Abstract:
This disclosure relates to a real-time video extensometer. Typically, the apparatus of the disclosure combines the image source, data processing and electrical output on to a single processing board in order to achieve high frequency images and low latency times on data flow. Further, the video processing engine processes the image on a pixel basis and updating the output the intermediate extension/strain result so that after receipt of the final image pixel, a final extension/strain value is achieved and immediately output for evaluation.

Description:
[0001]    This application claims priority under 35 U.S.C. 119(e) of U.S. provisional application Ser. No. 62/029,650, filed on Jul. 28, 2014, the contents of which is hereby incorporated by reference in its entirety and for all purposes. 
     
    
     BACKGROUND OF THE DISCLOSURE 
       [0002]    Field of the Disclosure 
         [0003]    The disclosure relates to a method of real-time measuring strain and related data by use of video methods. 
         [0004]    Description of the Prior Art 
         [0005]    Video extensometry is known in the prior art and well-developed for its intended purposes. However, a significant restrictive aspect of measuring strain with a video device is collecting the images at significant speed, providing the images to an image processing engine, processing the images to produce a displacement or strain value, outputting the strain value in a software consumable format and synchronizing it with other data collected via traditional real-time methods (e.g. load cells have electrically balanced bridges). 
         [0006]    There are many manufacturers of video processing extensometers. Some of the major companies that provide these are Shimadzo, Zwick and Imetrum. Generally, all of these use the methodology of employing an external machine vision camera, inputting into the PC or video processing hardware and using hardware to convert the data to an electrical signal or having a software interface compatible with the materials testing system. 
         [0007]    The prior art includes IPVE and AVE 1 which are manufactured by Instron and which are well developed for their intended purposes. These devices utilize an external camera, PC and analog outputs to capture images and process strain values from these images. The strain data is calculated by software in the PC and output via analog outputs. This is illustrated in  FIG. 1 . 
         [0008]    There are many algorithms for calculating strain from a video images and each has advantages and disadvantages. The main drawback to most of the systems is they use an off-the-shelf high speed machine vision camera, transmit the images via a high speed bus to a processing system, manipulate the images using a standard or dedicated processing system such as a PC or microcontroller and then output the data internally to software on the processing system or via convertors to electrical signals. Typically these systems consume an entire image and work on the array of pixels to produce a strain or displacement value. Computing strain or displacement in this manner is computationally intensive and requires a large microprocessor system. Additionally, to guarantee real-time behavior in order to fulfill many materials testing needs, a real-time operating system is used on the processing system. After computation of the strain or displacement data, it is output to the software on a PC which requires a specialized interface and is not very portable or output via an analog or encoder device. These systems have issues with respect to time latency, integration and required computational power. 
       OBJECTS AND SUMMARY OF THE DISCLOSURE 
       [0009]    It is therefore an object of the present disclosure to develop further improvements with respect to a real-time video extensometer. 
         [0010]    Embodiments of this disclosure address the above-identified deficiencies by combining the image source, data processing and electrical output on to a single processing board in order to achieve high frequency images and low latency times on data flow. Further, the data processing engine or FGPA (field programmable gate array) processes the image on a pixel basis and updating the output the intermediate strain result so that after receipt of the final image pixel, a final extension/strain value is achieved and immediately output for evaluation. This hardware and process makes the real-time video extensometer similar to traditional electro-mechanical devices (such as clip-ons) and allows them to be connected and used by materials testing systems in the same manner. The net result of the high speed real-time video processing is the greatly improved accuracy, much faster tracking of the specimen elongation and very low latency data which allows the user to perform and meet a complete range of testing standards. 
         [0011]    The real-time video extensometer combines the image inputs, data processing engine and extension/strain data output onto a single video processing board to minimize input and output data latency and maximize processing speed. The video processing board also eliminates the external latency and processing time issues related to operating systems. The primary reason for the improvement with respect to the processing system is the implementation of the entire algorithm on the FPGA (field programmable gate array) portion of the data processing system. The design and implementation makes the entire data path from input occur in hardware and therefore the entire system is deterministic and high speed. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0012]    Further objects and advantages of the disclosure will become apparent from the following description and from the accompanying drawings, wherein: 
           [0013]      FIG. 1  is a perspective view of the prior art. 
           [0014]      FIG. 2  is a perspective view of components of the apparatus of the present disclosure. 
           [0015]      FIG. 3  is a schematic of the apparatus of the present disclosure. 
