5), a Human-Machine Interface(HMI), an output control board(OCB), switched mode power supply(SMPS1, SMPS2, SMPS3) connected to 220 volt AC supply.
DETAILED DESCRIPTION OF THE DRAWINGS
The invention will now be described with reference to the accompanying drawings which do not limit the scope and ambit of the invention. The description provided is purely by way of example and illustration.
Figure 1 illustrates an isometric view of a machine for the detection of abnormalities in wood based products (100) in accordance with the present invention. The machine includes a table assembly having an inlet(I), a guide(G), a guide bearing(BG), a set of rollers(R), a conveyor belt(B), a leg support(LS) to support the Legs(L), ECHO sensor holder(SH) attached to the machine(100), a main controller board(MCB) attached to the machine(100). The wood-based product is entered through the inlet(I), with the help of rollers(R) on a conveyor belt(B).
Figure 2 illustrates a detailed component level view of a machine for the detection of abnormalities in wood based products (100) in accordance with the present invention having a main controller board(MCB) connected with micro-controllers(IC1, IC2, IC3, IC4, IC5), ECHO sensors connected to micro-controllers(IC1, IC2, IC3, IC4), a motor driver(D) and a motor(M) connected to micro-controller(IC5), part sensors(PS1, PS2, PS3, PS4) connected to micro-controller(IC5), a Human-Machine Interface(HMI), an output control board(OCB), switched mode power supply(SMPS1, SMPS2, SMPS3) connected to 220 volt AC supply. The machine includes a table assembly having an inlet(I), a guide(G), a guide bearing(BG), a set of rollers(R), a conveyor belt(B), a leg support(LS) to support the Legs(L), ECHO sensor holder(SH) attached to the machine(100), a main controller board(MCB) attached to the machine(100). In one embodiment of the present invention, multiple number of rollers(R) are used, and can range anywhere between one to seven such rollers(R). Switched mode power supply(SMPS) is used to provide power to the different components of the machine. The main controller board(MCB) is connected to SMPS1, which in turn is directly connected to 220v AC supply. The motor driver(D) is connected to SMPS2, which in turn is directly connected to 220v AC supply. The output controller board(OCB) is connected to SMPS3, which in turn is directly connected to 220v AC supply.
The present invention makes use of a python based raspberry pi controller board(MC). The main controller board(MCB) includes at least five micro-controllers(IC1, IC2, IC3, IC4 & IC5). At least one of micro-controller (IC5) is connected to a motor driver(D) which in turn is connected to a DC motor(M). The main function of the motor driver(D) is to control the speed to the motor(M) in terms of Pulse with Modulation(PWM) signal. This signal is generated by the python based raspberry pi micro-controller(MC). The main function of this DC motor(M) is to give motion to the rollers(R) on the machine(100) so that the conveyor belt(B) can move. At least four of such micro-controllers(IC1, IC2, IC3 & IC4) are connected to ECHO sensors(E1, E2, E3, E4, E5, E6, E7, E8, E9, E10, E11, E12, E13, E14, E15, E16, E17, E18, E19, E20) which perform the basic operations on the wood-based product to detect any abnormality in it. The sensor(PS1) connected to IC5, detects the input wood-based product available to be fed to the machine through the inlet(I) space, and sends a signal to the main controller board(MCB). The main controller board(MCB) in turn sends a signal (START CONV.) to the motor(M) to start the conveyor belt(B). As a result of this, the conveyor belt(B) starts and feeds the wood-based product to the machine(100). As the wood-based product reaches the contact point of sensor(PS2) connected to IC5, the sensor sends a signal to the main controller board(MCB). The main controller board(MCB) in turn sends a signal (START SCANNING) to the ECHO sensors via micro-controllers(IC1, IC2, IC3, IC4) to start the scanning of the wood-based product. As a result of this, the ECHO sensors starts scanning the wood-based product to detect abnormalities. The ECHO sensors used here are ultrasonic ECHO sensors, the main function of which is to check the wood-based products for any abnormality in terms of presence or absence of electrical signals. At least one such ECHO sensor is to be used with the machine(100). The present invention has been worked with several number of such sensors, and can vary in number anywhere in between one to twenty. In the meantime, the wood-based product continues to move further on the conveyor belt(B). As the wood-based product reaches the contact point of sensor(PS3) attached to IC5, the sensor sends a signal to the main controller board(MCB). The main controller board(MCB) in turn sends a signal(STOP SCANNING) to the ECHO sensors via micro-controllers(IC1, IC2, IC3, IC4) to stop the scanning of the wood-based product. In the meantime, the wood-based product continues to move further on the conveyor belt(B). As the wood-based product reaches the contact point of sensor(PS4) connected to IC5, the sensor sends a signal to the main controller board(MCB). The main controller board(MCB) in turn sends a signal(STOP CONV.) to the motor(M) to stop the conveyor belt(B). As a result of this, the conveyor belt(B) stops completely. In another variation of the present invention ATMEGA 328P microcontrollers are used as IC1, IC2, IC3, IC4 & IC5.
From the point in time when the ECHO sensors starts to the point in time when the ECHO sensors stop, the ECHO sensors sends the data so received i.e. electrical signals to the main controller board(MCB). The main controller board(MCB) processes the data so received based on pre-defined processes and technical standards, and would segregate the wood based product based on any abnormalities found and then would send results to the output controller board(OCB). The output controller board(OCB) uses an ATTINY 8 micro-controller and connects and receives signals from the python based raspberry pi micro-controller(MC). The output controller board(OCB), displays the result with a visual and an audio component. The combination of such visual and audio components that can be displayed are: in the case of detection of steam pockets, “a red light” as the visual output and “Steam Pocket” as the audio output ; in the case of detection of core gap, “a yellow light” as the visual output and “Core Gap” as the audio output and in the case of detection of no abnormalities, “a green light” as the visual output and “Good product” as the audio output.
At least one ECHO sensor is to be attached to each micro-controller i.e. IC1, IC2, IC3 & IC4. The present invention has been worked with several different combinations of number of sensors attached to each such micro-controller, and can vary from a minimum of one to five such sensors attached to each of micro-controller. The number of sensors can vary on each such micro-controller irrespective of the number of sensors attached on the other micro-controller.
LIST OF REFERENCE NUMERALS
100 - A machine for the detection of abnormalities in wood-based products
B - Conveyor Belt
BG - Bearing Guide
D - Motor Driver
E1, E2, E3, E4, E5, E6, E7, E8, E9, E10, E11, E12, E13, E14, E15, E16, E17, E18, E19, E20 - Echo Sensors
G - Guide
HMI - Human-Machine Interface
I - Inlet
IC1, IC2, IC3, IC4, IC5 - Micro-Controllers
L - Leg
LS - Leg Support
M - DC Motor
MC - Micro-Controller with raspberry pi as its operating system
MCB - Main Controller Board
O - Output
OCB - Output Controller Board
PS1, PS2, PS3, PS4 - Part sensors
R - Rollers
SH - Echo Sensor Holder
SMPS1, SMPS2, SMPS3 - Switched Mode Power Supply