corrosion_revised

docs/GPR/Applications/Corrosion.html

@@ -148,15 +148,15 @@ <h2>Prerequisites<a class="headerlink" href="#prerequisites" title="Link to this
 <section id="corrosion-assessment-results">
 <h2>Corrosion Assessment Results<a class="headerlink" href="#corrosion-assessment-results" title="Link to this heading"></a></h2>
 <p>Executing our code along with proper input variables, it automatically outputs interpolated rebar signal amplitudes in decibel unit. Figure 3 (a), (b), and (c) shows the pinpointed rebar signals on the split GPR B-scans. Our code reads the absolute amplitude values right on the rebar signals, save as a list. Subsequently, the code concatenates the split B-scans and generates 2D scatter plots for the entire data and splits the concatenated B-scans again to plot the 2D scatter plots along the actual four GPR scan lines (Figure 3 (d) and (e)). To check how the rebar signal amplitudes vary, we also output the amplitude distribution histogram on each lane (4 GPR lines), shown in Figure 3 (f). Lastly, the code outputs the interpolated amplitude contour for each lane (Figure 3 (g)).</p>
-<a class="reference internal image-reference" href="../../_images/Figure_3.png"><img alt="figure 3" class="align-center" src="../../_images/Figure_3.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_3_tz.png"><img alt="figure 3" class="align-center" src="../../_images/Figure_3_tz.png" style="width: 1000px;" /></a>
 <p>Figure 3. CHARISMA outputs from Mississippi I-10 Region 01 rebar cover depth for the first 4 GPR scan lines. Figure 3 (a), (b), and (c) are the rebar mapping result (3 examples among 20 split B-scans), (d) and (e) show the rebar coordinates, (f) displays the rebar amplitude distribution histogram, and (g) exhibits the interpolated 2D contour map.</p>
 <p>Figure 4 shows the output of processing GPR data with CHARISMA, which is the interpolated 2D contour from the entire lanes in the bridge Zone 01. Figure 4 (a) follows the ASTM standard, stating the rebar signals below -6 or -8 dB is suspected to be under corrosive environment. Figure 4 (b) is a rainbow contour map, which is also used in LTBP InfoBridge™. We repeat this process for the other zones to gather all the rebar points on the entire bridge.</p>
-<a class="reference internal image-reference" href="../../_images/Figure_4.png"><img alt="figure 4" class="align-center" src="../../_images/Figure_4.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_4_tz.png"><img alt="figure 4" class="align-center" src="../../_images/Figure_4_tz.png" style="width: 1000px;" /></a>
 <p>Figure 4. Interpolated reinforcing reflection amplitude 2D contour from the entire lanes in the bridge Zone 01. (a) follows the ASTM standard and (b) uses rainbow contour map. The black circle shows the reference points that have the maximum amplitude among each lane.</p>
 <p>Once we have obtained the rebar points from all regions, CHARISMA generates the rebar cover depth contour map for the entire bridge. It combines all the rebar point lists from individual regions and establishes a grid space based on the XML file. For each colormap (ASTM and rainbow), There are two options available: one involves plotting without interpolating the gap among regions (Figure 5 and 6 (a)), while the other interpolates the entire bridge based on the gathered rebar points (Figure 5 and 6 (b)). Since we use the linear interpolation method, there is no available value for the edges, which is shown in grey color.</p>
-<a class="reference internal image-reference" href="../../_images/Figure_5.png"><img alt="figure 5" class="align-center" src="../../_images/Figure_5.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_5_tz.png"><img alt="figure 5" class="align-center" src="../../_images/Figure_5_tz.png" style="width: 1000px;" /></a>
 <p>Figure 5. CHARISMA output (ASTM style): 2D contour plot of reinforcing reflection amplitude on Mississippi I-10 concrete bridge without interpolating the gap among regions (a), and with interpolating the entire bridge (b).</p>
-<a class="reference internal image-reference" href="../../_images/Figure_6.png"><img alt="figure 6" class="align-center" src="../../_images/Figure_6.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_6_tz.png"><img alt="figure 6" class="align-center" src="../../_images/Figure_6_tz.png" style="width: 1000px;" /></a>
 <p>Figure 6. CHARISMA output (Rainbow colormap): 2D contour plot of reinforcing reflection amplitude on Mississippi I-10 concrete bridge without interpolating the gap among regions (a), and with interpolating the entire bridge (b).</p>
 </section>
 <section id="discussion">
@@ -179,9 +179,9 @@ <h2>Jupyter Notebook – Mississippi Bridge<a class="headerlink" href="#jupyter-
 <p>For this reason, readers are directed to <a class="reference internal" href="rebar_cover_depth_case_study.html#code-explanation-rebar-cover-depth-section"><span class="std std-ref">Code Explanation</span></a> section from the Cover Depth Measurement, as the input parameters for the code are identical. We will also compare the two applications, highlighting the differences in the code.</p>
 <section id="corrosion-assessment-details">
