• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.103-109
• /
• 2001

Soft sensor is an effective method to deal with the estimation of variables, which are difficult to measure because of the reasons of economy or technology. Fuzzy logic system can be used to develop the soft sensor model by infinite rules, but the fuzzy dividing of variable sets is a key problem to achieve an accurate fuzzy logic model, In this paper, we proposed a new method to develop soft sensor model based on fuzzy neural network. First, using a novel method to divide the variable fuzzy sets by the process input and output data. Second, developing the fuzzy logic model based on that fuzzy set dividing. After that, expressing the fuzzy system with a fuzzy neural network and getting the initial soft sensor model based FNN. Last, adjusting the relative parameters of soft sensor model by the BP learning method. The effectiveness of the method proposed and the preferable generalization ability of soft sensor model built are demonstrated by the simulation.

• The Journal of Korea Robotics Society
• /
• v.16 no.1
• /
• pp.1-11
• /
• 2021

Soft robotics has attracted a huge amount of interest in the recent decade or so, be it either actuators or sensors. Recently, a soft optical waveguide sensor has proven its effectiveness for various sensing applications such as strain, force, and bending measurements. The operation principle of the waveguide is simple, but the present technology is far too much complex to manufacture the waveguide. The waveguide fails to attract various practical applications in comparison to other types of sensors despite its superior safety and ease working principle. This study pursues to develop the soft sensors based on the optical phenomena so that the waveguide can be easily manufactured and its design can be conducted. Several physical properties of the waveguide are confirmed through the repetitive experiments in the aspects of strain, force, and bending of the waveguide. Finally, the waveguide sensor is embedded inside the actuator to verify the effectiveness of the proposed waveguide as well as to extend the application fields of the waveguide sensor.

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.131-138
• /
• 2022

Soft sensors are used to anticipate complicated model parameters using data from classifiers that are comparatively easy to gather. The goal of this study is to use artificial intelligence techniques to design and build soft sensors. The combination of a Long Short-Term Memory (LSTM) network and Grey Wolf Optimization (GWO) is used to create a unique soft sensor. LSTM is developed to tackle linear model with strong nonlinearity and unpredictability of manufacturing applications in the learning approach. GWO is used to accomplish input optimization technique for LSTM in order to reduce the model's inappropriate complication. The newly designed soft sensor originally brought LSTM's superior dynamic modeling with GWO's exact variable selection. The performance of our proposal is demonstrated using simulations on real-world datasets.

• Journal of Sensor Science and Technology
• /
• v.33 no.1
• /
• pp.7-11
• /
• 2024

Soft-pressure sensors have numerous applications in soft robotics, biomedical devices, and wearable smart devices. Herein, we present a highly sensitive electronic skin device with an isotropic wrinkled pressure sensor. A conductive ink for soft pressure sensors is produced by a solution process using polydimethylsiloxane (PDMS), poly 3-hexylthiophene (P3HT), carbon black, and chloroform as the solvents. P3HT provides high reproducibility and conductivity by improving the ink dispersibility. The conductivity of the ink is optimized by adjusting the composition of the carbon black and PDMS. Soft lithography is used to fabricate a conductive elastic structure with an isotropic wrinkled structure. Two conductive elastic structures with an isotropic wrinkle structure is stacked to develop a pressure sensor, and it is confirmed that the isotropic wrinkle structure is more sensitive to pressure than when two elastic structures with an anisotropic wrinkle structure are overlapped. Specifically, the pressure sensor fabricated with an isotropic wrinkled structure can detect extremely low pressures (1.25 Pa). Additionally, the sensor has a high sensitivity of 15.547 kpa^-1 from 1.25 to 2500 Pa and a linear sensitivity of 5.15 kPa^-1 from 2500 Pa to 25 kPa.

