Study and Design of Human-Machine Interface System for Embedded CNC Precision Internal Grinder

With the development of high-speed and high-precision printing, the shaft-less drive system has been widely used in roll-to-roll gravure printing machines. In order to meet the functional demand of controlling printing unit conveniently and quickly, this paper designed an embedded human-machine interface (HMI) system of printing unit for the gravure printing machine. Based on analyzing the structure and composition of the shaft-less drive system, the functional requirements of the printing unit HMI system are analyzed, and the functional scheme of the embedded HMI system is proposed. Then the hardware circuit of the HMI system is designed with ARM as the core, and the software of the HMI system is developed with Keil C. Finally, the performance of the HMI system is studied by experiment. The experimental results show that the embedded HMI system can meet the requirements of printing unit control operation of roll-to-roll gravure printing machine.

Conventional human-machine interface (HMI) systems generally take surface electromyography as the only signal source, which often faces the problem of multi-channel crosstalk. To enhance HMI performance, this study introduces a novel three-degree-of-freedom HMI system for surgical robot control, which integrates surface electromyography signals and inertial measurement unit signals. A cost-effective wearable HMI hardware system is designed to address the high price and poor portability of existing commercial equipment, which also has a higher signal-to-noise ratio of 35.9 dB. Based on the proposed simultaneous and proportional control strategy, ten subjects were recruited to conduct an online experiment involving four upper limb postures to assess the real-time performance of the HMI system. Additionally, six able-bodied participants participated in a validation experiment to statistically verify and rigorously evaluate the implemented HMI system. The experimental results demonstrate that our HMI system can accurately decode the angles of the wrist and metacarpophalangeal joints in both single-degree-of-freedom and three-degree-of-freedom movements, achieving stable control and robust online performance. Furthermore, the proposed HMI system was applied to a flexible endoscopic robot to realize remote simultaneous and proportional control, and the results indicate that it can perform well in the practical application. The current study proves the feasibility and practicability of multi-source data fusion for HMI, providing a new direction.

The paper presents an electromyographic based (EMG based) human-machine interface system. To retain a constraint-free user environment, EMG sensing is limited to three arm muscles. EMG signals are processed to attain parameters that are related to the muscles' temporal activities. Using these parameters, a unique signature is constructed for each particular gesture. The problem of gesture classification is carried out in a framework of statistical pattern recognition. Experimental investigation was carried out to examine the system's reliability in recognizing 12 arm gestures. The results show that the system can recognize the 12 gestures with a success rate of 96%.

Nowadays, the research on wearable electronics have received tremendous attraction because of their potential applications in personalized health monitoring and treatment, energy conversion and storage, and human-machine interface system. Herein, we report a facile route for the fabrication of electrically conductive cotton fabric with excellent joule heating and high electromagnetic shielding performances using graphene oxide (GO) and silver nitrate (AgNO3). The GO used in this study is exclusively synthesized from spent batteries in order to minimize the environmental pollution. The surface morphology, elemental analysis, electrical conductivity, thermo-heating behavior and electromagnetic shielding performance have been studied systematically. Due to the high electrical conductivity, the GO-Ag coated cotton with 5 wt% of GO reached high surface temperature of 117.8°C within 35 s, and also it exhibits high electromagnetic interference shielding efficiency value of 79.08 dB. The high flexibility, excellent conductivity, electromagnetic shielding efficiency and joule heating performance of GO-Ag coated cotton fabric suggesting that the GO synthesized from spent batteries will be a potential and valuable resource for the new generation of wearable electronics.

