Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
2,237
result(s) for
"soft sensor"
Sort by:
Soft-Sensor Modeling of Temperature Variation in a Room under Cooling Conditions
Non-uniform temperature distributions in air-conditioned areas can reduce the energy efficiency of air conditioners and cause uncomfortable thermal sensations for occupants. Furthermore, it is impractical to use physical sensors to measure the local temperature at every position. This study developed a soft-sensing model that integrates the fundamentals of thermodynamics and transport phenomena to predict the temperature at the target position in space. Water experiments were conducted to simulate indoor conditions in an air-conditioning cooling mode. The transient temperatures of various positions were measured for model training and validation. The velocity vectors of water flow were acquired using the particle image velocimetry method. Correlation analysis of various positions was conducted to select the input variable. The soft-sensing model was developed using the multiple linear regression method. The model for the top layer was modified by the correction of dead time. The experimental results showed the temperature inhomogeneity between different layers. The temperature at each target position under two initial temperatures and two flow rates was accurately predicted with a mean absolute error within 0.69 K. Moreover, the temperature under different flow rates can be predicted with one model. Therefore, this soft-sensing model has the potential to be integrated into air-conditioning systems.
Journal Article
Generic biomass estimation methods targeting physiologic process control in induced bacterial cultures
Advanced bioprocess development strategies focus on the control of physiological entities, which rely on accurate real‐time determination of the biomass concentration. Various methods have been proposed in literature but up to this date a comprehensive and differentiated comparison of biomass estimation approaches for early stage bioprocess development is missing. In this study, we compared hard sensor, soft‐sensor, and data‐driven approaches for real‐time biomass estimation in respect to accuracy, transferability, and costs. The outlined methods were tested with two different microbial strains and recombinant products using Escherichia coli. To investigate the applicability of the outlined methods, method performance was assessed in correspondence to metabolic activity. Based on statistical descriptors the methods were compared and discussed. The results indicate no significant impact of strain or biomass estimation approach on the measurement quality. The average relative error of 11–13% can be greatly reduced by over 85% combining the outlined methods by the means of weighted average. This approach proved to be highly robust even during highly dynamic process conditions of oscillating specific substrate uptake rates. Concluding, the combination of low cost first principle soft‐sensor approaches in combination with a hybrid soft‐sensor yields the best information‐to‐effort ratio.
Journal Article
Large-Area and Low-Cost Force/Tactile Capacitive Sensor for Soft Robotic Applications
This paper presents a novel design and development of a low-cost and multi-touch sensor based on capacitive variations. This new sensor is very flexible and easy to fabricate, making it an appropriate choice for soft robot applications. Materials (conductive ink, silicone, and control boards) used in this sensor are inexpensive and easily found in the market. The proposed sensor is made of a wafer of different layers, silicone layers with electrically conductive ink, and a pressure-sensitive conductive paper sheet. Previous approaches like e-skin can measure the contact point or pressure of conductive objects like the human body or finger, while the proposed design enables the sensor to detect the object’s contact point and the applied force without considering the material conductivity of the object. The sensor can detect five multi-touch points at the same time. A neural network architecture is used to calibrate the applied force with acceptable accuracy in the presence of noise, variation in gains, and non-linearity. The force measured in real time by a commercial precise force sensor (ATI) is mapped with the produced voltage obtained by changing the layers’ capacitance between two electrode layers. Finally, the soft robot gripper embedding the suggested tactile sensor is utilized to grasp an object with position and force feedback signals.
Journal Article
From Fully Physical to Virtual Sensing for Water Quality Assessment: A Comprehensive Review of the Relevant State-of-the-Art
Rapid urbanization, industrial development, and climate change have resulted in water pollution and in the quality deterioration of surface and groundwater at an alarming rate, deeming its quick, accurate, and inexpensive detection imperative. Despite the latest developments in sensor technologies, real-time determination of certain parameters is not easy or uneconomical. In such cases, the use of data-derived virtual sensors can be an effective alternative. In this paper, the feasibility of virtual sensing for water quality assessment is reviewed. The review focuses on the overview of key water quality parameters for a particular use case and the development of the corresponding cost estimates for their monitoring. The review further evaluates the current state-of-the-art in terms of the modeling approaches used, parameters studied, and whether the inputs were pre-processed by interrogating relevant literature published between 2001 and 2021. The review identified artificial neural networks, random forest, and multiple linear regression as dominant machine learning techniques used for developing inferential models. The survey also highlights the need for a comprehensive virtual sensing system in an internet of things environment. Thus, the review formulates the specification book for the advanced water quality assessment process (that involves a virtual sensing module) that can enable near real-time monitoring of water quality.
