• Journal of the Korean Society for Precision Engineering
• /
• v.17 no.8
• /
• pp.106-112
• /
• 2000

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skiful engineers. grinding operations include a large number of functional parameters since there are several ways of coping with ginding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workshop the other is the quantitative method which utilizes the experimental data obtained by sensor. But they are all difficult to accomplish from the grinding trouble-shooting system The reason is that grinding troubles are not accomplish from the grinding trouble-shooting system,. The rason is that grinding troubles are not easily controlled in the quantitative method and therefore trouble-shooting has mainly relied on the knoledge of skiful engineers. Thus there is an important issue of how a grinding touble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper basic strategy to develop the grinding database by taking rule-based model which is strongly depended upon experience and intuition is described.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.20 no.9
• /
• pp.28-34
• /
• 2021

The Fourth Industrial Revolution has led to the development of drones for commercial and private applications. Therefore, the malfunction of drones has become a prominent problem. Failure mode and effect analysis was used in this study to analyze the primary cause of drone failure, and blade breakage was observed to have the highest frequency of failure. This was tested using a vibration sensor placed on drones along the breakage length of the blades. The data exhibited a significant increase in vibration within the drone body for blade fracture length. Principal component analysis was used to reduce the data dimension and classify the state with machine learning algorithms such as support vector machine, k-nearest neighbor, Gaussian naive Bayes, and random forest. The performance of machine learning was higher than 0.95 for the four algorithms in terms of accuracy, precision, recall, and f1-score. A follow-up study on failure prediction will be conducted based on the results of fault diagnosis.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.21 no.3
• /
• pp.77-85
• /
• 2022

In this study, to diagnose the grinding state of a micro drill bit, a sensor attachment location was selected through random vibration analysis of the grinding unit of the micro drill-bit grinding system. In addition, the vibration data generated during the drill bit grinding were collected from the grinding unit for the grinding wheels under the steady and worn conditions, and data feature extraction and dimension reduction were performed. The wear of the micro-drill-bit grinding wheel was diagnosed by applying KNN, a machine-learning algorithm. The classification model showed excellent performance, with an accuracy of 99.2%. The precision, recall and f1-score were higher than 99% in both the steady and wear conditions.

• Journal of Korea Multimedia Society
• /
• v.12 no.11
• /
• pp.1609-1622
• /
• 2009

In wireless sensor networks, a clustering protocol is an efficient method to prolong network lifetime. In general, it results in more energy consumption at the cluster-head node. Hence, such a protocol must changes the cluster formation and cluster-head node in each round to prolong the network lifetime. But, this method also causes large amount of energy consumption during the set-up process of cluster formation. In order to improve energy efficiency, in this paper, we propose a new clustering algorithm. In this algorithm, we exclude duplicated data of adjacent nodes and transmits the threshold value. We define a group as the sensor nodes within close proximity of each other. In a group, a node senses and transmits data at a time on the round-robin basis. In a view of whole network, group is treated as one node. During the setup phase of a round, intra clusters are formed first and then they are re-clustered(network cluster) by choosing cluster-heads(group). In the group with a cluster-head, every member node plays the role of cluster-head on the round-robin basis. Hence, we can lengthen periodic round by a factor of group size. As a result of analysis and comparison, our scheme reduces energy consumption of nodes, and improve the efficiency of communications in sensor networks compared with current clustering methods.

• Journal of Korea Multimedia Society
• /
• v.11 no.8
• /
• pp.1082-1092
• /
• 2008

In wireless sensor networks, clustering protocol such as LEACH is an efficient method to increase whole networks lifetime. However, this protocol result in high energy consumption at the cluster head node. Hence, this protocol must changes the cluster formation and cluster head node in each round to prolong the network lifetime. But this method also causes a high amount of energy consumption during the set-up process of cluster formation. In order to improve energy efficiency, in this paper, we propose a new cluster formation algorithm. In this algorithm, we define a intra cluster as the sensor nodes within close proximity of each other. In a intra cluster, a node senses and transmits data at a time on the round-robin basis. In a view of whole network, intra cluster is treated as one node. During the setup phase of a round, intra clusters are formed first and then they are re-clustered(network cluster) by choosing cluster-heads(intra clusters). In the intra cluster with a cluster-head, every member node plays the role of cluster-head on the round-robin basis. Hence, we can lengthen periodic round by a factor of intra cluster size. Also, in the steady-state phase, a node in each intra cluster senses and transmits data to its cluster-head of network cluster on the round-robin basis. As a result of analysis and comparison, our scheme reduces energy consumption of nodes, and improve the efficiency of communications in sensor networks compared with current clustering methods.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38B no.11
• /
• pp.911-923
• /
• 2013