 <h3>Corrosion Assessment Details<a class="headerlink" href="#corrosion-assessment-details" title="Link to this heading"></a></h3>
-<p>We first process the GPR B-scans with time-zero correction, background removal, F-K migration, and contrast adjustment. In accordance with the ASTM standards, we use the migrated data without any visual modifications (as contrast adjustment can alter the amplitude and affect the decibel values) to obtain the amplitude signals on the rebars.</p>
+<p>We first process the GPR B-scans using time-zero correction, background removal, F-K migration, and contrast adjustment. Following ASTM standards, we locate the rebars using the migrated data. Then, we use these rebar locations on the time-zero corrected data without any visual modifications (since contrast adjustment can alter the amplitude and affect the decibel values) to obtain the amplitude signals on the rebars. We noticed that the rebar locations from migration sometimes do not align precisely with the exact peak of the A-scan. Thus, we correct the rebar locations using the <code class="code docutils literal notranslate"><span class="pre">Scipy</span> <span class="pre">find_peaks</span></code> function.</p>
 <p>After mapping the rebars (unitless) with the migrated data, we create a Pandas dataframe to process further, as shown in Figure 7. In the dataframe, the rebar coordinate x represents the GPR survey line, and y represents the wave travel time. Since the rebar coordinates are not integers (the data is discrete and the amplitude between two data points is unknown), we use the <code class="code docutils literal notranslate"><span class="pre">SciPy</span> <span class="pre">interp2d</span></code> function to determine the amplitude at the exact points. Then, we convert the amplitude to a logarithmic scale in decibels and subtract it from the maximum dB value.</p>
-<a class="reference internal image-reference" href="../../_images/Figure_7.png"><img alt="figure 7" class="align-center" src="../../_images/Figure_7.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_7_tz.png"><img alt="figure 7" class="align-center" src="../../_images/Figure_7_tz.png" style="width: 1000px;" /></a>
 <p>Figure 7. (a) table is an output from the <code class="code docutils literal notranslate"><span class="pre">extract_reinforcing_reflection_amplitude</span></code> function, the first 20 rows in corrosion assessment data processing and the rows with the maximum amplitude. (b) shows the rebar points (red line) on the GPR a-scans to check whether the interpolation works correctly or not.</p>
 </section>
 </section>

docs/GPR/Applications/corrosion_case_study.html

@@ -123,15 +123,15 @@ <h1>Prerequisites<a class="headerlink" href="#prerequisites" title="Link to this
 <section id="corrosion-assessment-results">
 <h1>Corrosion Assessment Results<a class="headerlink" href="#corrosion-assessment-results" title="Link to this heading"></a></h1>
 <p>Executing our code along with proper input variables, it automatically outputs interpolated rebar signal amplitudes in decibel unit. Figure 3 (a), (b), and (c) shows the pinpointed rebar signals on the split GPR B-scans. Our code reads the absolute amplitude values right on the rebar signals, save as a list. Subsequently, the code concatenates the split B-scans and generates 2D scatter plots for the entire data and splits the concatenated B-scans again to plot the 2D scatter plots along the actual four GPR scan lines (Figure 3 (d) and (e)). To check how the rebar signal amplitudes vary, we also output the amplitude distribution histogram on each lane (4 GPR lines), shown in Figure 3 (f). Lastly, the code outputs the interpolated amplitude contour for each lane (Figure 3 (g)).</p>
-<a class="reference internal image-reference" href="../../_images/Figure_3.png"><img alt="figure 3" class="align-center" src="../../_images/Figure_3.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_3_tz.png"><img alt="figure 3" class="align-center" src="../../_images/Figure_3_tz.png" style="width: 1000px;" /></a>
 <p>Figure 3. CHARISMA outputs from Mississippi I-10 Region 01 rebar cover depth for the first 4 GPR scan lines. Figure 3 (a), (b), and (c) are the rebar mapping result (3 examples among 20 split B-scans), (d) and (e) show the rebar coordinates, (f) displays the rebar amplitude distribution histogram, and (g) exhibits the interpolated 2D contour map.</p>
 <p>Figure 4 shows the output of processing GPR data with CHARISMA, which is the interpolated 2D contour from the entire lanes in the bridge Zone 01. Figure 4 (a) follows the ASTM standard, stating the rebar signals below -6 or -8 dB is suspected to be under corrosive environment. Figure 4 (b) is a rainbow contour map, which is also used in LTBP InfoBridge™. We repeat this process for the other zones to gather all the rebar points on the entire bridge.</p>
-<a class="reference internal image-reference" href="../../_images/Figure_4.png"><img alt="figure 4" class="align-center" src="../../_images/Figure_4.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_4_tz.png"><img alt="figure 4" class="align-center" src="../../_images/Figure_4_tz.png" style="width: 1000px;" /></a>