High-performance flexible pressure sensors are highly desirable in health monitoring, robotic tactile, and artificial intelligence. Construction of microstructures in dielectrics and electrodes is the dominating approach to improving the performance of capacitive pressure sensors. Herein, we have demonstrated a novel three-dimensional microconformal graphene electrode for ultrasensitive and tunable flexible capacitive pressure sensors. Because the fabrication process is controllable, the morphologies of the graphene that is perfectly conformal with the electrode are controllable consequently. Multiscale morphologies ranging from a few nanometers to hundreds of nanometers, even to tens of micrometers, have been systematically investigated, and the high-performance capacitive pressure sensor with high sensitivity (3.19 kPa-1), fast response (30 ms), ultralow detection limit (1 mg), tunable-sensitivity, high flexibility, and high stability was obtained. Furthermore, an ultrasensitivity of 7.68 kPa-1 was successfully achieved via symmetric double microconformal graphene electrodes. The finite element analysis indicates that the microstructured graphene electrode can enhance large deformation and thus effectively improve the sensitivity. Additionally, the proposed pressure sensors are demonstrated with practical applications including insect crawling detection, wearable health monitoring, and force feedback of robot tactile sensing with a sensor array. The microconformal graphene may provide a new approach to fabricating controllable microstructured electrodes to enhance the performance of capacitive pressure sensors and has great potential for innovative applications in wearable health-monitoring devices, robot tactile systems, and human-machine interface systems.

Accurate temperature monitoring in the furnace is an important element in the processing of steel metals at PT Krakatau Baja Construction. Type S thermocouple sensors are used to measure temperature by converting temperature changes into voltage signals. However, to ensure the accuracy of the readings, thermocouple performance verification is carried out periodically. This research aims to verify thermocouples in several furnace zones to increase the accuracy of temperature data in the Human Machine Interface (HMI) system. The verification process uses the Fluke 17 B+ tool and Universal Transmitter PR4116. The measurement results are compared with the reference table and HMI readings before and after verification. The results show that all thermocouples function well with the largest deviation of 23°C in Zone 2A before adjustment and the smallest deviation of 1°C in Zone 1. Verification succeeded in reducing the deviation, ensuring the reliability of the measurement system. This research confirms the importance of thermocouple verification to improve production efficiency and product quality, with recommendations for regular evaluation of the HMI system and temperature measurements.

Remote welding robot system may be used for nuclear components maintenance, space assemble, underwater structures repair. This paper describes the remote welding robot system (RWRS) based on shared control. The paper introduces the structure of remote welding robot system, stereo vision system, autonomous seam-tracking system, the human-machine interface and graphics simulation system of teleoperation.

This paper describes the developmental study of HMI (human-machine interface) for a user-friendly automatic control system for the ESR process running in Changwon Specialty Steel in South Korea. ESR is a second-phase refining process, commonly applied to production of high purity specialty steel like high-speed tool steels. Because the current ESR system is fully manually operated for five hours, (1) the working condition is very hard, (2) the product quality varies according to time, product and worker, and (3) there is no standard control scheme especially in the transient stage of the start up and the ending hot top phases. Therefore, the main objective of this research is to develop a user-friendly automatic control system with human machine interface for unmanned operation. For this purpose, a melt rate measurement system is developed; real process variables are measured and analyzed; a standard control scheme is developed utilizing the expertise of experienced workers; a human machine interface system is developed utilizing graphical user interface; H/W and S/W is developed for integrated process control; and finally based upon a series of experiments the results are discussed. With this enhanced system, the workers can standardize their individual work knowledge and reach the optimum control pattern of their own as their work experiences accumulate.

Automatic media conversion schemes from speech to a facial image and a construction of a real-time image synthesis system are presented. The purpose of this research is to realize an intelligent human-machine interface or intelligent communication system with synthesized human face images. A human face image is reconstructed on the display of a terminal using a 3-D surface model and texture mapping technique. Facial motion images are synthesized by transformation of the 3-D model. In the motion driving method, based on vector quantization and the neural network, the synthesized head image can appear to speak some given words and phrases naturally, in synchronization with voice signals from a speaker. >

This paper reports the relation between glance-times at the screen of an in-vehicle HMI (Human-Machine Interface) system near the driver’s seat and the number of letters and characters dis-played on it. Our experimental results and discussion provide the fundamentals of a design method for HMIs operated by drivers to minimize glance-times. We conducted an experiment with a driving simulator to collect such data as time to read words displayed on in-vehicle HMIs while participants drove on an experimental course. The results indicate that for driving safety, the number of letters and characters displayed on an in-vehicle HMI screen should be less than 120.

