Corrosion Potential Sensor for Remote Monitoring of Civil Structure Based on Printed Circuit Board Sensor
Bibliographic record
Abstract
We present a printed circuit board-based wireless inductively coupled corrosion potential sensor for monitoring corrosion of steel-reinforced concrete civil infrastructure. The sensor is a passive LC coil resonator whose resonant frequency varies owing to the corrosion potential produced by two electrodes connected across a voltage-controlled capacitor. The junction capacitance of the voltage-controlled capacitor also varies according to the potential generated by the two electrodes, which is in turn responsible for changing resonant frequency of the sensor. The two electrodes are a stainless steel reference electrode and a steel reinforcement electrode. An external interrogator coil coupled with the sensor coil monitors the sensor resonant frequency shift remotely by measuring the impedance change from the source end. The sensor has a sensitivity of ~1.2 kHz/mV both before and after it is embedded in the cement-based mortar used for testing the sensor. The sensor can be used to sense the corrosion susceptibility of existing structures by embedding the corrosion electrodes in new grout within a small slot formed in an existing structure. Using this approach, weight concentrations of NaCl mixed in cement-based mortars of greater than 2%-3% were detected. Accelerated corrosion tests on embedded sensors in simulations of both new and existing structure demonstrated corrosion potential resolution of less than 10 mV and an uncertainty of less than 50 mV. The sensor is simple in design, inexpensive, and passive making it a battery-less option for long-term corrosion monitoring, and widely deployable for civil structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".