           [0016]      FIG. 4  is a block diagram of the video processing board of the apparatus of the present disclosure. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
       [0017]    Referring now to the drawings in detail wherein like numerals refer to like elements throughout the several views, one sees that  FIG. 1  is an extensometer  1000  of the prior art. This extensometer  1000  utilizes an external camera, PC and data communications to capture images and produce extension/strain values. The extension/strain data is calculated by software in both the PC and via analog outputs. More specifically, electronics housing  1010  holds a printed circuit board, a camera (typically with a polarizing and light filter), and lenses for different fields of view. The image received by the camera is taken through a constant density air tube (CDAT)  1020 . An integral illumination unit  1030  is fixed to the side of the constant density air tube (CDAT)  1020 . Further, a two-dimensional calibration fixture  1040  is provided. 
         [0018]      FIG. 2  illustrates the external appearance of an embodiment of the real-time video extensometer  10  of the present disclosure. The real-time video extensometer  10  includes an integral illumination unit  12 , implemented as an LED array, to illuminate the specimen (see  FIG. 3 , element  200 , as well as video targets  202  which are painted or otherwise affixed to the specimen  200 ) under test, as implemented by test frame  190  of  FIG. 3 . The real-time video extensometer  10  further includes an electronics housing  14 , including a printed circuit board or video processing board  15  (also see  FIGS. 3 and 4 ) and a camera or image sensor  16  (also see  FIG. 3 ) with a polarizing filter  17  (see  FIG. 3 ). The camera or image sensor  16  includes various lenses for a range of fields of view. The electronics housing  14  further includes lens access  18  to allow access to the various lenses and a plate to calibrate the real-time video extensometer  10 . Additionally, the extensometer  10  includes a constant density air tube (CDAT)  20  and 90 degree light polarization on the integral illumination unit  12  (implemented as an LED array) and the lens of camera  16 . A two-dimensional calibration fixture  21 , similar to that of the prior art, is additionally used. 
         [0019]    As shown in  FIG. 3 , the video processing board  15  includes a field programmable gate array (FPGA)  22  (to increase processing speed) and a microprocessor  24 . The video processing board further includes line  19  to control the fans  20 ′ of the constant density air tube (CDAT)  20  in order to create a virtual air tube. The real-time video extensometer  10  connects to the materials testing machine (test frame  190 ) and software utilizing standard interfaces that includes Ethernet, analog, encoder or SPI. This allows the device to be plugged into and used by existing systems without the need for specialized integration software or hardware. The real-time video extensometer  10  provides axial and transverse encoder or analog information to materials testing machine  190  through lines  302 ,  304 , respectively. Materials testing machine  190  provides trigger/synch information to real-time video extensometer  10  through line  306 . Real-time video extensometer  10  and materials testing machine  190  exchange real-time test data, including extension/strain data, with the external computer  400  (illustrated as a laptop, although it is envisioned that other computing or processing devices may be implemented) via lines  308 ,  310 , which may be configured via an ethernet connection. Typically, the real-time video extensometer  10  provides extension/strain data to the materials testing machine  190 , which in turn, provides stress and extension/strain data to the external computer  400 . 
         [0020]      FIG. 4  is a block diagram which is an overview of a typical embodiment of the real-time video extensometer  10  of the present disclosure. The video image is input to the system using an onboard image sensor  16  or auxiliary camera link connector input  40  (also shown in  FIG. 3 ). The image data collected is consumed by the processing system entirely in the programmable logic (see FPGA  22  of  FIG. 3 ) of the processing system  30  (such as, but not limited to, a Zync XC7020 SoC) where specialized logic is utilized to calculate multiple axes of extension/strain values (i.e., the change or percentage change in inter-target distance as calculated by video monitoring of the video targets  202  affixed to specimen  200  as shown on  FIG. 3 ) and output the data to materials testing machine  190  ( FIG. 3 ) via the onboard axial or transverse digital-to-analog converter (DAC)  32  or  34 , encoder  36  or SPI interface  38  electrical outputs, ultimately leading through lines  302 ,  304  of  FIG. 3 . More specifically, Digital-to-Analog Converter (DACs)  32 ,  34  provide axial and transverse, respectively, strain or displacement signals (typically in the range of negative ten volts to positive ten volts) that allow two separate (typically axial and transverse, or otherwise orthogonal to each other) strain or displacement signals to be output in real-time to the materials testing machine  190 . Encoder  36  may include two quadrature encoder outputs that allow two separate strain or displacement signals to be output in real-time to a materials testing controller. The SPI interface  38  communicates digitized signals to any number of PCs, and further outputs in real-time to the materials testing machine  190 . 
