String Sensors Research Articles

Soft modularized robotic arm for safe human–robot interaction based on visual and proprioceptive feedback

This study proposes a modularized soft robotic arm with integrated sensing of human touches for physical human–robot interactions. The proposed robotic arm is constructed by connecting multiple soft manipulator modules, each of which consists of three bellow-type soft actuators, pneumatic valves, and an on-board sensing and control circuit. By employing stereolithography three-dimensional (3D) printing technique, the bellow actuator is capable of incorporating embedded organogel channels in the thin wall of its body that are used for detecting human touches. The organogel thus serves as a soft interface for recognizing the intentions of the human operators, enabling the robot to interact with them while generating desired motions of the manipulator. In addition to the touch sensors, each manipulator module has compact, soft string sensors for detecting the displacements of the bellow actuators. When combined with an inertial measurement unit (IMU), the manipulator module has a capability of estimating its own pose or orientation internally. We also propose a localization method that allows us to estimate the location of the manipulator module and to acquire the 3D information of the target point in an uncontrolled environment. The proposed method uses only a single depth camera combined with a deep learning model and is thus much simpler than those of conventional motion capture systems that usually require multiple cameras in a controlled environment. Using the feedback information from the internal sensors and camera, we implemented closed-loop control algorithms to carry out tasks of reaching and grasping objects. The manipulator module shows structural robustness and the performance reliability over 5,000 cycles of repeated actuation. It shows a steady-state error and a standard deviation of 0.8 mm and 0.3 mm, respectively, using the proposed localization method and the string sensor data. We demonstrate an application example of human–robot interaction that uses human touches as triggers to pick up and manipulate target objects. The proposed soft robotic arm can be easily installed in a variety of human workspaces, since it has the ability to interact safely with humans, eliminating the need for strict control of the environments for visual perception. We believe that the proposed system has the potential to integrate soft robots into our daily lives.

Simulating self-powered neutron detector responses to infer burnup-induced power distribution perturbations in next-generation light water reactors

Understanding how 3D power distribution will be monitored throughout reactor core volumetric space in next-generation nuclear power reactors is crucial to the design, deployment, and licensing of these reactors. Although numerous techniques exist for 3D power distribution monitoring based on the response of both in situ and ex situ sensors currently implemented or proposed for use in the US reactor fleet, crucial details about these techniques are often unclear. The publicly available documentation does not include information such as how well these techniques are characterized and optimized in their implementations and the levels of uncertainty in the inferred 3D power distribution. The work described herein investigated a recently developed 3D power distribution inferencing method as applied to two next-generation reactor simulations: (1) the NuScale small modular reactor design and (2) the Westinghouse AP1000 design, both of which contain in-core strings of vanadium self-powered neutron detectors (SPNDs). This investigation considered a range of SPND string sensor densities, as well as a range of 3D power distribution axial segment sizes. SPND response simulation is informed by neutron flux calculations in representative homogenized cores. For the different sensor densities and power distribution axial segment sizes in these simulations, the average solution error, solver iterations, and run time were tracked to parameterize the sensor-core configuration.

Dietary discrimination using a dual-choice self-feeding system in seabream (Sparus aurata)

