Field Measurement Trend Compression for Predictive Diagnosis
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Solution Overview
Problem
Existing predictive diagnosis methods for field devices, such as vortex flowmeters, require continuous communication with external devices for extended periods, leading to reduced user convenience and the need for massive data storage if the connection is lost.
Innovation Solution
A field device equipped with a detector, a controller, and a memory that calculates and stores data for measured trends, allowing for local storage and compression of data, enabling predictive diagnosis without continuous external connection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the field device is continuously connected to an external device for extended periods to perform predictive diagnosis, then the measurement data can be collected and analyzed, but the user convenience is reduced and the system complexity increases
Solution Approach 1:
The field device performs predictive diagnosis independently using its own processor and storage unit. The processor calculates measured trends from detection signals and stores them locally, enabling the device to diagnose its own status without requiring continuous external device connection, thus improving user convenience while maintaining diagnostic reliability
Solution Approach 2:
The system is divided into independent functional units: the field device with detector and processor, and the external device. The field device can operate autonomously for predictive diagnosis, and the external device is only needed when data transmission is required, reducing the need for continuous connection and improving ease of operation
2Adaptability or versatility
If the field device stores a massive amount of past data to maintain predictive diagnosis capability without continuous connection, then the autonomous diagnostic capability is improved, but the storage capacity requirements and device complexity increase
Solution Approach 1:
The field device performs preliminary data processing by calculating measured trends from raw detection signals and storing only the essential trend data in its storage unit. This preliminary action reduces the volume of data that needs to be stored locally while maintaining the capability for autonomous predictive diagnosis, avoiding the need for massive data storage
Solution Approach 2:
The system extracts only the essential measured trend data from the raw detection signals for storage. By extracting and storing only the calculated trends rather than all raw data, the storage capacity requirements are reduced while the predictive diagnosis capability is preserved
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This configuration enhances user convenience by allowing predictive diagnosis to be performed independently by the field device, reducing the need for continuous communication and minimizing data storage requirements.
Implementation Method 1
a detector configured to detect a physical quantity and output a detection signal
Implementation Method 2
a controller configured to calculate, based on the detection signal, data for a measured trend indicating a temporal change in a parameter used for predictive diagnosis of the field device
Data Source
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AI summary
A field device (10) includes a detector (11) that detects a physical quantity and outputs a detection signal, a controller (121) that calculates, based on the detection signal, data for a measured trend indicating a temporal change in a parameter used for predictive diagnosis of the field device (10), and a memory (122) that stores the data. The controller (121) stores the data in the memory (122) at time intervals from the start time of measurement in the field device (10) to the current time and executes a compression process on the data stored in the memory (122) upon the amount of the data stored in the memory (122) reaching the upper limit of the storage capacity of the memory (122).