         [0021]    Further functions of the real-time video extensometer  10  are typically implemented by the main printed circuit board implemented as the video processing board  15 . 
         [0022]    On-board imager and lens (camera)  16  implements a machine vision image sensor to provide high speed images to the processing system  30 . 
         [0023]    Auxiliary camera link connector input  40  uses standard connectors to allow the use of an off-the-shelf machine vision camera. This can be used in place of the on-board imager and lens (camera)  16  or in conjunction with it. An accelerometer  42  is mounted at the lens  16  to detect acceleration (typically in all three dimensions) for use in the algorithm and/or event detector. 
         [0024]    Sync  44  allows an external device such as a materials test machine  190  (see  FIG. 3 ) to provide a synchronization pulse via line  306  (see  FIG. 3 ) to time-stamp images sent to the external computer or PC  400  (see  FIG. 3 ) for later alignment. This time-stamping allows for the addition calculation of a time-dependent stress/strain test result from images (which may be a post--processing result). Similarly, trigger  46  allows an external device such as a materials testing machine  190  to trigger an event via line  306  (see  FIG. 3 ) in the data processing engine and perform functionality such as high speed image buffering and transmission to the external computer or PC  400  (see  FIG. 3 ). This allows for the real-time calculation of a time-dependent stress/strain test result. 
         [0025]    Fan control  19  the speed control of the fans  20 ′ of the CD AT  20  to optimize the CDATs  20  for distance. LED control  48  includes two banks of LED/projector array controls to utilize with the two different cameras. 
         [0026]    Video GigE block  50  provides an ethernet connection dedicated to high speed image transfers. Similarly, User GigE block  52  and Controller GigE block  54  provide ethernet connections to allow the processing system  30  and the controller f the materials testing machine  190  to communicate via an Ethernet switch  56  to external computer PC  400 . 
         [0027]    USB port  58  provides debug and messaging to the image processing engine. 
         [0028]    DDR 3 RAM  60  provides internal memory to allow storage of images and other data as captured by the high speed image sensor  16 . Furthermore, some embodiments may include a SODIMM connection (not pictured) to provide an onboard memory connection to allow the storage of high speed and long duration images from the high speed image sensor  16 . 
         [0029]    Embodiments of the present disclosure typically have many of the following advantages: 
         [0030]    1. High speed data input, data processing and data output. 
         [0031]    2. Hardware (FPGA) based algorithm implementation for real-time deterministic behavior without side effects of microprocessor or PC systems. 
         [0032]    3. Single board instead of many hardware pieces integrated together. 
         [0033]    4. Major cost reduction of the camera, processing system and output device. This provides price flexibility while still achieving very high specifications. 
         [0034]    5. Standalone video device directly outputs extension or strain and can be used on many existing systems. 
         [0035]    6. Ease of use due to the standalone capability. It is similar to the standard clip-on extensometers. 
         [0036]    7. The device can provide data at a rate that can be used for closed loop control. 
         [0037]    8. The device can be used on higher speed application due to the increased data rate. For example, this can be used to collect data and perform control on a dynamic system running a sinusoidal waveform. 
         [0038]    Substantial advantages of typical embodiments of this disclosure are greatly improved accuracy, much faster tracking of the specimen and very low latency data which allows the user to perform and meet a complete range of testing standards. 
         [0039]    A typical testing procedure is illustrated by  FIG. 3 . The specimen  200  with video targets  202  is engaged within materials testing machine  190 . Proximate to the time when specimen  200  is subjected to a stress-inducing load by materials testing machine  190 , a command signal is sent to the video processing board  15  and the materials testing machine  190  to the external computer  400 . The real-time video extensometer  10  then captures the absolute distance between video targets  202  and monitors the relative movement of video targets  202  to calculate extension/strain in real time. The stress data and the strain data exchanged among the real-time video extensometer  10 , the materials testing machine  190  and the external computer  400 , and typically organized and displayed via the screen of the external computer  400 . 
         [0040]    Thus the several aforementioned objects and advantages are most effectively attained. Although preferred embodiments of the invention have been disclosed and described in detail herein, it should be understood that this invention is in no sense limited thereby.