Subsurface Electrical Device Fault Detection via Diagnostic Parameter Extraction
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Solution Overview
Problem
Conventional methods for monitoring electrical devices like ESPs in remote locations are inefficient due to limited bandwidth for high sample rate data transmission, making it difficult to detect faults in a timely manner.
Innovation Solution
A system and method that selects measured parameters from sensors, removes invalid samples based on predefined criteria, computes diagnostic parameters, and evaluates these against stored rules to determine the operating condition of the electrical device, enabling effective remote monitoring and diagnostics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high sample rate data is transmitted from the accelerometer, then fault detection precision is improved, but bandwidth consumption increases
Solution Approach 1:
The system performs preliminary processing of accelerometer data at the remote location by computing diagnostic parameters (RMS, peak values, frequency spectrum) before transmission. This preliminary computation reduces the data volume to be transmitted while preserving the essential diagnostic information needed for fault detection, thereby resolving the contradiction between detection precision and bandwidth consumption.
Solution Approach 2:
The system extracts only the essential diagnostic parameters from the raw accelerometer data rather than transmitting the complete high-sample-rate signal. By taking out only the relevant features (RMS, peak values, spectral characteristics), the system maintains fault detection capability while significantly reducing the quantity of transmitted data.
2Reliability
If continuous monitoring is performed, then reliability is improved, but loss of time for data transmission increases
Solution Approach 1:
The system computes diagnostic parameters locally in real-time before transmission is needed. This preliminary computation enables continuous monitoring of device health at the remote location while minimizing transmission time, as only processed results rather than raw continuous data need to be transmitted.
Data Source
AI summary
A method for fault detection includes selecting a measured parameter from a subsurface electrical device and obtaining a plurality of samples for the measured parameter. The method also includes removing at least one invalid sample from the plurality of samples to generate a remaining number of samples. The method further includes computing a diagnostic parameter based on the remaining number of samples, if the remaining number of samples is greater than a predefined threshold number and terminating the method otherwise. The method also includes obtaining a rule from a plurality of rules stored in a database, based on the diagnostic parameter. The rule is indicative of a standard operating condition of the subsurface electrical device. The method further includes evaluating whether the determined diagnostic parameter satisfies the obtained rule, to generate an output and determining a measured operating condition of the subsurface electrical device based on the output.