<p class="has-ast-global-color-8-color has-text-color has-link-color wp-elements-de6e2267e688cf7c02bf964a7c2630be wp-block-paragraph"><strong>Project Identity:</strong><em> Bianque-System</em><br><strong>Author:</strong><em> Yi Zeng</em><br><strong>Manuscript PDF</strong>:<em> </em><a href="https://www.researchgate.net/publication/407033609_From_Causal_Auditing_to_Value_Maximization_for_Core_Distribution_Assets-Part_I_Underground_Cable_Management?_sg%5B0%5D=QmJFgDmBsHtmP5ZVUtdWBpqROFMOOYmq8jmFZuimDSpwu9AzPm134GjiR9DYpAd7urotbUv15CgkNJHDOYVX8mWg8eriBtfknBjpmADW.vq68eEqikG4hlAFgT0-nuFX8Szs88hCgPsMIb7ay7kZOu6HwYOJ4byv5gauO5wRzJtNgWrKdb2ajeOiluLNqRg&_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6InByb2ZpbGUiLCJwYWdlIjoicHJvZmlsZSIsInByZXZpb3VzUGFnZSI6InByb2ZpbGUiLCJwb3NpdGlvbiI6InBhZ2VDb250ZW50In19" target="_blank" rel="noreferrer noopener">Read the Full Paper Here</a>(ResearchGate)<br><strong>DOI:</strong><em> </em><a href="https://doi.org/10.5281/zenodo.20810645" target="_blank" rel="noreferrer noopener">10.5281/zenodo.20676445</a><br><em><strong>GITHUB</strong>:</em><a href="https://github.com/Shinar-of-Clark/Bianque-System" target="_blank" rel="noreferrer noopener">Shinar-of-Clark/Laplace_Paper_Framework</a><br></p>
<p class="has-ast-global-color-8-color has-text-color has-link-color wp-elements-3325d7dea27c91a6b8cfcd53798c7726 wp-block-paragraph">This paper aims to address the “Population Fallacy” dilemma in the maintenance of underground cables in smart distribution networks. Conventional O&M strategies rely excessively on uniform alarm thresholds and static depreciation models based purely on calendar time (e.g., MTBF). Such a “one-size-fits-all” paradigm ignores the inherent microscopic manufacturing defects and highly uneven environmental erosion of cable insulation, inevitably leading to the premature retirement of healthy assets or unexpected breakdowns of high-risk assets. To break this deadlock, this paper proposes the “Bianque System”—a novel asset management paradigm shifting from population statistics to an “Individualized Health Ledger”. We construct a non-intrusive sensing framework that deeply integrates failure physics with survival analysis algorithms. First, using the cumulative equivalent operational flux as the lifecycle baseline, the system derives seven major physical and electromagnetic degradation equations (including Arrhenius thermal aging, harmonic skin effect heating, short-circuit I2t mechanical damage, arrester-count-based electrical fatigue, moisture penetration dynamics, abnormal sheath circulation, and high-frequency partial discharge). These accurately map multi-dimensional disaster-inducing stresses into feature vectors readable by survival models. Second, cutting-edge Neural Cox and Transformer survival models are introduced to replace conventional linear assumptions, characterizing the nonlinear cumulative fatigue under intertwined stresses with high precision and outputting individualized Weibull survival curves (a thousand curves for a thousand cables). Furthermore, this paper pioneers a “dynamic closed-loop calibration” mechanism deeply coupling online prediction with offline VLF (Very Low Frequency) inspection, utilizing the actual diagnostic error for backpropagation to correct the algorithm’s penalty weights (β). Finally, utilizing the ECE-calibrated high-confidence survival probabilities combined with Optimal Stopping Theory, the system successfully solves for the economic red line of maintenance value maximization while strictly guarding the safety baseline, providing a full-lifecycle Digital Twin solution for next-generation distribution asset management.</p>
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Project Identity: Bianque-System
Author: Yi Zeng
Manuscript PDF: Read the Full Paper Here(ResearchGate)
DOI: 10.5281/zenodo.20676445
GITHUB:Shinar-of-Clark/Laplace_Paper_Framework
This paper aims to address the “Population Fallacy” dilemma in the maintenance of underground cables in smart distribution networks. Conventional O&M strategies rely excessively on uniform alarm thresholds and static depreciation models based purely on calendar time (e.g., MTBF). Such a “one-size-fits-all” paradigm ignores the inherent microscopic manufacturing defects and highly uneven environmental erosion of cable insulation, inevitably leading to the premature retirement of healthy assets or unexpected breakdowns of high-risk assets. To break this deadlock, this paper proposes the “Bianque System”—a novel asset management paradigm shifting from population statistics to an “Individualized Health Ledger”. We construct a non-intrusive sensing framework that deeply integrates failure physics with survival analysis algorithms. First, using the cumulative equivalent operational flux as the lifecycle baseline, the system derives seven major physical and electromagnetic degradation equations (including Arrhenius thermal aging, harmonic skin effect heating, short-circuit I2t mechanical damage, arrester-count-based electrical fatigue, moisture penetration dynamics, abnormal sheath circulation, and high-frequency partial discharge). These accurately map multi-dimensional disaster-inducing stresses into feature vectors readable by survival models. Second, cutting-edge Neural Cox and Transformer survival models are introduced to replace conventional linear assumptions, characterizing the nonlinear cumulative fatigue under intertwined stresses with high precision and outputting individualized Weibull survival curves (a thousand curves for a thousand cables). Furthermore, this paper pioneers a “dynamic closed-loop calibration” mechanism deeply coupling online prediction with offline VLF (Very Low Frequency) inspection, utilizing the actual diagnostic error for backpropagation to correct the algorithm’s penalty weights (β). Finally, utilizing the ECE-calibrated high-confidence survival probabilities combined with Optimal Stopping Theory, the system successfully solves for the economic red line of maintenance value maximization while strictly guarding the safety baseline, providing a full-lifecycle Digital Twin solution for next-generation distribution asset management.