• Transactions of the Korean hydrogen and new energy society
• /
• v.25 no.5
• /
• pp.491-499
• /
• 2014

It is important to accurately measure and control the relative humidity of humidified gas entering a PEM (polymer electrolyte membrane) fuel cell stack because the level of humidification strongly affects the performance and durability of the stack. Humidity measurement devices can be used to directly measure the relative humidity, but they cost much to be equipped and occupy spaces in a fuel cell system. We present soft sensors for predicting the relative humidity without actual humidity measuring devices. By combining FIR (finite impulse response) model with PLS (partial least square) and SVM (support vector machine) regression models, DPLS (dynamic PLS) and DSVM (dynamic SVM) soft sensors were developed to correctly estimate the relative humidity of humidified gases exiting a planar-type membrane humidifier. The DSVM soft sensor showed a better prediction performance than the DPLS one because it is able to capture nonlinear correlations between the relative humidity and the input data of the soft sensors. Without actual humidity sensors, the soft sensors presented in this work can be used to monitor and control the humidity in operation of PEM fuel cell systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.4774-4796
• /
• 2018

Wireless sensor networks are composed of a large number of inexpensive and tiny sensors used in different areas including military, industry, agriculture, space, and environment. Fault tolerance, which is considered a challenging task in these networks, is defined as the ability of the system to offer an appropriate level of functionality in the event of failures. The present study proposed an intelligent throughput descent and distributed energy-efficient mechanism in order to improve fault tolerance of the system against soft and permanent faults. This mechanism includes determining the intelligent neighborhood radius threshold, the intelligent neighborhood nodes number threshold, customizing the base paper algorithm for distributed systems, redefining the base paper scenarios for failure detection procedure to predict network behavior when running into soft and permanent faults, and some cases have been described for handling failure exception procedures. The experimental results from simulation indicate that the proposed mechanism was able to improve network throughput, fault detection accuracy, reliability, and network lifetime with respect to the base paper.

• Ceramist
• /
• v.23 no.1
• /
• pp.16-26
• /
• 2020

Recently, polymer-metal composite (IPMC)-based ionic artificial muscle has been drawing a huge attention for its excellent soft actuator performance having outstanding soft actuator performance with efficient conversion of electrical energy to mechanical energy under low working voltage. In addition, light, flexible and soft nature of IPMC and high bending strain response enabled development of versatile sensor application in association with soft actuator. In this paper, current issues of IPMC were discussed including standardizing preparation steps, relaxation under DC bias, inhibiting solvent evaporation, and improving poor output force. Solutions for these drawbacks of IPMC have recently been suggested in recent studies. After following explanation of the IPMC working mechanism, we investigate the main factors that affect the operating performance of the IPMC. Then, we reviewed the optimized IPMC actuator fabrication conditions especially for the preparation process, additive selection for a thicker membrane, water content, solvent substitutes, encapsulation, etc. Lastly, we considered the pros and cons of IPMCs for sensor application in a theoretical and experimental point of view. The strategies discussed in this paper to overcome such deficiencies of IPMCs are highly expected to provide a scope for IPMC utilization in soft robotics application.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2009.10a
• /
• pp.641-644
• /
• 2009

We demonstrated a solvent-assisted soft-lithographic patterning method for producing patterned structure and patterned ordering with lyotropic liquid crystalline polymer (LCP) film. Experimental results showed that the liquid crystalline ordering of lyotropic film could be controlled by shearing effects of the fluidic solvent though the patterned mold channels. In this work, two types of lyotropic LCPs were used to investigate the effects of the alkyl chain length of the lyotropic LCP on producing liquid crystalline ordering through the solvent-assisted fluidic patterning.

• Journal of the Korean Institute of Gas
• /
• v.2 no.3
• /
• pp.49-53
• /
• 1998

It takes quite a long time for an analyzer, such as gas chromatography, to measure a bulk property of a system, which prevents on-line measurements. Also, the cost of installation and maintenance is very high. Consequently, some other means is needed for on-line measurements of properties and the development of soft sensors based on process variables like temperature and pressure is of great interest. In the field of gas industry, the development of a soft sensor which makes indirect on-line measurements of gas compositions and flow rate, is in progress. In this paper, we proposed a hybrid inner model PLS which improved the prediction performance by taking into account the data structure, as an empirical modeling algorithm. When applied to a design of a soft sensor of a distillation tower, the hybrid inner model PLS showed better prediction performance than other methods.

• Journal of Adhesion and Interface
• /
• v.21 no.4
• /
• pp.162-167
• /
• 2020

The skin-inspired multimodal soft sensors have been developed through multidisciplinary approaches to mimic the sensing ability with high sensitivity and mechanical durability of human skin. For practical application, although the stimulus discriminability against a complex stimulus composed of various mechanical and thermal stimuli experienced in daily life is essential, it still shows a low level actually. In this paper, we first introduce the operating mechanisms and representative studies of the unimodal soft sensor, and then discuss the recent research trend in the multimodal soft sensors and the stimulus discriminability.