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长春光学精密机械与物... [4]
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专题:长春光学精密机械与物理研究所
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Laser pulse coded signal frequency measuring device based on DSP and CPLD (EI CONFERENCE)
会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Laser Sensing and Imaging; and Biological and Medical Applications of Photonics Sensing and Imaging, May 24, 2011 - May 26, 2011, Beijing, China
Zhang H.-B.
;
Cao L.-H.
;
Geng A.-H.
;
Li Y.
;
Guo R.-H.
;
Wang T.-F.
收藏
  |  
浏览/下载:24/0
  |  
提交时间:2013/03/25
Laser pulse code is an anti-jamming measures used in semi-active laser guided weapons. On account of the laser-guided signals adopting pulse coding mode and the weak signal processing
it need complex calculations in the frequency measurement process according to the laser pulse code signal time correlation to meet the request in optoelectronic countermeasures in semi-active laser guided weapons. To ensure accurately completing frequency measurement in a short time
it needed to carry out self-related process with the pulse arrival time series composed of pulse arrival time
calculate the signal repetition period
and then identify the letter type to achieve signal decoding from determining the time value
number and rank number in a signal cycle by Using CPLD and DSP for signal processing chip
designing a laser-guided signal frequency measurement in the pulse frequency measurement device
improving the signal processing capability through the appropriate software algorithms. In this article
we introduced the principle of frequency measurement of the device
described the hardware components of the device
the system works and software
analyzed the impact of some system factors on the accuracy of the measurement. The experimental results indicated that this system improve the accuracy of the measurement under the premise of volume
real-time
anti-interference
low power of the laser pulse frequency measuring device. The practicality of the design
reliability has been demonstrated from the experimental point of view.
A high-speed acquisition and processing system of the laser speckle signal on the magnetic fluid (EI CONFERENCE)
会议论文
International Symposium on Photoelectronic Detection and Imaging 2009: Laser Sensing and Imaging, June 17, 2009 - June 19, 2009, Beijing, China
Wan Q.-H.
;
Jiang Y.
;
Su S.-C.
;
Sun Y.
;
Wu Y.-Z.
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  |  
浏览/下载:24/0
  |  
提交时间:2013/03/25
In order to achieve the dynamical detection and real-time analysis of the movement status of the magnetic fluid
according to the difficulties of the detection of the magnetic fluid
established a high-speed acquisition and processing system of laser speckle signal on the magnetic fluid. First of all
the FPGA (EP2C8T144C8N) drived the linear array CCD(TCD1501D) to scan in the corresponding time sequence given by the computer
collected the laser speckle interferometric image in rapid change on the surface of the magnetic fluid
which followed the movement of the magnetic fluid
and the signal collected by CCD was converted into the digital data through the high-speed A/D convertor and stored into the internal buffer FIFO of the FPGA
whose width and depth were designed by the user as required. Then
the FPGA sent the digital signal of the laser speckle interferometric images into the computer through the USB2.0 highspeed differential bus
whose transmission rate can reach 480Mb/s in theory. Finally
the distribution of the laser speckle on the magnetic fluid was messy and random
which carried certain information about the surface of the magnetic fluid
based on the theories of the statistic correlation and the subdivision of images
analysing and processing the laser speckle interferometric images
indirectly got the movement status of the magnetic fluid under the electromagnetic field. The experimental results show that: the High Speed Acquisition and Processing System has the advantage of full-court
non-contact
non-invasive
high-precision and high reliability and so on. The detection resolution of high speed acquisition and processing system is superior to 1m and the sample rate is 3Msps
which basically meets the requirements of the magnetic fluid movement state detection. 2009 SPIE.
Real-time quality control on a smart camera (EI CONFERENCE)
会议论文
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
Xiao C.
;
Zhou H.
;
Li G.
;
Hao Z.
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浏览/下载:18/0
  |  
提交时间:2013/03/25
A smart camera is composed of a video sensing
high-level video processing
communication and other affiliations within a single device. Such cameras are very important devices in quality control systems. This paper presents a prototyping development of a smart camera for quality control. The smart camera is divided to four parts: a CMOS sensor
a digital signal processor (DSP)
a CPLD and a display device. In order to improving the processing speed
low-level and high-level video processing algorithms are discussed to the embedded DSP-based platforms. The algorithms can quickly and automatic detect productions' quality defaults. All algorithms are tested under a Matlab-based prototyping implementation and migrated to the smart camera. The smart camera prototype automatic processes the video data and streams the results of the video data to the display devices and control devices. Control signals are send to produce-line to adjust the producing state within the required real-time constrains.
AE signal processing and DSP implementation based on wavelet packet analysis (EI CONFERENCE)
会议论文
ICMIT 2005: Information Systems and Signal Processing, September 20, 2005 - September 23, 2005, Changchun, China
Zhao J.
;
Wang K.
;
Yang M.
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  |  
浏览/下载:9/0
  |  
提交时间:2013/03/25
To improve the accuracy of AE (Acoustic Emission) testing
the wavelet packet analysis was introduced to process the AE signals. Extraction of the fault characteristic information would be influenced greatly if the faulted AE signal was not effectively denoised. Based on discussing the fast searching algorithm of BWPB (Best Wavelet Packet Basis) adopting Shannon entropy
a new method based on BWPB was presented to denoise the AE signal from the faulted composite plate. Analyzing was performed on the denoised signal and the fault characteristic information was exacted. To improve the real-time performance of the wavelet packet analysis algorithm
it was performed on the DSP (Digital Signal Processing) chip TMS320VC5409. The experimental results show that the algorithm can not only reduce the noise by 10dB but also effectively extract the faulted characteristics information from the AE signal.
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