Design Of Multi-Sensor Detection System Based On ARM

Among industrial control system,smart home and sensor experiments, the sensor data acquisition system is used to complete the data acquisition for temperature,pressure,humidity,speed,acceleration and other parameters, to complete the output and input of digital signal and switch signal, information fusion and other issues.This paper analysied the characteristics of college laboratory equipments and industrial data acquisition systems and current situation of laboratory of school of Automation in Wuhan University of Technology. According to analysis result, the multi-sensor detection system, which can complete sensor data acquisition at a sampling rate of 100kbps, was designed in this paper to meet the requirements of sensor experiments.This paper mainly includes three parts of the sensor data acquisition system design, such as hardware design, software design and the algorithm of sensor information procession. The hardware design of the system mainly includes gate circuit for low-frequency analog signal between 1Hz and 10kHz, signal processing circuit with programmable amplification, data acquisition and processing circuit for rotational speed, input circuits and output circuits for switch signal, human-machine interface circuit, microprocessor circuit and others. The LPC2214, which belongs to ARM7 series, was used as the processor of this system.The program of this system includes slave computer program and master computer program. The former includes subprogram for external analog channels gating, subprogram for programmable amplification of signal and subprogram for human-machine interface, while, the later includes subprogram for communication between master computer and slave computer through the serial port, subprogram for sensor data display,data record,alert,data query and data print.In order to reduce the systematic error of thesystem to improve the acquisition accuracy, this paper used some filtering algorithms to filter out the interference signal, such as mean filtering,threshold filtering. It also used BP neural network algorithm to complete the fusion of sensor data and the nonlinear processing. The system was used to complete the data acquisition for small range weighing sensor, and then the BP neural network algorithm was used to complete non-linear processing for sensor in this paper.