Method and device for equipment abnormality analysis based on real-time acquisition of sensor data

Abstract

The invention discloses a method and a device for analyzing equipment abnormality based on real-time acquisition of sensing data, and relates to the technical field of industrial equipment detection. , thereby optimizing the real-time analysis process, not only ensuring the timeliness of detection equipment for abnormalities, but also avoiding false alarms and improving detection accuracy. Stream data obtained in real time from sensors of production line equipment; use the sliding window of the stream computing engine to cache the sensing data; determine whether the sensing data cached in the sliding window satisfies the preset repetition condition; if so, then It is determined that the device is abnormal, and an alarm is triggered. The present invention is applied to detect whether there is an abnormality in the equipment by using the received sensor data in the application scenario combining edge computing and the industrial Internet of Things.

Description

technical field [0001] The invention relates to the technical field of industrial equipment detection, and in particular, to a method and device for analyzing equipment abnormality based on real-time acquisition of sensor data. Background technique [0002] The Industrial Internet of Things is the continuous integration of various acquisition and control sensors or controllers with sensing and monitoring capabilities, as well as mobile communication, intelligent analysis and other technologies into all aspects of the industrial production process, thereby greatly improving manufacturing efficiency, improving product quality and reducing product quality. Cost and resource consumption, and finally realize the upgrading of traditional industries to a new stage of intelligence. From the application form, the application of the Industrial Internet of Things has the characteristics of real-time, automation, embedded (software), security, and information interoperability. . [000...

AI Technical Summary

Problems solved by technology

However, as the workload increases, the temperature, humidity, pressure, flow, etc. of the equipment will suddenly increase, but the equipment will also have self-adaptive capabilities. There may be cases where the warning threshold is reached but the real situation is that the equipment does not work abnormally. , so if the alarm is triggered immediately when the detection reaches the early warning threshold, it is inevitable that false alarms will occur, resulting in inaccurate real-time analysis results of whether the detection equipment is abnormal.

Images