This study proposes a data quality-driven channel selection methodology to improve hand gesture recognition performance in multi-channel wearable Human-Machine Interface (HMI) systems. The methodology centers around calculating (i) five data quality indices for both surface electromyography (sEMG) and pressure-based force myography (pFMG) signals and (ii) establishing a relationship between these data quality indices and the accuracy of gesture recognition for applications typified by prosthetic hand control. Machine learning (ML)-based and correlation-based methods were used to select three optimal channel/pair configurations from an eight-channel/pair system. Evaluations on the UOW and Ninapro DB2 datasets showed that the proposed methods consistently outperformed random channel selection, with the ML-based approach achieving the best results (76.36% for sEMG, 71.59% for pFMG, and 88.2% for fused sEMG-pFMG on the UOW dataset and 70.28% on Ninapro DB2). Notably, using three pairs of strategically selected sEMG-pFMG channels generated 88.2%, which is comparable to the 88.38% accuracy obtained with a full eight-channel sEMG system on the UOW dataset, highlighting the efficacy of our channel selection methodologies. These results highlight the value of data quality indices for sensor selection and provide a foundation for developing more efficient wearable HMI systems.

This work reports an ultrasensitive wearable temperature sensor based on GNWs/PDMS for personalized healthcare and human–machine interface systems.

This paper proposes a proximity sensing system, which has advantages of wide sensing area and rapid response. For the rapid and safe behavior of robots, high-speed detection of nearby and noncontact objects is important because of shorter time-to-contact. Here, we propose net-structure proximity sensor (NSPS), which covers large sensing area and fulfills 1-ms response time. NSPS is an array of infrared reflective proximity sensor elements integrated by a resistor network circuitry. Executing analog computation on the electrical circuitry, the sensing system outputs a few of meaningful signals, from the reaction distribution of all the elements. The signals mean the center position and approximate distance to the object. This sensor requires only six external wires regardless of the number of detecting elements. In this paper, we first show that various sizes of NSPS are easily configured by only using standard electronic parts. Next, we prototype NSPS with 25 elements in $5 \times 5$ matrix, and verify the output characteristics by experiments. At last, we discuss the availability of NSPS for robot hand systems and human–machine interface systems.

The automation control system to plate production line is developed independently. The whole system is divided into several levels and control functions are put into effect by the basic automation system, process automation system and human-machine-interface (HMI) system. Plate production thickness accuracy depends on the Automatic Gauge Control (AGC) function in the basic automation system for the plate mill area. With date communication module, process tracking module, data management module, and model calculation module, the core process model setup function is implemented by process automation system. Process monitoring and operation are implemented by HMI system. This automation control system proposed here has been applied successfully to several plate production lines in China with a good effect.

Fabrication process in industries requires highly skilled workforce to get caliber in part finishing. Welding process joins two materials at their melting point temperatures using thermal energy to melt and allowing them to cool results in fusion of materials. A quality welding demands high accuracy in the welding posture and hand speed of the skilled person. During mass production, manual welding results in loss in quality and production rate. An automatic welding Robot for compressor tank fabrication is developed with PLC as the controller, this design gives higher accuracy in the welding process in the compressor tank fabrication. A compressor tank is made from a sheet metal that is cut and rolled to desired diameter and then the edges are welded to prevent them from separating. The quality of welding in this case needs to be high because there must be no holes and pores in the welded area which may cause air leakage in the life cycle. The automation system gives a workable solution to the existing system and a dynamic analysis of stress and strain profiles of the impact that the welding machine supported by a cantilever beam is done. Programmable logic controller takes control of the transverse velocity with which the wielding head is moving and the optimal values for the welding process. Automation of the welding process is done with SPM(Special purpose machine) combined with automation tools viz. PLC, servo motors, servo drive, human machine interface, sensors & pneumatics systems.