Self-feeding systems have been extensively used to study animal behaviour and food preferences in vertebrates. In this study, we used a dual-choice self-feeding system to explore feeding behaviour and dietary discrimination based on organoleptic cues. Experimental tanks were provided with 2 self-feeders activated by string sensors and connected to a computer system. In the first experiment (E1) [6 tanks, 10 animals/tank, body weight (BW) 266 g ± 19.4 g], both feeders delivered the same control standard diet to evaluate the potential preference for one feeder. E1 had 3 phases: 1st, animals were allowed to demand from both feeders; 2nd, from only one feeder and 3rd from both feeders again. The second experiment (E2) (11 tanks, 15 animals/tank, BW range 25–50 g) examined whether seabream can discriminate between 3 isoenergetic diets: the control diet; a positive/palatable diet containing high levels of fish, squid and krill meal; and a negative diet in which 1.5% quinine hydrochloride was added to the control diet. E2 had 3 phases: 1st acclimation with control diet; 2nd dual-choice; 3rd dual-choice with reversal of feeders. The third experiment (E3) (8 tanks, 10 animals/tank, BW range 25-50 g) was performed using a single self-feeder per tank, with each tank being fed either control or quinine diet, to corroborate the aversive response to quinine in the absence of dietary choice. E1 demonstrated that animals demanded significantly less when only one feeder/sensor was available. E2 shows that seabream can easily discriminate a bitter compound (quinine) in the diet, showing negative preference (P < 0.05) in both phases, 2nd and 3rd. When no choice was available (E3), seabream equally demanded control or quinine diet, presumably driven by its energy requirements. However, the presence of the bitter substance increased feed refusals, 14.3% rejection of demanded feed in quinine diet, versus 2.6% in control diet, indicating a role of sensory systems in assessing food quality. A positive conditioning with a palatable diet was not effective and no positive choices were measured over a basal diet, although results were possibly influenced by the previous familiarization with the basal diet and by the experimental conditions (fast growing juveniles at high temperature). This poor dietary selection during active feeding periods could partly explain the easy adaptation of this species to substitution diets. Finally, results suggest that food intake is conditioned by agonistic behaviour in an age-dependent manner. The information will be useful for diet and feeding strategy design in seabream.

Quadratic Support Vector Machine and K-Nearest Neighbor Based Robust Sensor Fault Detection and Isolation

Fault detection plays a serious role in high-cost and safety-critical processes. There are two main drivers for continuous improvement in the area of early detection of process faults safety and reliability of technical plants. Detect fault in Geophone string sensors (SG-10) are very important in oil exploration to avoid loss economy. Methods are developed to enable earlier detection of process faults than the traditional limit and trend checking based on a single process variable and the development of these methods is a key matter. Classification methods will be used for pattern recognition and as such is appropriate for fault detection. In supervised training input-output pairs, both for normal and fault conditions, are presented to the network. The models were trained on the free fault and fault sensors. Then the Quadratic Support Vector Machine (QSVM) and k-Nearest Neighbor (KNN) as the classifiers are used. The test results for measuring the performance of 1232 sample classifiers from data show that the accuracy of fault-free sensor recognition is 97.4 % and 100% consecutively for these classifiers.

WITHDRAWN: Robust geophone string sensors fault detection and isolation using pattern recognition techniques based on Raspberry Pi4

Abstract In the early detection of process faults, safety and the reliability of technical plants are two key drivers for continuous improvement. Detecting faults in Geophone string sensors (SG-10) is necessary in oil exploration to prevent economic losses. Methods are being developed to allow for earlier detection of process faults than conventional limit and trend checking based on a single process variable, and the development of these methods is a key issue. This paper analyses and compares the efficiency of pattern recognition techniques using a low-computational power device for drift fault detection in sensors, such as the Raspberry Pi 4. Support Vector Machine (SVM), Artificial Neural Networks (ANNs) and K-Nearest Neighbor (KNN) classifiers are among the pattern recognition algorithms being studied. The data for this study were from (SG-10). The four features (resistance, noise, leakage and tilt) were extracted from normal and faulty sensors in training data and testing data. Trained models have been offline tested, using models for sensor performance to detect drift faults. Specificity, sensitivity, and accuracy were used to compare algorithm efficiency, with 98% accuracy in the KNN, 98.3% accuracy in the ANN and 62% accuracy in the SVM. The results show that from the given classifiers the (ANN) and (KNN) outperform to the (SVM).

A Simple Low-Cost Wearable Sensor for Long-Term Ambulatory Monitoring of Knee Joint Kinematics.

