Project Detail

Specialised testing and corrosion assessments of select transmission tower structures associated with an overhead High Voltage Alternating Current (HVAC) Electric Power transmission system in Brazil, South America were executed using corrosion prediction modeling. The purpose of the testing, inspection, and analysis for this project was to:

  • Perform indirect assessments of selected transmission tower structures
  • Assess the feasibility of applying corrosion risk model algorithms for galvanised transmission towers
  • Compare and correlate direct inspection results of tower footings with the risk model results
  • Demonstrate the validity of the technical approach for a full scale assessment project.

The project integrated corrosion science, field electrochemical and assessment technologies, with field deployable computing hardware in a tool that can provide real time risk ranking in the field.

A degradation classification criterion was developed to assist in characterising the findings of this project. This criterion is shown in Table 2 and is based on the metal loss of the steel members and other visual observations.

1. Introduction

A demonstration project of assessment methodology for high voltage transmission tower footings was carried out with the following objectives:

  • Perform indirect assessments of selected transmission tower structures
  • Demonstrate a corrosion risk model algorithm for galvanised transmission towers
  • Compare and correlate direct inspection results of tower footings with the risk model results
  • Demonstrate the validity of technical approach for a full scale assessment project.

1.1 Tower Assessed

Ten towers were selected on three circuits. Eight towers were actually assessed because inclement weather prevented the assessment of the other two towers. Table 1 lists the towers that were assessed and Figure 1 shows the locations of the towers displayed in Google Earth Images. Figure 2 shows a photograph of a typical electrical transmission tower encountered on this project.

Circuit Tower Number Latitude Longitude
ACDM 1 153 -22.558631 -42.893735
ACDM 1 174 -22.560661 -42.812508
ACDM 2 156 -22.558346 -42.893588
ACDM 2 165 -22.559004 -42.854979
ACDM 2 174 -22.560661 -42.812508
RMLA 1 & 2 41 -22.558908 -42.893731
RMLA 1 & 2 42 -22.558942 -42.890631
RMLA 1 & 2 61 -22.560933 -42.812338

 

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Figure 1: Overview of locations of the towers that were assessed

 

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Figure 2: Typical HVAC Transmission Tower

1.2 Tower Footing Components

The steel member foundations of the towers are a multi-component system. Figures 3 and 4 shows the components of the footings and their associated names used in this report.

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Figure 3: Inside view of tower footing Components Figure 4: Below ground components of tower footings

 

2.0 Technical approach

The technical approach involves the application of Direct Assessment methodology in a similar manner to integrity assessments for buried pipelines. Field electrochemical assessment technologies are utilized and critical data is recorded and stored in a field deployable computing hardware tool that can provide real time risk ranking in the field. This allows quick identification of towers with the highest risk of degradation and timely direction of remediation crews to those towers.

2.1 Corrosion Risk Ranking

A proprietary algorithm was developed from to evaluate the likelihood and severity of corrosion based on electrochemical data collected at each transmission tower. The algorithm integrates 16 electrochemical, chemical and physical measurements at each tower leg to determine the relative likelihood of corrosion of that tower leg.

To continually improve the performance of the model, the subsurface direct examination condition data of the footings are inputted into the model and it performs a Bayesian like update to its coefficients to better correlate with the direct observations. The algorithm development is based upon the assessment of the following factors:

  • Soil characteristics
  • Electrochemical factors
  • Electrical interferences
  • Design
  • Cathodic protection
  • Topograph

The corrosion severity index is computed using the following relationship:

The Soil Factor considers the absolute value of the soil resistivity and the variation in resistivity with depth and at each tower leg along with specific soil chemistry (soluble anions and cations) and drainage and topography and soil moisture. The Electrochemical Factor considers the measured structure-to-electrolyte potential of each tower leg and the measured corrosion rate at each leg as determined by linear polarization resistance (LPR). The Interference Factor accounts for the impact of static and dynamic stray current influences. The Design Factor considers materials and the type of fabrication and construction of the structure including protective coating type and/or presence of galvanizing. The Visual Factor accounts for the observed condition of the structure at the time of the investigation while the CP Factor considered the effectiveness of any existing cathodic protection.

The model output provides risk numbers on the individual categories as well as an overall risk number for each tower leg.

2.2 Risk Scores and Degradation Classification

The risk model provides a score for each footing and these are combined for a collective tower risk score. These scores translate to different degrees of degradation for different transmission systems. However, for a given transmission system the scores can provide a reasonable prediction of the average degradation of the footings for a tower.

A degradation classification criterion was developed to assist in characterising the findings of this project. This criterion is shown in Table 2 and is based on the metal loss of the steel members as measures in percent metal (section) loss and other visual observations.

Table 2: Degradation Classification Criteria

Degradation Classification Degree of Corrosion Visual Description
6 Extremely severe expect 50% to 100%metal loss Extreme amount of scale greater then 25mm thick with reported nodules and other indications of severe degradation.
5 Severe expect 40% to 70% metal loss Scale up to 25mm thick with severe pitting reported
4 Moderate to severe expect 30 to 50% metal loss Up to 50% reported metal loss
3 Moderate corrosion expect 10% to 40% Up to 10mm scale reported
2 Minor corrosion up to 10% metal loss General corrosion and pitting less than or equal to 10%
1 No corrosion to minor corrosion Zinc coating still intact in some places below grade

Table 3 provides both the description of the Degradation Classifications and the corresponding Total Risk Score for those classifications based on the data obtained from this project. This table was created by integrating the results of the subsurface direct examination of the tower footings with the corresponding risk scores.

