A Study On Noise And Vibration Monitoring Network System

Taking a look at the development of the vessels, the noise of vibration has beenan unneglectable problem. To detect the vibration can not only help the peoplediagnose the running characteristic of the equipments in the vessels, but also has afar-reaching significance for the protection of the persons' health and the increase ofthe sound characteristic of some particular vessels. In order to detect the noisecharacteristic of the vessel vibration real-timely, to predict the sound fieldcharacteristic on typical navigational status, to monitor the running conditions of themainframes and auxiliaries and to increase the safety and reliability of the vessels, itis necessary to install real-time monitor network for vibration noise on the vessels.Considering the actual case of the vessels noise, a real-time monitor network forvibration noise is established. This paper studies on the four aspects below:1.The hardware implement project of the real-time monitor network:This paper puts forward a solution which includes the design of the network andnodes and applies the DSP+CPLD to the design of the nodes. Dividing up the systemtask, the design of the real-time monitor network system based on DSP+CPLD isfinished.2.The logic controller based on CPLD:Using the Verilog language and schematic, this paper designs the logic circuits ofthe data processing module in the nodes and carries out its timing and logic control.3.Using DSP to process the data:According to the system request and the noise characteristic of the vesselvibration, this paper puts forward the data processing arithmetic, including FFT, FIR.Using the assembly language and C language to program, the conversion from time tofrequency of 32 points is implemented.4.The test experiment of the nodes:Use the vibration platform to inflict the single frequency signal to the samechannel of the nodes. Observe the data result which has been processed by DSP andcompare it with the sample. Analyze the data based on large numbers of experimentsand calibrate the node.Then, comparing it with the sample, we sum up the maximumrelative error is 0.275%, and it can meet the system request.