Optical Interferometric Force Sensor based on a Buckled Beam

This paper reports a novel extrinsic Fabry-Perot interferometer (EFPI)-based fiber optic sensor for force measurement. The prototype force sensor consists of two EFPIs mounted on a stainless-steel rectangular frame. The primary sensing element, i.e., the first EFPI, is formed between the endface of a horizontally placed optical fiber and a stainless-steel buckled beam. The second EFPI, fashioned between a longitudinally placed optical fiber and a silver-coated glass beam, is arranged to demonstrate the amplification mechanism of the buckled beam structure. When the sensor is subjected to a tension force, the pre-buckled beam will deflect backward, resulting in a longitudinal/axial displacement of the pre-buckled beam. The axial displacement is further transferred and amplified to a horizontal/vertical deflection at the middle of the buckled beam, leading to a relatively significant change in the Fabry-Perot cavity length. A force sensitivity of 796 nm/ {N} (change in cavity length/Newton) is achieved with a low-temperature dependence of 0.005 {N} /°C. The stability of the sensor is also investigated with a standard deviation of ± 5 nm, corresponding to a measurement resolution of ±0.0064 N. A simulation is conducted to study the axial displacement and stress distribution of the sensor when it is subjected to a tension load of 250 N. It is demonstrated that the maximum stress of the sensor is tremendously reduced attributed to the buckled design, enabling a long service life cycle of the force sensor. The robust and simple-to-manufacture force sensor has great potential in structural health monitoring, robotics control, and oil/ gas refining systems

Embeddable Soil Moisture Content Sensor based on Open–end Microwave Coaxial Cable Resonator

In This Paper, We Propose and Demonstrate a Novel Corrosion-Resistant, Embeddable Open-End Coaxial Cable Soil Moisture Sensor. This Microwave Resonator is Constructed using Two Reflectors Along the Coaxial Line. the First Reflector is a Metal Post at the Signal Input End, Short-Circuiting the Inner Conductor to the Outer Conductor. the Second Reflector Comprises a Welded Metal Plate Parallel to the Open-End of the Coaxial Line, Maintaining a Fixed Gap. a Moisture-Sensitive Polyvinyl Alcohol (PVA) Film is Inserted into This Gap. the Resonance Frequency of the Open-End Coaxial Cable Resonator is Highly Dependent on the Fringe Capacitance, Which Varies with Soil Moisture Levels. as Such, Tracking Resonance Frequency Changes Allows for Correlation with Soil Moisture Fluctuations. We Provide a Detailed Discussion of the Embeddable Open-End Microwave Coaxial Cable Resonator (EOE-MCCR) Mathematical Model and a Proof of Concept for Soil Moisture Measurement. the Demonstration Experiments Investigate Soil Moisture Content Ranging from 4% to 24%. the Prototype Device Exhibits a Soil Moisture Measurement Sensitivity of 0.76MHz% for Soil Moisture between 4% and 10%, and 1.44MHz% for Soil Moisture between 10% and 24%. the Soil Moisture Sensor Presented Here is Robust, Easy to Manufacture, Chemically Resistant, Low-Cost, and Suitable for Long-Term Applications and Potential Industrial Uses. This Innovative Sensor is Ideal for Sensing Applications in Harsh Environments, Advancing the Field of Chemical Trace Sensing

Characteristics Analysis and Measurement of Inverter-Fed Induction Motors for Stator and Rotor Fault Detection

Inverter-fed induction motors (IMs) contain a serious of current harmonics, which become severer under stator and rotor faults. The resultant fault components in the currents affect the monitoring of the motor status. With this background, the fault components in the electromagnetic torque under stator faults considering harmonics are derived in this paper, and the fault components in current harmonics under rotor faults are analyzed. More importantly, the monitoring based on the fault characteristics (both in the torque and current) is proposed to provide reliable stator and rotor fault diagnosis. Specifically, the fault components induced by stator faults in the electromagnetic torque are discussed in this paper, and then, fault components are characterized in the torque spectrum to identify stator faults. To achieve so, a full-order flux observer is adopted to calculate the torque. On the other hand, under rotor faults, the sidebands caused by time and space harmonics in the current are analyzed and exploited to recognize rotor faults, being the motor current signature analysis (MCSA). Experimental tests are performed on an inverter-fed 2.2 kW/380 V/50 Hz IM, which verifies the analysis and the effectiveness of the proposed fault diagnosis methods of inverter-fed IMs

Artificial Human Balance Control by Calf Muscle Activation Modelling

The natural neuromuscular model has greatly inspired the development of control mechanisms in addressing the uncertainty challenges in robotic systems. Although the underpinning neural reaction of posture control remains unknown, recent studies suggest that muscle activation driven by the nervous system plays a key role in human postural responses to environmental disturbance. Given that the human calf is mainly formed by two muscles, this paper presents an integrated calf control model with the two comprising components representing the activations of the two calf muscles. The contributions of each component towards the artificial control of the calf are determined by their weights, which are carefully designed to simulate the natural biological calf. The proposed calf modelling has also been applied to robotic ankle exoskeleton control. The proposed work was validated and evaluated by both biological and engineering simulation approaches, and the experimental results revealed that the proposed model successfully performed over 92% of the muscle activation naturally made by human participants, and the actions led by the simulated ankle exoskeleton wearers were overall consistent with that by the natural biological response

COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking

Expert finding, a popular service provided by many online websites such as Expertise Finder, LinkedIn, and AMiner, benefits seeking consultants, collaborators, and candidate qualifications. However, its quality is suffered from a single source of support information for experts. This paper employs AMiner, a free online academic search and mining system, having collected more than over 100 million researcher profiles together with 200 million papers from multiple publication databases, as the basis for investigating the problem of expert linking, which aims at linking any external information of persons to experts in AMiner. A critical challenge is how to perform zero shot expert linking without any labeled linkages from the external information to AMiner experts, as it is infeasible to acquire sufficient labels for arbitrary external sources. Inspired by the success of self supervised learning in computer vision and natural language processing, we propose to train a self supervised expert linking model, which is first pretrained by contrastive learning on AMiner data to capture the common representation and matching patterns of experts across AMiner and external sources, and is then fine-tuned by adversarial learning on AMiner and the unlabeled external sources to improve the model transferability. Experimental results demonstrate that COAD significantly outperforms various baselines without contrastive learning of experts on two widely studied downstream tasks: author identification (improving up to 32.1% in HitRatio@1) and paper clustering (improving up to 14.8% in Pairwise-F1). Expert linking on two genres of external sources also indicates the superiority of the proposed adversarial fine-tuning method compared with other domain adaptation ways (improving up to 2.3% in HitRatio@1).Comment: TKDE under revie

4-Bromo-2,6-dimethyl­anilinium bromide monohydrate

In the title compound, C8H11BrN+·Br−·H2O, a network of N—H⋯O, N—H⋯Br and O—H⋯Br hydrogen bonds helps to consolidate the crystal packing