Degradation Classification Total Risk Score Range Degree of Corrosion Visual Description
6 >1200 Extremely severe expect 50% to 9% metal loss Extreme amount of scale greater then 25mm thick with reported nodules and other indications of severe degradation.
5 1150 to 1250 Severe expect 40% to 70% metal loss Scale up to 25mm thick with severe pitting reported
4 1000 to 1175 Moderate to severe expect 30 to 50% metal loss Up to 50% reported metal loss
3 900 to 1050 Moderate corrosion expect 10% to 40% Up to 10mm scale reported
2 780 to 900 Minor corrosion up to 10% metal loss General corrosion and pitting less than or equal to 10%
1 <780 No corrosion to minor corrosion Zinc coating still intact in some places below grade

Figure 5 shows the results of the modeling for this case study. The bar graph colors and numerical indication represent the individual tower leg corrosion severity score.

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Figure 5: Display of risk scores by tower ranked in severity

3.0 Results

3.1 Degree of Degradation by Tower and by Leg

Table 4 provides a summary of the results of the assessment. The table is listed in increasing amounts of degradation and shows the correlation between the predicted and observed corrosion severity. Examples of minor, moderate and severe corrosion are shown in Figure 6-8.

By Tower By Leg Comments
Circuit Avg. of Degr. Total Risk
Index
Leg Risk Score Degr.
Rating
Figure #
ADCM-2-165 2.3 907 A 221 1 6 no appreciable corrosion
B 263 2
C 216 3
D 207 3 minor surface rusting
ADCM-2-176 2.5 999 A 216 2 7 up to 50% metal loss on some cross members
B 211 2
C 286 2
D 286 4
RMLA 1&2-42 3.0 972 A 207 3
B 263 3
C 286 3
D 216 3
RMLA 1&2-61 3.3 11056 A 221 3
B 211 4 severe localised attack at the soil/air interface
C 286 3
D 338 3
ADCM-2-156 4.0 913 A 263 2 8 up to 100% metal loss with cracking the remaining ligament of the cross
B 221 6
C 191 4
D 238 4
ADCM-1-153 4.3 1056 A 261 4
B 186 5
C 271 4
D 338 4
ADCM-1-174 4.3 1149 A 291 4 up to 50% metal loss on some cross members
B 286 6 up to 100% metal loss on some cross members
C 286 5 Over 50% metal loss on some cross members
D 286 2
RMLA 1&2-41 5.0 1455 A 438 5
B 338 5
C 263 5 25mm thick corrosion deposits
D 416 5

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Figure 6: ADCM-2-165, Leg A, no appreciable Corrosion loss

 

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Figure 7: ADCM-2-176, Leg D, up to 50% metal loss

 

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Figure 8: ADCM-2-156, Leg B, 100% metal loss in some locations

3.2 Nature of the Degradation

Fifty percent of the footings that were assessed had a degradation category of 4 or greater. This is indicative of metal loss between 30 to 100 percent on some components of the footings. The degradation tended to be more severe at the soil/air interface of the footings and in water table transition zones.
On Leg B of Tower ADCM-2-156 portions of an angle iron support had completely corroded away and the remaining ligament was cracked as shown in Figure 9.

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Figure 9: Tower ADCM-2-156, Leg B, severe metal loss with cracking

3.3 Model Performance

The principle purpose of the corrosion prediction model is to provide a relative ranking of the severity of degradation of the towers. As can be noted in Table 4, the Total Risk Score for a tower generally increased with increasing levels of degradation. Figure 10 shows this trend in a graphical format.

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Figure 10: Total Tower Risk Scores vs. Degradation Classification

To assist in remediation planning and budgeting, corrosion growth rates were applied to the data set to predict the corrosion classification with time. These rates were based on Linear Polarisation Resistance corrosion rates measured in the field at each tower leg. The results for this project indicate that significant corrosion damage will be expected within 5 years if remedial measures are not implemented.

By Tower Projected Degradation Classification
Circuit Avg. of Degr. 2013 2015 2023
ADCM-2-165 2.3 2.62 2.86 3.47
ADCM-2-176 2.5 3.01 3.35 4.20
RMLA 1&2-42 3.0 3.45 3.75 4.51
RMLA 1&2-61 3.3 3.59 3.82 4.39
ADCM-2-156 4.0 4.68 5.13 6.26
ADCM-1-153 4.3 4.71 5.01 5.78
ADCM-1-174 4.3 5.01 5.51 6.78
RMLA 1&2-41 5.0 5.74 6.23 7.46

4.0 Conclusions

The electric utility involved in this study operates over 80,000 transmission towers that are 30-50 years old. In an effort to ensure reliability of power delivery, a methodology was needed to assess the likelihood and severity of corrosion of the underground grillages associated with these structures. Hardware and software were developed to aid in data collection and a risk ranking model was developed using a corrosion severity indexing algorithm. The process was applied to a small sample of structures to evaluate the applicability of the process and to assess the predictive capabilities of the model.   The assessment found:

  • Two towers had an average Level 2 degradation
  • Two towers had an average Level 3 degradation
  • Three towers had an average Level 4 degradation
  • One tower had an average Level 5 degradation
  • No towers had an average Level 1 degradation

In addition, two towers had one footing each classified with Level 6 degradation indicating 50-100% section loss

The predictive capability of the risk ranking model was successful, even for the small population sampled. It is expected that the performance of the model will continue to improve with a larger sample size and as Bayesian updating with observed degradation results enhances the model’s algorithm with observed degradation data. The approach, process and model may now be used for large scale projects to assist in identifying structures that may be at risk due to corrosion.

 

The process of assessing towers for corrosion risk is typically followed by a direct examination phase of high risk towers (based on predicted corrosion severity, structural loading and operational criticality), which is then followed by the implementation of structure repairs and corrosion mitigation through the application of protective coatings and cathodic protection