# A Novel Pipeline Age Evaluation: Considering Overall Condition Index and Neural Network Based on Measured Data

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## Abstract

**:**

## 1. Introduction

## 2. Literature Review

## 3. Evaluation Methods

#### 3.1. Overall Condition Index

#### 3.2. Neural Network

## 4. Data Monitoring

- The cathodic protection station (CPS) is set every 15 days, including pre-set voltage, pre-set current, pre-set injection voltage, pre-set cut-off voltage, post-set transformer voltage, and present, and the color is silica gel;
- Test point measurement (TP) is carried out every four months. If it is in the form of a pool, the cleaning of the pool should also be carried out, and if it is in the form of science, it is measured from the three parts of the science valve, the sheath, and the surge arrester;
- Measurement of flange insulation of turner broadcasting system (TBS) stations once every six months;
- Anodic control is performed every six months to measure the flow of anodes;
- Test the cover with a holiday device or by installing a current source by insulating the damaged points;
- AC line voltage measurement (caused by stray currents), according to US NACL standards, can be omitted if it is less than 15 volts (every four months). This voltage enters the line from one point, and from where it exits it will cause corrosion of the pipe in the same place;
- Existence of a protected structure next to a protected gas pipe (such as a water pipe). Additionally, two lines must be potentialized to prevent corrosion;
- The presence of DC voltage (700 volts) on city trains is harmful;
- The presence of AC voltage (20 kV) in the subway is harmful.

- DC voltage of measuring points in gas networks; the normal value of this voltage is between 0.85 and 2.1 volts;
- AC voltage of measuring points in gas networks; the maximum acceptable voltage is 15 volts;
- DC voltage measuring points. Before adjusting, if the voltage value is more than 2.1 volts and less than 0.85 volts it should be checked;
- The voltage of measuring points in the transformer off mode depends on the type of cover and transformer capacity;
- Circuit resistance in GPS stations; if it is more than 3 ohms, the circuit should be checked;
- Transformer output voltage depends on the injection voltage, and its value is adjusted according to the injection voltage;
- Transformer output current is determined according to the surface of the pipe and the amount of damage to the cover;
- Output current in 75 volts and 25 amps transformers can be from 1 to 25 amps;
- Anode current rate: MMO in water is 8 amps, and silicon in water is 4 amps;
- Water column: at the beginning of drilling, the well should be about 10 m above the anodes;
- Circuit resistance: factors that increase it are lowering the water level, cable cross-section, end of anodes, incomplete coding, and sulfation of cable washer and busbars inbox.

## 5. Case Study

#### 5.1. Results from the Overall Condition Index

^{−1}= 0.367 the equipment conditions will be critical.

#### 5.2. Predicting the Failure Time of Cathodic Protection by the Neural Network

## 6. Conclusions

#### Future Study

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 5.**Monitoring the general condition of equipment, (

**a**) Equipment item 1, (

**b**) Equipment item 2, (

**c**) Equipment item 3, (

**d**) Equipment item 4, (

**e**) Equipment item 5, (

**f**) Equipment item 6.

Method | Nazar Abad | Eshtehard | Karaj |
---|---|---|---|

Previous | 17 years and 7 months | 19 years and 9 months | 17 years and 2 months |

New | 16 years and 3 months | 18 years and 3 months | 16 years and 1 month |

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**MDPI and ACS Style**

Noroznia, H.; Gandomkar, M.; Nikoukar, J.; Aranizadeh, A.; Mirmozaffari, M.
A Novel Pipeline Age Evaluation: Considering Overall Condition Index and Neural Network Based on Measured Data. *Mach. Learn. Knowl. Extr.* **2023**, *5*, 252-268.
https://doi.org/10.3390/make5010016

**AMA Style**

Noroznia H, Gandomkar M, Nikoukar J, Aranizadeh A, Mirmozaffari M.
A Novel Pipeline Age Evaluation: Considering Overall Condition Index and Neural Network Based on Measured Data. *Machine Learning and Knowledge Extraction*. 2023; 5(1):252-268.
https://doi.org/10.3390/make5010016

**Chicago/Turabian Style**

Noroznia, Hassan, Majid Gandomkar, Javad Nikoukar, Ali Aranizadeh, and Mirpouya Mirmozaffari.
2023. "A Novel Pipeline Age Evaluation: Considering Overall Condition Index and Neural Network Based on Measured Data" *Machine Learning and Knowledge Extraction* 5, no. 1: 252-268.
https://doi.org/10.3390/make5010016