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Temperature characteristics of a piezoresistive accelerometer for high impact shock application
(2018)
This study presents the characterization of a piezoresistive accelerometer damped with silicon oil for the application in drop tests carried out at BAM. Experiments were performed with the Hopkinson Bar method in close correlation to the real-world application conditions. The results point out certain limitations regarding the temperature influence and the frequency response. Additional experiments were performed with a gas damped type of piezoresistive accelerometer, which has superior specifications, particularly for low temperatures. The results allow for a comparison.
In civil engineering, many structures are made of reinforced concrete. Most Degradation processes relevant to this material, e.g., corrosion, are related to an increased level of material moisture.
Therefore, moisture monitoring in reinforced concrete is regarded as a crucial method for structural health monitoring. In this study, passive radio frequency identification (RFID)-based sensors are embedded into the concrete. They are well suited for long-term operation over decades and are well protected against harsh environmental conditions. The energy supply and the data transfer of the humidity sensors are provided by RFID. The sensor casing materials are optimised to withstand the high alkaline environment in concrete, having pH values of more than 12. Membrane materials are also investigated to identify materials capable of enabling water vapour transport from the porous cement matrix to the embedded humidity sensor. By measuring the corresponding relative humidity with embedded passive RFID-based sensors, the cement hydration is monitored for 170 days.
Moreover, long-term moisture monitoring is performed for more than 1000 days. The Experiments show that embedded passive RFID-based sensors are highly suitable for long-term structural health monitoring in civil engineering.
Increasing traffic volume on the one hand and ageing infrastructure on the other hand have created many new challenges for maintenance and structural health monitoring of roads and bridges. In the past, many bridges and road structures have been neglected, often resulting in traffic congestion, road closure, and increased repair costs.
This research is concerned with the development of a system to improve the challenge of maintenance and early detection of damage, particularly moisture penetration and corrosion of steel reinforced concrete components. The objective is to develop a method that will also work after 30 years and longer. Many new IoT solutions are equipped with internal energy storage elements (accumulators or batteries) which are inappropriate here, since most relevant signs of concrete degradation occur after decades, where the functioning of such elements are more than questionable. The presented technology approach uses radio-frequency identification (RFID) and enables connectivity to sensors. It offers the advantage of an passive, completely independent energy supply without any energy storage components.
Since the system should be permanently embedded in concrete, it is crucial to develop a long-term stable device which is adapted to the environmental influences of the structure, e.g., long-term resistance in very alkaline environment of pH 13. In numerous experiments, the robustness of the system was tested and evaluated. Various tests with encapsulations to protect the electronics were performed, and for long-term validation different concrete specimens were instrumented with RFID-sensor-systems. Their operating time is now around two years and investigations for signs of fatigue and damage to the encapsulation and the electronics are ongoing.
Increasing traffic volume on the one hand and ageing infrastructure on the other hand have created many new challenges for maintenance and structural health monitoring of roads and bridges. In the past, many bridges and road structures have been neglected, often resulting in traffic congestion, road closure, and increased repair costs.
This research is concerned with the development of a system to improve the challenge of maintenance and early detection of damage, particularly moisture penetration and corrosion of steel reinforced concrete components. The objective is to develop a method that will also work after 30 years and longer. Many new IoT solutions are equipped with internal energy storage elements (accumulators or batteries) which are inappropriate here, since most relevant signs of concrete degradation occur after decades, where the functioning of such elements are more than questionable. The presented technology approach uses radio-frequency identification (RFID) and enables connectivity to sensors. It offers the advantage of an passive, completely independent energy supply without any energy storage components.
Since the system should be permanently embedded in concrete, it is crucial to develop a long-term stable device which is adapted to the environmental influences of the structure, e.g., long-term resistance in very alkaline environment of pH 13. In numerous experiments, the robustness of the system was tested and evaluated. Various tests with encapsulations to protect the electronics were performed, and for long-term validation different concrete specimens were instrumented with RFID-sensor-systems. Their operating time is now around two years and investigations for signs of fatigue and damage to the encapsulation and the electronics are ongoing.
Sensor network deployment
(2018)
In the present paper the development of a semi-automated device for long-term monitoring of gaseous ammonia is described. A sensor material was produced that changes its optical properties in the pres-ence of low concentrations of ammonia in air. The implementation into an electronic device enables precise, simple, economic and fast monitoring of low concentrations of harmful gases, like ammonia, and hence can help to improve the climate monitoring in livestock housing, barns or stables.
The present paper describes the development of a sensor material that changes its fluorescence in the presence of gaseous ammonia in a relevant concentration range. The implementation into a semi-automatic gas measurement device enables low-cost, precise, simple and fast monitoring of low con-centrations of harmful gases, like ammonia, and hence can help to improve the climate monitoring in livestock housing, barns or stables.
This paper describes the development of a semi-automatic gas measurement device presenting potentially a broad range of applications, noteworthy in the agricultural sector. Non-reversible fluorescent molecular sensors were designed and syn-thesized. Upon, integration into a hydrogel matrix with an optimal ratio of co-solvents, the sensors reacting selectively to ammonia were illuminated by excitation light to produce a concentration-correlated fluorescence emission. An automated mechanical-elec-trical device initiates a given gas mixture and thus simulates con-centrations similar to a threshold value. The aim of this project is to develop a sensor or a low-cost method which can monitor low concentrations of harmful gases and aid in their elimination or regulation in livestock housing, barns or stables.
Wastewater contains harmful chemicals and heavy metals that are known to cause various environmental and health problems. Therefore, the water quality control using sensitive, simple, fast, accurate, and portable tools is of great importance. This study aimed to evaluate the pollution parameters of wastewaters collected at different treatment stages from a wastewater treatment plant (WWTP) that treats domestic and industrial wastewaters by using an electronic nose (E-nose) and a voltammetric electronic tongue (E-tongue) combined with chemometric techniques. Water and wastewater pollution parameters determination were performed using inductively coupled plasma optical emission spectrometry for the determination of cations, and anions by using ion chromatography. Chemometric techniques, such as Principal Component Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to process the E-nose and E-tongue datasets to describe the similarities between the samples. In addition, Partial Least Squares Regression (PLSR) model was constructed using electronic sensing data to simultaneously predict the concentration values of physicochemical parameters. The obtained correlation coefficient, for training and testing sets, is higher than 0.91 for the prediction of the concentration of all physicochemical parameters, except for iron (Fe) which remains 0.84. These results suggest that simple, portable, and inexpensive tools such as electronic nose and tongue are suitable for wastewater analysis.
Structural Health Monitoring (SHM) has become very important in today's rapidly developing time. High buildings, large bridges and complex technical structures need to be monitored continuously and this over long periods.
Visual monitoring cannot evaluate the internal condition of building structures. Thus, material embedded sensors are needed. Cable connection of these sensors pose the disadvantage of weak spots and water intrusion. For concrete embedded sensors the use of batteries is not convenient, because of limited lifetime, difficult charging, and generation of electrical waste.. Hence, monitoring should be implemented preferentially with firmly embedded passive RFID sensor modules. However, since the concrete structure forms an electromagnetically reflective and absorbing barrier, only limited energy can be transmitted to the module. This project requires a highly energy-saving system, which can record different sensor parameters at critical points.