Fast and robust detection of solar modules in electroluminescence images

Fast, non-destructive and on-site quality control tools, mainly high sensitive imaging techniques, are important to assess the reliability of photovoltaic plants. To minimize the risk of further damages and electrical yield losses, electroluminescence (EL) imaging is used to detect local defects in an early stage, which might cause future electric losses. For an automated defect recognition on EL measurements, a robust detection and rectification of modules, as well as an optional segmentation into cells is required. This paper introduces a method to detect solar modules and crossing points between solar cells in EL images. We only require 1-D image statistics for the detection, resulting in an approach that is computationally efficient. In addition, the method is able to detect the modules under perspective distortion and in scenarios, where multiple modules are visible in the image. We compare our method to the state of the art and show that it is superior in presence of perspective distortion while the performance on images, where the module is roughly coplanar to the detector, is similar to the reference method. Finally, we show that we greatly improve in terms of computational time in comparison to the reference method

1st International round robin on EL imaging: automated camera calibration and image normalisation

Results from the first international Round Robin on electroluminescence (EL) imaging of PV devices are presented. 17 Laboratories across Europe, Asia and the US measured EL images of ten commercially available modules and five single-cell modules. This work presents a novel automated camera calibration and image scaling routine. Its performance is quantified through comparing intensity deviation of corrected images and their cell average. While manual calibration includes additional measurement of lens distortion and flat field, the automated calibration extracts camera calibration parameters (here: lens distortion, and vignetting) exclusively from EL images. Although it is shown that the presented automated calibration outperforms the manual one, the method proposed in this work uses both manual and automated calibration. 501 images from 24 cameras are corrected. Intensity deviation of cell averages of every measured device decreased from 10.3 % (results submitted by contributing labs) to 2.8 % (proposed method), For three images the image correction produced insufficient results and vignetting correction failed for one camera, known of having a non-linear camera sensor. Surprisingly, largest image quality improvements are achieved by spatially precise image alignment of the same device and not by correcting for vignetting and lens distortion. This is due to overall small lens distortion and the circumstance that, although vignetting caused intensity reduction of more than 50%, PV devices are generally positioned in the image centre in which vignetting distortion is lowest

A Modified RMCE-Compatible Rosa26 Locus for the Expression of Transgenes from Exogenous Promoters

Generation of gain-of-function transgenic mice by targeting the Rosa26 locus has been established as an alternative to classical transgenic mice produced by pronuclear microinjection. However, targeting transgenes to the endogenous Rosa26 promoter results in moderate ubiquitous expression and is not suitable for high expression levels. Therefore, we now generated a modified Rosa26 (modRosa26) locus that combines efficient targeted transgenesis using recombinase-mediated cassette exchange (RMCE) by Flipase (Flp-RMCE) or Cre recombinase (Cre-RMCE) with transgene expression from exogenous promoters. We silenced the endogenous Rosa26 promoter and characterized several ubiquitous (pCAG, EF1α and CMV) and tissue-specific (VeCad, αSMA) promoters in the modRosa26 locus in vivo. We demonstrate that the ubiquitous pCAG promoter in the modRosa26 locus now offers high transgene expression. While tissue-specific promoters were all active in their cognate tissues they additionally led to rare ectopic expression. To achieve high expression levels in a tissue-specific manner, we therefore combined Flp-RMCE for rapid ES cell targeting, the pCAG promoter for high transgene levels and Cre/LoxP conditional transgene activation using well-characterized Cre lines. Using this approach we generated a Cre/LoxP-inducible reporter mouse line with high EGFP expression levels that enables cell tracing in live cells. A second reporter line expressing luciferase permits efficient monitoring of Cre activity in live animals. Thus, targeting the modRosa26 locus by RMCE minimizes the effort required to target ES cells and generates a tool for the use exogenous promoters in combination with single-copy transgenes for predictable expression in mice

A validated quantification of triclosan in toothpaste using high-performance thin-layer chromatography and a 48-bit fatbed scanner

