Research Of Data Acquisition System Based On Cortex-M3

The topic originates from partial contents of Research on Sparse Feature Identification ofInitial Fault for Large Low-speed Heavy-duty Machinery of the National Natural ScienceFoundation, which lays foundations for constructing diagnosis platform for initial fault oflow-speed heavy-duty machinery.In the process of working, low-speed heavy-duty mechanical equipment (such as converter,blast furnace, ladle turret etc.) is the key position in the metallurgical enterprises may breakdown, which can result in stoppage of the production line and further cause significant economicloss and social effect. In the actual industrial application, in order to identify initial fault, the keycomponents of the equipment are needed to conduct real-time data acquisition, transmission andsignal processing. The essay focuses on data interference, error, loss and other issues occurred inthe process from transferring test signal of site sensor to control room, provides solutions that isimplemented through direct site acquisition, and teletransmission via CAN bus or Ethernet,meanwhile, study profoundly on fault diagnosis and prediction methods for mechanicalequipment.Taking vibration signals from low-speed heavy-duty machinery as sampling object, a kindof multi-channel data acquisition system, which uses Cortex-M3-LPC1788as a microcontrolleris designed. Vibration signals through conditioning board of four-way synchronization andfour-way asynchronous circuit by the controlling of photoelectric switch to complete dataacquisition and transmission. The main control unit is based on ARM-Cortex-M3-LPC1788asmicrocontroller, and its interior integrates RS-485bus controller, CAN bus controller andEthernet controller, all of which can be combined as data communication method on site toenable site application more flexible and convenient. What’s more, so as to make fieldapplication convenient, there is adding a serial screen to input parameter configuration anddisplay status. Host computer use LabVIEW to analyse and process collected data, and thencomplete remote online real-time fault diagnosis and prediction of machinery equipment.This system is based on ARM-Cortex-M3kernel, which materially saves hardwarespending and development circle for the system. The system realizes stability and reliability ofdata acquisition, interface work-friendly, flexibility of communication, remote online monitoringand other functions.