Accurate monitoring of joint kinematics in individuals with neuromuscular and musculoskeletal disorders within ambulatory settings could provide important information about changes in disease status and the effectiveness of rehabilitation programs and/or pharmacological treatments. This paper introduces a reliable, power efficient, and low-cost wearable system designed for the long-term monitoring of joint kinematics in ambulatory settings. Seventeen healthy subjects wore a retractable string sensor, fixed to two anchor points on the opposing segments of the knee joint, while walking at three different self-selected speeds. Joint angles were estimated from calibrated sensor values and their derivatives in a leave-one-subject-out cross validation manner using a random forest algorithm. The proposed system estimated knee flexion/extension angles with a root mean square error (RMSE) of 5.0°±1.0° across the study subjects upon removal of a single outlier subject. The outlier was likely a result of sensor miscalibration. The proposed wearable device can accurately estimate knee flexion/extension angles during locomotion at various walking speeds. We believe that our novel wearable technology has great potential to enable joint kinematic monitoring in ambulatory settings and thus provide clinicians with an opportunity to closely monitor joint recovery, develop optimal, personalized rehabilitation programs, and ultimately maximize therapeutic outcomes.

Measuring control of construction materials parameters in order to increase reliability of engineering objects

The use of string and string elements find widespread practical application in technology. In the field of measuring technology, there are many devices in which the sensitive elements are elements in the form of strings: strain gauges, accelerometers, crack meters, etc. String sensors are widely used due to its simplicity and low cost. The present paper demonstrates that preliminary studies of structural materials for the parameters of structural materials caused by a group of factors, such as surface properties, chemical composition, processing technology, can be achieved using modern methods of scanning probe, confocal, electron raster microscopy, spectroscopy, and x-ray.

Effect of changing of the parameters of the cable network of monitoring systems of high-rise buildings on the basis of string converters on their operability

The article is devoted to the problem of improving the reliability of monitoring systems for the technical conditions of high-rise buildings. The improvement is based on string sensors with an impulsed excitation method ensuring the maximum signal-to-noise ratio at their output. The influence of the parameters of the monitoring system on the shape of the excitation impulses of the string, and, consequently, on the amplitude of the string vibration of the string converter is also considered in the article. It has been experimentally proved that the parameters of the excitation impulses of the string converters. The article presents the results of the experiments showing the effect of the fronts duration of the excitation impulses on the amplitude of the oscillations of the strings. The influence of the fronts duration of the excitation impulse with the frontal lengths up to 0.5 ms is studied at the excitation impulse duration not exceeding 0.5 times the duration of natural oscillation periods of the string. The experimental data are compared with the theoretical ones and hypotheses explaining their difference are advanced. The article suggests some methods of reducing the influence of the cable-switching equipment system parameters on the amplitude of string oscillations. The possibilities of improving the reliability of the systems developed on the basis of string sensors with an impulsed excitation method and used for monitoring the technical conditions of the high-rise buildings are proposed.

A Simple and Facile Glucose Biosensor Based on Prussian Blue Modified Graphite String

This work describes the string sensor for the simple and sensitive detection of glucose which is based on Prussian blue (PB) modified graphite utilizing dipping. First, PB modified graphite (PB-G) strings are characterized by physical and electrochemical techniques to optimize the PB-G layer thickness. Then, glucose oxidase (GOx) is immobilized on PB-G string electrode with biocompatible chitosan overlayer (Chi/GOx/PB-G). The Chi/GOx/PB-G string electrode exhibits a sensitivity of 641.3 μA·mM−1·cm−2to glucose with a linear range of 0.03 to 1.0 mM (R2=0.9957) and a rapid response time (&lt;3 s). Moreover, the Chi/GOx/PB-G string electrodes are less sensitive to common interference materials such as ascorbic acid, uric acid, galactose, and acetaminophen than to glucose. The Chi/GOx/PB-G string electrodes also show excellent reproducibility (&lt;5% RSD). Therefore, our Chi/GOx/PB-G string electrodes can be simple, robust, and reliable tools for glucose sensing which can avoid complicated and difficult multistep fabrication processes. In addition, we expect that they have many potential applications in fields ranging from health care to food analysis, in particular where single use is favorable.