We present a densitometric quantification method for triclosan in toothpaste, separated by high-performance thin-layer chromatography (HPTLC) and using a 48-bit flatbed scanner as the detection system. The sample was band-wise applied to HPTLC plates (10 × 20 cm), with fluorescent dye, Merck, Germany (1.05554). The plates were developed in a vertical developing chamber with 20 min of chamber saturation over 70 mm, using n-heptane–methyl tert-butyl ether–acetic acid (92:8:0.1, V/V) as solvent. The RF value of triclosan is hRF = 22.4, and quantification is based on direct measurements using an inexpensive 48-bit flatbed scanner for color measurements (in red, green, and blue) after plate staining with 2,6-dichloroquinone-4-chloroimide (Gibbs' reagent). Evaluation of the red channel makes the measurements of triclosan very specific. For linearization, an extended Kubelka–Munk expression was used for data transformation. The range of linearity covers more than two orders of magnitude and is between 91 and 1000 ng. The separation method is inexpensive, fast and reliable

Macht, Charisma und Ästhetik - oder: Caligula, Heliogabal und die allegorisch-instrumentelle Wiederentdeckung der Antike in der modernen Literatur: George, Couperus, Grünbein

Voß T. Macht, Charisma und Ästhetik - oder: Caligula, Heliogabal und die allegorisch-instrumentelle Wiederentdeckung der Antike in der modernen Literatur: George, Couperus, Grünbein. In: Doll B, Oliver K, eds. Zwei Körper der Nation. Ästhetische Figurationen des Politischen. München: Wilhelm Fink Verlag; In Press: 451-483

An improved Patulin determination in apple juice using HPTLC in combination with a DAD-scanner, a 16-bit camera and a 48-bit flatbed scanner

We present a video-densitometric high-performance thin-layer chromatography (HPTLC) quantification method for patulin in apple juice, developed in a vertical chamber from the starting point to a distance of 50 mm, using MTBE, n-pentane (9 + 5, v/v) as mobile phase. After separation the plate is sprayed with methyl-benzothiazolinone hydrazone hydrochloride monohydrate (MBTH) solution (40 mg in 20 mL methanol) and heated at 105 °C for 15 min. Patulin zones are transformed into yellow spots. The quantification is based on direct measurements using an inexpensive 48-bit flatbed scanner for color measurements (in red, green, and blue). Evaluation of the blue channel makes the measurements very specific. Quantification in fluorescence was also done by use of a 16-bit CCD-camera and UV-366 nm illumination as well as using a HPTLC DAD-scanner. For linearization the extended Kubelka–Munk expression for data transformation was used. The range of linearity covers more than two magnitudes and lies between 5 and 800 ng patulin. The extraction of 20 g apple juice and an extract application on plate up to 50 µL allows statistically defined checking the limit of detection (LOD) of 50 ng patulin per track, which is equivalent to 50 µg patulin per kg apple juice

Verfahren und System zur Bewertung von Solarzellen

Die vorliegende Erfindung betrifft ein Verfahren für eine Bewertung der Qualität von Solarzellen einer Fotovoltaikanlage. Die Erfindung betrifft auch ein System zur Bewertung von Solarzellen. Fotovoltaikanlagen umfassen in der Regel eine Vielzahl von Solarmodulen. Ein Solarmodul ist eine bauliche Einheit, die eine Vielzahl von Solarzellen umfasst. Um hinreichend hohe elektrische Spannungen erzeugen zu können, sind Solarzellen eines Solarmoduls elektrisch seriell miteinander verbunden

Using Deep Learning to Predict PV Module IV Curves From Electroluminescence Images

The performance of a PV string can be assessed by extracting quantitative information from the electroluminescence images of each of the PV modules included in the string. In this work, we propose a method to predict PV module IV curves from electroluminescence (EL) images using a deep learning algorithm. The proposed method consists of creating eleven deep learning models that predict ten points on the IV curve, including ISC, Impp, Vmpp and VOC. We use 376 samples (EL images and corresponding IV curves) for training the deep learning models, 114 samples for validating the models, and 92 samples for testing the models, whereas 84 samples were measured in the lab and 8 samples were measured in the field. The dominant fault present in the PV modules used in this work is cell cracks resulting in disconnected areas. Results show that the PV module IV curves are predicted with a mean absolute error for all points below 5 W. This indicates that the deep learning models are able to find a relationship between the inactive areas present in the PV module EL image and the respective PV module IV curve. The module power that were used in this research experiment range from 210 W to 120 W. To compare field measurements to deep learning predictions, we corrected Pmpp predictions to values at Standard Testing Conditions, and at the same conditions we measured modules with the flasher. The results from the field experiment showed that the Pmpp prediction error of the high power modules in relation to the ground truth Pmpp values was less than 7 % or 16 W. While the low power modules with a high number of inactive cell areas presented a Pmpp prediction error of 15 % or 20 W