| By the developing of traditional industry, heavy metal caused water pollution has not only harms to human health, but also damages ecosystems. So it's important to detect the heavy metal contents in the rivers and lakes. With the development of wireless sensor network (WSN), heavy mental detection technologies have been wildly applied in environment protection. This project aims to design a heavy metal detection system based on wireless technology and heavy metal sensors.Firstly, the damage of heavy metals and heavy metal detection solutions were introduced. Then, the test methods and principles of normal electrode, microelectrode array, LAPS and the Hybird Photo-electrical sensors were reviewed.In the data processing module, finite impulse response (FIR) filter was applied to remove high frequency noise and a multiple linear regression model was implemented in Photo-electrical sensors. A windowed-baseline remove method was applied to eliminate the impact of the irregular baseline and partial least squares method was introduced to deal with the recognition of ions.The heavy metal wireless detection system was composed by wireless detection node and wireless node management software. The wireless detection node emploied ARM9 as a control board with Linux operating system. Processes of network service control and LAPS/MEA detection board control ran on the ARM9 simultaneously to receive commands from and send data to management software. Wireless node manager software was designed based on cross-platform Qt library. It was compatible both on Windows and Linux operating systems. The main function of this software was remote node finding, data analysis and measurement process control.At last, this project illustrated the practical application of heavy metal wireless analysis system and heavy metal analyzer on ships, analyzed and verified wireless coverage distance and software performance. The results proved that the system was competent for requirements of heavy metal detection. |
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