• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.7
• /
• pp.101-108
• /
• 1999

A reliable and practical monitoring of drill breakage is a crucial technique in automatic machining system. In this study, a real-time monitoring system was developed to predict drill breakage using both spindle and z-axis motor current. Drill breakage is monitored by detecting the level of residual motor current which is obtained through the moving average filter algorithm. The residual exhibits a feature of sharp decrease just before drill breakage. Therefore, drill breakage can be predicted by detecting this characteristic of residual component. Z-axis motor current is better to predict the drill breakage than spindle motor current, because the former is faster in response than the latter when drill breakage is occurred. The evaluation experiments have shown that the developed monitoring system works very well.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.57 no.6
• /
• pp.107-115
• /
• 2015

The objective of the this study is to find the breakage index and changes in permeability of Bottom ash from thermoelectric power plants in Korea. Bottom ash was crushed by compaction according to compaction energy from 0 to $1661.4\;kN/m^2$. The particle size distribution was estimated by sieve analysis. The various breakage indexes were used for analyzing the change in particle size distribution and effect of compaction energy. In the result, breakage indexes were increased as compaction energy and initial upper 4.75 mm diameter ratio, but values and tendencies of breakage indexes appeared in different as calculation method of breakage indexes. The coefficient of permeability was decreased with particle breakage, but decreasing ratio of permeability was very small. Bottom ash has a higher permeability than the weathered soil and it is considered high usability as a permeable materials.

• Geomechanics and Engineering
• /
• v.11 no.5
• /
• pp.639-655
• /
• 2016

The effect of particle breakage and intermediate principal stress ratio on the behaviour of crushable granular assemblies under true triaxial stress conditions is studied using the discrete element method. Numerical results show that the increase of intermediate principal stress ratio $b(b=({\sigma}_2-{\sigma}_3)/({\sigma}_1-{\sigma}_3))$ results in the increase of dilatancy at low confining pressures but the decrease of dilatancy at high confining pressures, which stems from the distinct increasing compaction caused by breakage with b. The influence of b on the evolution of the peak apparent friction angle is also weakened by particle breakage. For low relative breakage, the relationship between the peak apparent friction angle and b is close to the Lade-Duncan failure model, whereas it conforms to the Matsuoka-Nakai failure model for high relative breakage. In addition, the increasing tendency of relative breakage, calculated based on a fractal particle size distribution with the fractal dimension being 2.5, declines with the increasing confining pressure and axial strain, which implies the existence of an ultimate graduation. Finally, the relationship between particle breakage and plastic work is found to conform to a unique hyperbolic correlation regardless of the test conditions.

• Smart Structures and Systems
• /
• v.30 no.5
• /
• pp.463-477
• /
• 2022

In this paper, a hybrid vibration-impedance-based damage monitoring approach is experimentally evaluated for prestressed concrete (PSC) structures with local strand breakage. Firstly, the hybrid monitoring scheme is designed to alert damage occurrence from changes in vibration characteristics and to localize strand breakage from changes in impedance signatures. Secondly, a full-scale PSC anchorage is experimented to measure global vibration responses and local impedance responses under a sequence of simulated strand-breakage events. Finally, the measured data are analyzed using the hybrid monitoring framework. The change of structural condition (i.e., damage extent) induced by the local strand breakage is estimated by changes in a few natural frequencies obtained from a few accelerometers in the structure. The damaged strand is locally identified by tomography analysis of impedance features measured via an array of PZT (lead-zirconate-titanate) sensors mounted on the anchorage. Experimental results demonstrate that the strand breakage in the PSC structure can be accurately assessed by using the combined vibration and impedance features.

• Tribology and Lubricants
• /
• v.28 no.3
• /
• pp.130-135
• /
• 2012

This study presents a new methodology for realtime tool breakage detection by sensor fusion concept of two hall sensor and an acoustic emission (AE) sensor. Spindle induction motor torque of CNC Lathe during machining is estimated by two hall sensor. Estimated motor torque instead of a tool dynamometer was used to measure the cutting torque and tool breakage detection. A burst of AE signal was used as a triggering signal to inspect the cutting torque. A significant drop of cutting torque was utilized to detect tool breakage. The algorithm was implemented on a NI DAQ (Data Acquisition) board for in-process tool breakage detection. The result of experiment showed an excellent monitoring capability of the proposed tool breakage detection system. This system is available tool breakage monitoring through internet also provides this system's user with current cutting torque of induction motor.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.14 no.6
• /
• pp.1-6
• /
• 2015

Tool condition monitoring plays one of the most important roles in the improvement of both machining quality and productivity. In this regard, various process signals and monitoring methods have been developed. However, most of the existing studies used cutting force or acoustic emission signals, which posed risks of interference with the machining system in dynamics, fixturing, and machining configuration. In this study, a feed motor current signal is used as a process signal representing process and tool states in tool breakage monitoring based on an adaptive autoregressive model and unsupervised neural network. From the experimental results using various cases of tool breakage, it is shown that the developed system can successfully detect tool breakage before two revolutions of the spindle after tool breakage.

• Geomechanics and Engineering
• /
• v.15 no.1
• /
• pp.687-694
• /
• 2018

To investigate the crushing behaviour of coarse granular materials, a specifically designed, large-scale simple shear apparatus with eight-staged shearing rings was developed. A series of monotonic simple shear tests were conducted on two kinds of coarse granular materials under different vertical stresses and large shear strains. The evolution of the particle breakage during the compression and simple shearing processes was investigated. The results show that the amount of particle breakage is related to the particle hardness and the state of the stresses. The amount of particle breakage is greater for softer granular materials and increases with increasing vertical stresses. Particle breakage may tend towards a critical value during both the compression and the shearing processes. Particle breakage mainly occurs during the processes of confined compression and contraction.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2013.05a
• /
• pp.236-237
• /
• 2013

In recent years, the use of glass applied to curtain wall as a building facade material has increased in our nation. However, the non-tempered curved double glass is very easy to broke because it is difficult to guarantee the quality in process of making it into double glazing. So, it is more vulnerable to thermal breakage than tempered double glass. In this paper, surface temperature difference on curved double glazing was compared to that of heat strengthened glass and flat glass by conducting thermal breakage experiments. As a result, flat single glass was broken at temperature difference of 100~140 degrees but curved double glazing was broken at that of 40~60 degrees. Therefore, it was concluded that curved double glazing is more vulnerable than flat double glazing to thermal breakage, and it should be considered the possibility of thermal breakage when curtain wall glazing is applied as a building facade material.

• Journal of Korea Water Resources Association
• /
• v.42 no.10
• /
• pp.785-793
• /
• 2009

Numerical model which can simulate the surge tank for unsteady flow was developed in the present study. Furthermore, reliability model which can calculate the probability of pipe breakage regarding unsteady effect was developed. For the risk estimation of pipe breakage and functional estimation of surge tank, probability of pipe breakage for pipe network with surge tank was calculated regarding unsteady effect. From the results, it was found that unsteady flow significantly increase the probability of pipe breakage and surge tank considerably decrease probability of pipe breakage as damping out the pressure oscillations.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1343-1346
• /
• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).