 <p>Figure 4. Interpolated reinforcing reflection amplitude 2D contour from the entire lanes in the bridge Zone 01. (a) follows the ASTM standard and (b) uses rainbow contour map. The black circle shows the reference points that have the maximum amplitude among each lane.</p>
 <p>Once we have obtained the rebar points from all regions, CHARISMA generates the rebar cover depth contour map for the entire bridge. It combines all the rebar point lists from individual regions and establishes a grid space based on the XML file. For each colormap (ASTM and rainbow), There are two options available: one involves plotting without interpolating the gap among regions (Figure 5 and 6 (a)), while the other interpolates the entire bridge based on the gathered rebar points (Figure 5 and 6 (b)). Since we use the linear interpolation method, there is no available value for the edges, which is shown in grey color.</p>
-<a class="reference internal image-reference" href="../../_images/Figure_5.png"><img alt="figure 5" class="align-center" src="../../_images/Figure_5.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_5_tz.png"><img alt="figure 5" class="align-center" src="../../_images/Figure_5_tz.png" style="width: 1000px;" /></a>
 <p>Figure 5. CHARISMA output (ASTM style): 2D contour plot of reinforcing reflection amplitude on Mississippi I-10 concrete bridge without interpolating the gap among regions (a), and with interpolating the entire bridge (b).</p>
-<a class="reference internal image-reference" href="../../_images/Figure_6.png"><img alt="figure 6" class="align-center" src="../../_images/Figure_6.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_6_tz.png"><img alt="figure 6" class="align-center" src="../../_images/Figure_6_tz.png" style="width: 1000px;" /></a>
 <p>Figure 6. CHARISMA output (Rainbow colormap): 2D contour plot of reinforcing reflection amplitude on Mississippi I-10 concrete bridge without interpolating the gap among regions (a), and with interpolating the entire bridge (b).</p>
 </section>
 <section id="discussion">
@@ -154,9 +154,9 @@ <h1>Jupyter Notebook – Mississippi Bridge<a class="headerlink" href="#jupyter-
 <p>For this reason, readers are directed to <a class="reference internal" href="rebar_cover_depth_case_study.html#code-explanation-rebar-cover-depth-section"><span class="std std-ref">Code Explanation</span></a> section from the Cover Depth Measurement, as the input parameters for the code are identical. We will also compare the two applications, highlighting the differences in the code.</p>
 <section id="corrosion-assessment-details">
 <h2>Corrosion Assessment Details<a class="headerlink" href="#corrosion-assessment-details" title="Link to this heading"></a></h2>
-<p>We first process the GPR B-scans with time-zero correction, background removal, F-K migration, and contrast adjustment. In accordance with the ASTM standards, we use the migrated data without any visual modifications (as contrast adjustment can alter the amplitude and affect the decibel values) to obtain the amplitude signals on the rebars.</p>
+<p>We first process the GPR B-scans using time-zero correction, background removal, F-K migration, and contrast adjustment. Following ASTM standards, we locate the rebars using the migrated data. Then, we use these rebar locations on the time-zero corrected data without any visual modifications (since contrast adjustment can alter the amplitude and affect the decibel values) to obtain the amplitude signals on the rebars. We noticed that the rebar locations from migration sometimes do not align precisely with the exact peak of the A-scan. Thus, we correct the rebar locations using the <code class="code docutils literal notranslate"><span class="pre">Scipy</span> <span class="pre">find_peaks</span></code> function.</p>
 <p>After mapping the rebars (unitless) with the migrated data, we create a Pandas dataframe to process further, as shown in Figure 7. In the dataframe, the rebar coordinate x represents the GPR survey line, and y represents the wave travel time. Since the rebar coordinates are not integers (the data is discrete and the amplitude between two data points is unknown), we use the <code class="code docutils literal notranslate"><span class="pre">SciPy</span> <span class="pre">interp2d</span></code> function to determine the amplitude at the exact points. Then, we convert the amplitude to a logarithmic scale in decibels and subtract it from the maximum dB value.</p>
-<a class="reference internal image-reference" href="../../_images/Figure_7.png"><img alt="figure 7" class="align-center" src="../../_images/Figure_7.png" style="width: 1000px;" /></a>
+<a class="reference internal image-reference" href="../../_images/Figure_7_tz.png"><img alt="figure 7" class="align-center" src="../../_images/Figure_7_tz.png" style="width: 1000px;" /></a>
 <p>Figure 7. (a) table is an output from the <code class="code docutils literal notranslate"><span class="pre">extract_reinforcing_reflection_amplitude</span></code> function, the first 20 rows in corrosion assessment data processing and the rows with the maximum amplitude. (b) shows the rebar points (red line) on the GPR a-scans to check whether the interpolation works correctly or not.</p>
 </section>
 </section>