ONEPREDICTㅣDigital Brain for Industrial Assets

Project

The client was considering implementing an automatic predictive diagnostics solution for key facilities as part of its Digital Transformation project, and onepredict was the candidate for its transformer facilities. Prior to the actual implementation, multiple tests were conducted on key features, namely diagnostics and precision of prediction, and the details of which are as follows.

1. Identifying failure and normal operation through the analysis of past DGA data, without the information on the failure status of each transformer

2. For faulty transformers, accurately predicting the time of unexpected failure using pre-failure DGA data

3. Verifying performance through a comparison of solution-suggested failure causes and repair measures with those of actual cases

Result

Guardione® Substation successfully passed the verification process.

1. Not only did guardione® solution accurately identify the normal transformer facility among various data, but it also predicted the time of failure for transformers with unexpected past failures.

2. Following the solution’s official implementation, a potential malfunction was diagnosed on a particular transformer, for which replacement of the insulation oil was suggested.

3. Just a few weeks later, a high frequency issue occurred with the same transformer, calling for a sudden insulation oil replacement, once again proving guardione® solution's diagnostics and prediction reliability.

4. The client continues to use guardione® through a licensing agreement that was concluded the following year, after seeing first-hand its predictive diagnostics and maintenance suggestion capabilities.

Project

The client was considering implementing an automatic predictive diagnostics solution for key facilities as part of its Digital Transformation project,

and onepredict was the candidate for its transformer facilities. Prior to the actual implementation, multiple tests were conducted on key features,

namely diagnostics and precision of prediction, and the details of which are as follows.

1. Identifying failure and normal operation through the analysis of past DGA data, without the information on the failure status of each transformer

2. For faulty transformers, accurately predicting the time of unexpected failure using pre-failure DGA data

3. Verifying performance through a comparison of solution-suggested failure causes and repair measures with those of actual cases

Result

Guardione® Substation successfully passed the verification process.

1. Not only did guardione® solution accurately identify the normal transformer facility among various data,

but it also predicted the time of failure for transformers with unexpected past failures.

2. Following the solution’s official implementation, a potential malfunction was diagnosed on a particular transformer,

for which replacement of the insulation oil was suggested.

3. Just a few weeks later, a high frequency issue occurred with the same transformer, calling for a sudden insulation oil replacement,

once again proving guardione® solution's diagnostics and prediction reliability.

4. The client continues to use guardione® through a licensing agreement that was concluded the following year,

after seeing first-hand its predictive diagnostics and maintenance suggestion capabilities.