Journal Article
Wireless, Smart Hemostasis Device with All‐Soft Sensing System for Quantitative and Real‐Time Pressure Evaluation
The properly applied pressure between the skin and hemostasis devices is an essential parameter for preventing bleeding and postoperative complications after a transradial procedure. However, this parameter is usually controlled based on the subjective judgment of doctors, which might cause insufficient hemostatic effect or thrombosis. Here this study develops a compact and wireless sensing system for continuously monitoring the pressure applied on the radial artery and wrist skin in clinical practice. A liquid metal (LM)‐based all‐soft pressure sensor is fabricated to enable conformal attachment between the device and skin even under large deformation conditions. The linear sensitivity of 0.007 kPa−1 among the wide pressure range of 0–100 kPa is achieved and the real‐time detection data can be wirelessly transmitted to mobile clients as a reference pressure value. With these devices, detailed pressure data can be collected, analyzed, and stored for medical assistance as well as to improve surgery quality. This work develops a wireless sensing system upon a hemostasis device. The system consists of liquid metal‐based all‐soft capacitive pressure sensors, tiny reading circuits with low‐power transmission functions, and software‐based model deployment. With these devices, detailed pressure data on retracting operations can be collected, analyzed, and stored for medical assistance as well as improving surgery quality.
Journal Article
Wearable Stretch Sensors for Motion Measurement of the Wrist Joint Based on Dielectric Elastomers
Motion capture of the human body potentially holds great significance for exoskeleton robots, human-computer interaction, sports analysis, rehabilitation research, and many other areas. Dielectric elastomer sensors (DESs) are excellent candidates for wearable human motion capture systems because of their intrinsic characteristics of softness, light weight, and compliance. In this paper, DESs were applied to measure all component motions of the wrist joints. Five sensors were mounted to different positions on the wrist, and each one is for one component motion. To find the best position to mount the sensors, the distribution of the muscles is analyzed. Even so, the component motions and the deformation of the sensors are coupled; therefore, a decoupling method was developed. By the decoupling algorithm, all component motions can be measured with a precision of 5°, which meets the requirements of general motion capture systems.
Journal Article
A Hydrogel-Based Electronic Skin for Touch Detection Using Electrical Impedance Tomography
Recent advancement in wearable and robot-assisted healthcare technology gives rise to the demand for smart interfaces that allow more efficient human-machine interaction. In this paper, a hydrogel-based soft sensor for subtle touch detection is proposed. Adopting the working principle of a biomedical imaging technology known as electrical impedance tomography (EIT), the sensor produces images that display the electrical conductivity distribution of its sensitive region to enable touch detection. The sensor was made from a natural gelatin hydrogel whose electrical conductivity is considerably less than that of human skin. The low conductivity of the sensor enabled a touch-detection mechanism based on a novel short-circuiting approach, which resulted in the reconstructed images being predominantly affected by the electrical contact between the sensor and fingertips, rather than the conventionally used piezoresistive response of the sensing material. The experimental results indicated that the proposed sensor was promising for detecting subtle contacts without the necessity of exerting a noticeable force on the sensor.
Journal Article
Toward Perceptive Soft Robots: Progress and Challenges
In the past few years, soft robotics has rapidly become an emerging research topic, opening new possibilities for addressing real‐world tasks. Perception can enable robots to effectively explore the unknown world, and interact safely with humans and the environment. Among all extero‐ and proprioception modalities, the detection of mechanical cues is vital, as with living beings. A variety of soft sensing technologies are available today, but there is still a gap to effectively utilize them in soft robots for practical applications. Here, the developments in soft robots with mechanical sensing are summarized to provide a comprehensive understanding of the state of the art in this field. Promising sensing technologies for mechanically perceptive soft robots are described, categorized, and their pros and cons are discussed. Strategies for designing soft sensors and criteria to evaluate their performance are outlined from the perspective of soft robotic applications. Challenges and trends in developing multimodal sensors, stretchable conductive materials and electronic interfaces, modeling techniques, and data interpretation for soft robotic sensing are highlighted. The knowledge gap and promising solutions toward perceptive soft robots are discussed and analyzed to provide a perspective in this field. Proprioception and tactile sensing in soft robots are needed for real‐world applications. Various soft sensing technologies that hold promise for inventing sensorized soft robots are available today. However, innovations in robust and high‐performance multimodal sensors, stretchable conductors for electrodes and interconnections, fully integrated and/or wireless electronic interfaces, modeling, and data interpretation methods are highly demanded.
Journal Article