Mass and force sensing of an adsorbate on a string resonator

The shift of resonant frequency is the sensing mechanism for a mechanical resonator. The adsorbate mass, position and induced force are the three dominant things responsible for the resonant frequency shifts of a string resonator. In the application of a resonator sensor, the (shifts of) resonant frequencies are the measured quantities and therefore, an inverse problem arises naturally: How to determine the adsorbate mass, position and induced force by the resonant frequencies? An inverse problem solving method on the string resonator with one adsorbate is presented and its accuracy is demonstrated. How the method can be used in a real string sensor application scenario is also discussed.

Pose measurement for fighter empennage based on string sensors

A follow-up control system is designed to fulfil the fatigue test experiment of fighter empennage. To measure the distortion of empennage, a cost-effective simple rapid measurement method is put forward to permit precise pose measurement on the basis of string sensors. Two sets of string sensor measurement systems are mounted on the base and the vibration table, respectively. The joint coordinates of the measure system composed of six string sensors are determined by a coordinate measurement machine (CMM). Using the forward kinematics, inverse kinematics of Stewart table and quaternion, the string sensor measurement system gets the pose of empennage after the high-frequency component arising from vibration table is filtered by a low-pass filter. Compared with the computation data obtained from CMM, it is demonstrated that the measurement method on pose measurement by string sensor is valid and convenient. All two string sensor measurement systems can run effectively in the fatigue test experiment of fighter empennage.

Daily feeding rhythms of Senegalese sole under laboratory and farming conditions using self-feeding systems

Although Senegalese sole is traditionally regarded as a night active fish, their daily feeding rhythm remains unknown. We therefore explored their ability to use self-feeders and their daily feeding rhythm under both indoors conditions and under farming outdoor conditions. First, the most suitable sensor for this benthic species was assessed under controlled conditions. The Senegalese sole were able to operate three different sensors: rod, string or optical. The most efficient was the string sensor, since this led to the lowest amount of food waste and the highest food demand levels, which occurred mostly (over 81%) at night. Consequently, the same sensor was tested in farming conditions using Senegalese sole reared in 5.6 m diameter circular tanks. These fish quickly learned to operate the self-feeders, reaching a stable feeding-demand level from the first day. When the food reward level (X) was modified (X/2, 2X), the fish displayed an accurate compensatory feeding behavior, increasing two-fold their feeding activity when the reward level was reduced to half or decreasing their demands by 50% when the reward level was doubled. Under farming conditions, food demands were mainly nocturnal (81%) and the uneaten feed was undetectable. In summary, Senegalese sole revealed their ability to use self-feeders and displayed a pronounced nocturnal feeding behavior regardless the experimental conditions, which should be taken into consideration when designing feeding strategies for this species.

Self-feeding of European sea bass ( Dicentrarchus labrax, L.) under laboratory and farming conditions using a string sensor

In the present paper, we describe the performance of a bite-and-pull feed-demand system adapted to the behavior of European sea bass. The system is activated by the fish biting and pulling on, which generates an electrical signal that triggers the feed distributor. Experiment I was designed to test the sensor under laboratory conditions, using four groups of four naive fish per sensor (non-trained fish, NTF) and eight groups of four fish per sensor (small groups) that had been trained to use the system 1 year earlier (TF). Experiment II compared the bite-and-pull trigger (BPT) with a screened hanging-rod trigger (ST) using 16 groups of 48 sea bass per sensor (medium groups) under laboratory conditions. Experiment III evaluated the performance of the BPT sensor under farming conditions using four groups of 1000 sea bass per sensor (large groups) held in sea cages. Some of the advantages of the BPT sensor over other sensors are: (1) a shorter learning period, 11–12 days in exp. I, 1–2 day in exp. II and 1 day in exp. III; (2) absence of temporal constraints, allowing sea bass to feed at night (60% of nocturnal demands in exp. II; 23% and 47% of nocturnal demands in September and February, respectively, exp. III); (3) prevents accidental activation by fish, wind or waves; (4) low feed waste when reward level is set correctly; and (5) low costs, durability, and easy replacement of its components. All these features make the BPT a useful system for sea bass self feeding in sea cages.