The Research On Pipeline Magnetic Flux Leakage Data Collection And Compression Algorithm

In order to enhance the measure precision and expand the using area of the existing oil pipeline MFL(Magnetic Flux Leakage) detecting system to natural gas pipeline testing, detailed information of flux obtained by decreasing sampling time and space interval is needed. The huge amount of data produced by this will exceed the processing ability. So existing systems must be improved.FPGA (Field-Programmable Gate Array) has merit of high integrated level the high speed and programmable in system etc, then has very applied extensively to the ultrafast signal process and in measure and control in real time. DSP (Digital Signal Processing) is a micro processor designed with real time and fast realization of various digital signal processing algorithm and specific structure. I studies and designs the measure and control system of pipeline magnetic flux leakage based on FPGA which is the core of data collection and DSP which is the core of data compression.The design is divided into two parts: multi data collection and control unit and data compression unit. The part of FPGA of multi data collection and control unit is composed by multi data collection unit and data temporary store unit. Multi data collection and control unit provide multi channel choice signal and A/D sample control time order. Data temporary store unit is to store the collected data temporarily and transport them to the part of data compression. Data compression unit compress the real measured data using one order embedded zero code algorithm. This method firstly handle the measured data using one order algorithm to decrease the scale of data distribution and improve the data compression then code them by embedded zero code algorithm in order to compress the data. In the last data which have been compression stored in the hard disk is decompressed.Through mass of experiment the compression rate of one order embedded zero code algorithm can reach about 8:1 and through comparison between raw data and decompresseddata the value of SPNR of decompressed data relative to the raw data can reach above 45 dB. Compressed data can replace the raw data to store completely.