Analytische Chemie
Filtern
Dokumenttyp
- Posterpräsentation (53) (entfernen)
Referierte Publikation
- nein (53)
Schlagworte
- Mobile Robot Olfaction (9)
- Nano aerial robot (5)
- Gas sensing (4)
- Swarm (4)
- TDLAS (4)
- Gas tomography (3)
- Low-cost (3)
- Tomographic reconstruction of gas plumes (3)
- Tunable Diode Laser Absorption Spectroscopy (TDLAS) (3)
- UAV (3)
Organisationseinheit der BAM
- 8.1 Sensorik, mess- und prüftechnische Verfahren (53) (entfernen)
Communities worldwide face significant threats from Explosive Remnants of War (ERW), which endanger lives and restrict land usage. From forest fires due to ERWs or in ERW-contaminated areas (e.g., in Jüterbog, Germany) to broader global challenges (e.g., the Ukrainian conflict), the need for efficient detection and removal of these remnants, especially for humanitarian demining, is paramount. Traditional methods, like manual demining, have severe limitations in safety and efficiency. Here, we introduce an innovative solution to these challenges: “Chemosensing Smart Dust.” This technology uses chemoselective dyes that change their fluorescence properties when exposed to explosives like 2,4,6-trinitrotoluene (TNT). Fluorescence-based detection offers superior sensitivity, reduced likelihood of false positives, and enhanced accuracy of explosive detection. Drones, equipped with excitation lasers or LEDs, deploy the Chemosensing Smart Dust over areas of interest and actively detect the fluorescence changes using high-resolution cameras, offering a rapid, safe, and adaptable detection method. Beyond demining, this innovative approach has potential applications in monitoring polluted areas, homeland security, and emergency response.
The transfer of data for the metrological traceability of measurement results is currently taking place in the form of paper-based calibration certificates, mostly. Especially accredited metrology services providers are often bound to paper certificates by regulatory constrictions and sometimes lack of IT-infrastructure. This analog form of metrology data transfer, however, implies hands-on work, in particular for the certificate receiver, as its key values need to be translated into the device- and quality management (QM) system, manually. With thousands of certificates transferred from accredited calibration labs until the industrial regime, this binds a significant amount of human resources and is a well-known source of errors, thus constricting cost-effective and secure workflows.
This contribution highlights the status of the advancing digital transformation in metrology, on the example of force calibration. Although this appealing initiative is to a large extend driven by German stakeholders, it currently evolves to extend across all Europe and far beyond.
Robotic Measurement System Concept for Greenhouse Gas Tomography in Wastewater Treatment Plants
(2023)
This paper introduces a conceptual framework for a greenhouse gas (GHG) measurement system designed for wastewater treatment plants (WWTPs). The emphasis is on accurate gas tomography measurements of emissions, crucial for national emission assessments. The proposed system is movable, semi-autonomous, and employs a combination of ground and air robots equipped with integral remote gas sensors and in-situ sensors. The proposed two/two configuration ensures comprehensive coverage of WWTPs, overcoming obstacles. The system concept lays the foundation for future implementation and evaluation, addressing the need for enhanced understanding of GHG emissions from WWTPs.
This poster reports an improved outdoor gas source localization algorithm, showing promising results under simulations with a realistic gas plume. In the scenario assumed in this work, an unmanned ground vehicle searches for the location of a gas source in an open outdoor field. The simulated gas plume in this work consists of frequent and large meandering as a real outdoor plume. The source location is estimated using gas and wind measurements obtained from sensors fixed on a mobile platform. When a gas puff is detected, its source is likely to be in the upwind direction. Particle filter-based algorithms have been proposed in previous work to estimate the most likely source location from multiple gas detection events. In this work, the particle weight update function has been modified by adopting a 2D Gaussian plume model, to improve the accuracy in estimating the likelihood of the source location. We have evaluated the performance of this algorithm combined with an estimation-based route planning algorithm. The simulator uses wind data recorded outdoors to calculate transport of gas puffs allowing a formation of a gas plume containing large meandering, due to real fluctuations of outdoor wind. Simulations of the improved particle filter with the estimation-based route planning algorithm have yielded more accurate, stable and time-efficient results than the pre-modified version.
Monitoring and maintenance of civil infrastructure are of great importance, as any undetected damage can cause high repair costs, unintended deadtime, or endanger structural integrity. The inspection of large concrete structures such as bridges and parking lots is particularly challenging and time-consuming. Traditional methods are mostly manual and involve mapping a grid of measurement lines to record the position of each measurement. Current semi-automated methods, on the other hand, use GPS or tachymeters for localization but still require trained personnel to operate. An entirely automated approach using mobile robots would be more cost- and time-efficient. While there have been developments in using GPS-enabled mobile robots for bridge inspection, the weak signal strength in indoor areas poses a challenge for the automated inspection of structures such as parking lots. This paper aims to develop a solution for the automated inspection of large indoor concrete structures by addressing the problem of robot localization in indoor spaces and the automated measurement of concrete cover and rebar detection.
