Internet of Things analog signal sampling method

Abstract

The invention discloses an Internet of Things analog signal sampling method. The Internet of Things analog signal sampling method is applicable to parameter (vibration and current) acquisition of rotary mechanical equipment and comprises the steps that S01, multiple running period data is sampled; S02, FFT processing is conducted on the data, and frequency of a spectral line having the maximum energy value of the data is calculated; S03, data periodicity is calculated and acquired according to the frequency of the spectral line having the maximum energy value; S04, based on the data periodicity, one period data is taken as reference data; S05, sampling is performed according to the data periodicity, the similarity of each period data and the reference data is judged, the next step is executed if the similarity large, and if the similarity is small, the sampling frequency is improved, multiple running period data is acquired, and then the step S02 is repeated; S06, the data is saved and the sampling frequency and the sampled data are uploaded. The acquisition mode variable in sampling frequency is adopted, key time point data is sampled at high frequency, common data is sample at low frequency, and the value of acquired data is embodied to the highest degree.

Description

technical field [0001] The invention relates to the field of the Internet of Things, in particular to a method for collecting analog signals of the Internet of Things. Background technique [0002] When the Internet of Things collects analog data, in view of the limitations of network bandwidth and server capacity, it is expected that the collected data can effectively reflect the value. When the existing equipment collects data remotely, it usually adopts a higher sampling frequency, which greatly increases the network burden and server storage burden. When the network is abnormal, the amount of local data storage will be increased, and data will be lost for a long time, thereby increasing the cost of remote maintenance. Another type of instrument adopts a lower sampling frequency. In the case of abnormal remote data, the lower sampling frequency basically cannot meet the needs of abnormal situation analysis, making the entire Internet of Things system lose its due functio...

AI Technical Summary

Problems solved by technology

[0007] All three existing technologies have irreparable shortcomings

When the three systems collect analog data, they cannot intelligently adjust the sampling frequency and reporting data frequency, which will cause loss or delay of valid data and cause a certain lag in troubleshooting

Images