A wireless data dynamic collection and transmission method

Abstract

The invention discloses a method for dynamic acquisition and transmission of wireless data. In a data acquisition process of the method, the time interval for data acquisition is dynamically adjusted, according to the change threshold of data acquisition. In a data storing process, the time interval and opportunity for data storing is dynamically adjusted according to the change threshold of data acquisition. In a data sending process, the opportunity for data sending is dynamically adjusted according to the acquisition value alarming threshold and changing rate alarming threshold of data acquisition. Dynamically increasing or reducing data sampling frequency without increasing power consumption of wireless equipment is realized based on data abnormity degree. Alarm information is timely sent by determination of dynamic data acquisition abnormity, so that managers can maintain equipment as early as possible. Wireless data bulk sent is reduced, and the power consumption of wireless monitoring equipment is reduced. The process state information of entire detected equipment can be monitored without increasing the total transmission data bulk.

Description

technical field [0001] The invention relates to the field of wireless sensor network information monitoring, in particular to a method for dynamic collection and transmission of data collected by sensors and transmitted in a wireless manner. Background technique [0002] At present, based on the particularity of many fields such as engineering structure health monitoring and environmental information monitoring and the advantages of wireless sensor network technology, the application of wireless sensor networks in these fields is becoming more and more extensive and important. [0003] Through the wireless sensor network, the status information of the equipment under test or the environment can be monitored online in a distributed, large-scale, and real-time manner, and alarms can be issued for abnormal conditions to reduce losses caused by major accidents. [0004] Based on the characteristics of the monitoring system of wireless sensor network technology, node energy consu...

AI Technical Summary

Problems solved by technology

This monitoring mode, because the data is collected once in a long period of time, the data will not be collected again during the time between the two adjacent data collections, so the device under test is between the two adjacent data collections. When there is an unexpected situation (such as a sudden rise in temperature, a sudden drop in pressure, a sudden increase in stress, etc.) within a certain period of time, it will not be found in time

[0006] However, if the sampling interval is shortened in order to detect emergencies in time, under the normal condition of the monitored equipment, it will inevitably cause too many invalid data transmissions, which will increase the power consumption of wireless sensor nodes.

Moreover, at present, when these wireless monitoring nodes are abnormal, due to the continuous transmission of instantaneous values, the transmission of invalid data in this process is also increased, and a part of energy consumption is wasted

At the same time, for the entire monitoring process, due to the fixed time interval between collection and sending, it is impossible to provide a more realistic process monitoring data

[0007] In general equipment process monitoring, characteristic values ​​are collected at fixed sampling intervals. Due to the limitation of the amount of sampled data, precise detection cannot be performed on unexpected abnormal states during equipment operation. It can only serve as a fault warning and cannot make a diagnosis of the cause of the fault. analyze

[0008] In addition, for general monitoring equipment, when there is a problem with the monitored equipment, the user will be notified to repair it. During the maintenance, the testing equipment needs to collect a large amount of data from the tested equipment, and some faults of the tested equipment cannot be reproduced. Therefore, the cause of the failure of these tested equipment cannot be judged

For example, for some large motors, when the vibration value exceeds a certain threshold, the user will be notified of an emergency shutdown and maintenance. However, part of the cause of the motor failure needs to be judged by collecting a large amount of vibration data when the motor fails and performing secondary analysis. However, these motors cannot be operated again, or even if they are restarted, some faults may not be reproduced again. Therefore, at this time, due to the inability to reproduce the collected data, it is impossible to make an accurate judgment on the cause of these equipment faults

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