Occupational health is an important topic, especially in industry, where workers are exposed to airborne by-products (e.g., dust particles and gases). Therefore, continuous monitoring of the air quality in industrial environments is crucial to meet safety standards. For practical and economic reasons, high-quality, costly measurements are currently only carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only.
The project “Robot-assisted Environmental Monitoring for Air Quality Assessment in Industrial Scenarios” (RASEM) addresses this issue by bringing together the benefits of both – low- and high-cost – measuring technologies enabling cost-efficient long-term air quality monitoring in realtime: A stationary network of low-cost sensors that is augmented by mobile units carrying high-quality sensors. By mapping the distribution of gases and particles in industrial environments with the proposed RASEM system, measures can be identified to improve on-site working conditions much faster than using traditional methods.
In this presentation, we detail the technical aspects of RASEM and introduce the mobile platforms used.
Die Magnetpulverprüfung ist eine weit verbreitete Prüfmethode für ferromagnetische Bauteile. Hierbei werden Oberflächenfehler wie Risse mit ferromagnetischem Pulver sichtbar gemacht, wodurch eine qualitative Bewertung des Bauteils ermöglicht wird. Allerdings können die Anzeigen kaum zu einer quantitativen Bewertung herangezogen werden. Hierfür sind Magnetfeldsensoren nötig, die die Stärke der Streufelder messen, wodurch z. B. die Tiefe der Risse abgeschätzt werden kann. Bei kommerziellen Magnetfeldsensoren sind die sensitiven Elemente auf Platinen angebracht bzw. in eine Verkapselung integriert. Hierdurch erhöht sich der Abstand der Elemente zur Oberfläche und kleine Fehler können unter Umständen nicht mehr detektiert werden. Auch wird eine automatisierte Prüfung komplexer Geometrien durch die starren Sonden erschwert.
Um Streufelder von kleinen Fehlern in komplexen Bauteilen quantitativ bewerten zu können, validiert die BAM den Einsatz neuartiger, flexibler Magnetfeldsensoren. Hierbei sind die sensitiven Elemente auf flexiblen Folien aufgebracht und lassen sich verformen, wodurch sie auf viele mögliche Oberflächenformen appliziert werden können. Es wird ein geringerer Abstand der Elemente zur Oberfläche erreicht und Streufelder von kleinen Defekten können besser aufgelöst werden. Zudem verlieren die Sensoren durch Verformung weder ihre Sensitivität noch werden sie hierdurch zerstört. Dies macht diese Sensoren zu perfekten Kandidaten für die quantitative Bewertung von Rissstreufeldern in komplex geformten, ferromagnetischen Bauteilen.
Der Beitrag präsentiert die Charakterisierung der Sensoren sowie erste Versuche an komplexen Bauteilen. Schließlich wird eine Einschätzung hinsichtlich weiterer Anwendungsmöglichkeiten gegeben.
In order to detect small and hidden material defects or micro-cracks, weak and localized magnetic stray fields need to be detected and characterized on the magnetic surface. Current flux leakage sensor elements are rigid and rely on air gaps to detect stray fields several hundred micrometers above the surface. Furthermore, the increasing complexity of critical components, enabled by novel fabrication technologies, primarily additive manufacturing, poses a significant challenge to the available flux leakage testing technologies.
The emergence of flexible magneto-electronics paves the way to a compliant form of magnetic sensors that, on one hand, are able to adapt to highly curved surfaces, allowing these measurements to be conducted on irregularly formed components, which are inaccessible for nowadays electromagnetic NDT equipment and, on the other hand, could enhance the detection limit for small magnetic stray fields, by allowing the magneto-sensitive elements to approximate the object’s surface until only a few µm, mediated by thin and flexible packaging.
In many cases, science falls back on self-developed prototype systems, which are used and developed for the measurement and execution of the tasks. About 80 % of the development is based on the same hardware design, which is used in only one application scenario and then discarded. For the most part, there are also uncalibrated sensors, since it is costly to calibrate a complicated sensor measurement system or the entire measurement chain since access to the sensor systems is not always available. This paper describes a conceptual design to implement a versatile sensor system with the motivation to fuse the data recording and data reception, which can cover large areas with the help of LoRaWAN (Long Range Wide Area Network) technology [1, 2]. To overcome disadvantages of LoRaWAN, namely the slow data rates, the proposed sensor system can also cover smaller areas with the widespread WiFi technology. An enormous advantage over individual complete systems in the form of a prototype, is the rapid expansion, uncomplicated calibration of the individual sensors and the ecological relief.
A modular design is used, where individual stacks with sensors and peripherals can be added separately. The stacks are standalone low-power systems and can be calibrated, maintained, and replaced separately and do not require the entire measurement chain. The measured and sent values are stored locally on the main stack and sent to the data collector (gateway) and evaluated by means of the automated selection between WiFi and LoRaWAN.