Gating Artificial Neural Network Based Soft Sensor

This work proposes a novel approach to Soft Sensor modelling, where the Soft Sensor is built by a set of experts which are artificial neural networks with randomly generated topology. For each of the experts a meta neural network is trained, the gating Artificial Neural Network. The role of the gating network is to learn the performance of the experts in dependency on the input data samples. The final prediction of the Soft Sensor is a weighted sum of the individual experts predictions. The proposed meta-learning method is evaluated on two different process industry data sets

Data-driven Soft Sensors in the Process Industry

In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control. This paper discusses characteristics of the process industry data which are critical for the development of data-driven Soft Sensors. These characteristics are common to a large number of process industry fields, like the chemical industry, bioprocess industry, steel industry, etc. The focus of this work is put on the data-driven Soft Sensors because of their growing popularity, already demonstrated usefulness and huge, though yet not completely realised, potential. A comprehensive selection of case studies covering the three most important Soft Sensor application fields, a general introduction to the most popular Soft Sensor modelling techniques as well as a discussion of some open issues in the Soft Sensor development and maintenance and their possible solutions are the main contributions of this work

A bistable soft gripper with mechanically embedded sensing and actuation for fast closed-loop grasping

Soft robotic grippers are shown to be high effective for grasping unstructured objects with simple sensing and control strategies. However, they are still limited by their speed, sensing capabilities and actuation mechanism. Hence, their usage have been restricted in highly dynamic grasping tasks. This paper presents a soft robotic gripper with tunable bistable properties for sensor-less dynamic grasping. The bistable mechanism allows us to store arbitrarily large strain energy in the soft system which is then released upon contact. The mechanism also provides flexibility on the type of actuation mechanism as the grasping and sensing phase is completely passive. Theoretical background behind the mechanism is presented with finite element analysis to provide insights into design parameters. Finally, we experimentally demonstrate sensor-less dynamic grasping of an unknown object within 0.02 seconds, including the time to sense and actuate

A Feasibility Study in Measuring Soft Tissue Artifacts on the Upper Leg Using Inertial and Magnetic Sensors

Soft-tissue artifacts cause inaccurate estimates of body segment orientations. The inertial sensor (or optical marker) is orientating (or displacing) with respect to the bone it has to measure, due to muscle and skin movement [1]. In this pilot study 11 inertial and magnetic sensors (MTw, Xsens Technologies) were placed on the rectus femoris, vastus medialis and vastus lateralis (upper leg). One sensor was positioned on the tendon plate behind the quadriceps (iliotibial tract, as used in Xsens MVN [1]) and used as reference sensor. Walking, active and passive knee extensions and muscle contractions without flexion/extension were recorded using one subject. The orientation of each sensor with respect to the reference sensor was calculated. During walking, relative orientations of up to 28.6º were measured (22.4±3.6º). During muscle contractions without flexion/extension the largest relative orientations were measured on the rectus femoris (up to 11.1º) [2]. This pilot showed that the ambulatory measurement of deformation of the upper leg is feasible; however, improving the measurement technology is required. We therefore have designed a new inertial and magnetic sensor system containing smaller sensors, based on the design of an instrumented glove for the assessment of hand kinematics [3]. This new sensor system will then be used to investigate soft-tissue artifacts more accurately; in particular we will focus on in-use estimation and elimination of these artifacts

MODLEACH: A Variant of LEACH for WSNs

Wireless sensor networks are appearing as an emerging need for mankind. Though, Such networks are still in research phase however, they have high potential to be applied in almost every field of life. Lots of research is done and a lot more is awaiting to be standardized. In this work, cluster based routing in wireless sensor networks is studied precisely. Further, we modify one of the most prominent wireless sensor network's routing protocol "LEACH" as modified LEACH (MODLEACH) by introducing \emph{efficient cluster head replacement scheme} and \emph{dual transmitting power levels}. Our modified LEACH, in comparison with LEACH out performs it using metrics of cluster head formation, through put and network life. Afterwards, hard and soft thresholds are implemented on modified LEACH (MODLEACH) that boast the performance even more. Finally a brief performance analysis of LEACH, Modified LEACH (MODLEACH), MODLEACH with hard threshold (MODLEACHHT) and MODLEACH with soft threshold (MODLEACHST) is undertaken considering metrics of throughput, network life and cluster head replacements.Comment: IEEE 8th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA'13), Compiegne, Franc

Eddy current based, contactless position transducer for a gas handle

In electric vehicles, it is normal to have an electronic set value for 'gas' and for 'brake'. Traditional potentiometers with sliding contacts are not reliable. Magnetoresistive sensors or hall effect sensors need a magnet on the moving part. The proposed sensor just needs iron on the moving part. It uses an oscillator circuit where the absorbed current is an indication of damping, so how close the iron is to the sensor. The component cost is low and the output has a soft gradual change with the displacement