Multipath routing is one of challenging issues for improving the reliability of end-to-end data delivery in wireless sensor networks. Recently, a disjointedness and management of path have been studying to enhance the robustness and efficiency of the multipath routing. However, previous multipath routing protocols exploit the disjointed multipath construction method that is not to consider the wireless communication environment. In addition, if a path failures is occurred due to the node or link failures in the irregular network environment, they maintain the multipath through the simple method that to construct a new extra path. Even some of them have no a method. In order to cope with the insufficiency of path management, a hole detouring scheme, to bypass the failures area and construct the new paths, was proposed. However, it also has the problem that requires a heavy cost and a delivery suspension to the some or all paths in the hole detouring process due to the centralized and inflexible path management. Due to these limitations and problems, the previous protocols may lead to the degradation of data delivery reliability and the long delay of emergency data delivery. Thus, we propose a flexible disjoint multipath routing protocol which constructs the radio disjoint multipath by considering irregular and constrained wireless sensor networks. It also exploits a localized management based on the path priority in order to efficiently maintain the flexible disjoint multipath. We perform the simulation to evaluate the performance of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10b
• /
• pp.530-533
• /
• 1993

This paper describes a new method of dynamic error compensation, using a digital convolution integrator and two digital low pass filters. In this method, the process of compensation consists of three steps. First, sampling and digitizing of input signal, second, removing the noise in sampled data by the low pass filter and third, making a convolution integral using the output data of low pass filters. This method showed a good experimental result of reducing dynamic error even if there was a slight noise in the input signal. As a result, the detecting time constant of resistance thermo-bulb was improved to about 1/10th.

• Journal of Advanced Marine Engineering and Technology
• /
• v.25 no.1
• /
• pp.115-123
• /
• 2001

This study describes the combustion characteristics under various condition of air excess ratio and ignition timing in a 2-valve gasoline optically accessible engine with swirl control valve(SCV). It adapted three different types of SCA(open ration 72.5%, 78%, 89%) to strengthen a swirl flow. Pressure data were acquired using pressure sensor to investigate the effect of swirl flow on combustion, and from these pressure data, IMEP(indicated mean effective pressure) and MFB(mass fraction burnt)were calculated to explain burn rate and flame speed. From acquired flame images, inspected the flame propagation direction, flame area, and flame centroid, Flame propagation direction was shown different tendency between with/without SCV, and flame area with SCV was faster and larger than that of conventional engine. Finally, the representative flame image at each crank angle were acquired by PDF method to verify flame growth process. It is found that strengthened swirl flow is more beneficial for faster and stable combustion.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.10a
• /
• pp.604-608
• /
• 2004

In this paper, an efficient method is proposed to analyze the radial error of a miniaturized-high speed spindle system. Initially, a device is constructed for measuring the radial error motion using capacitance sensors. The capacitance sensors are placed perpendicular to the axis of the shaft and at 90o to each other. The spindle is rotated at high speed and the profile of the spindle is recorded. An algorithm is developed for analyzing the spindle data and determining the radial error of spindle. The present algorithm uses homogeneous transform matrix (HTM) method and iterative process for determining the radial error. The analysis procedure is performed for different speeds of the spindle. The data obtained from the present system and the results of evaluation are also presented in this paper. It is observed that this method is effective in determining and analyzing the spindle errors for high speed miniaturized spindle.

• Transactions on Electrical and Electronic Materials
• /
• v.14 no.5
• /
• pp.254-257
• /
• 2013

In-situ optical emission spectroscopy (OES) is employed for PECVD chamber monitoring. OES is used as an addon sensor to monitoring and cleaning end point detection (EPD). On monitoring plasma chemistry using OES, the process gas and by-product gas are simultaneously monitored. Principal component analysis (PCA) enhances the capability of end point detection using OES data. Through chamber cleaning monitoring using OES, cleaning time is reduced by 53%, in general. Therefore, the gas usage of fluorine is also reduced, so satisfying Green Fab challenge in semiconductor manufacturing.