CONDITION MONITOR OF DEEP-HOLE DRILLING BASED ON MULTI-SENSOR INFORMATION FUSION

A condition monitoring method of deep-hole drilling based on multi-sensor information fusion is discussed. The signal of vibration and cutting force are collected when the condition of deep-hole drilling on stainless steel 0Cr17Ni4Cu4Nb is normal or abnormal. Four eigenvectors are extracted on time-domain and frequency-domain analysis of the signals. Then the four eigenvectors are combined and sent to neural networks to dispose. The fusion results indicate that multi-sensor information fusion is superior to single-sensor information, and that cutting force signal can reflect the condition of cutting tool better than vibration signal.

Crack status analysis for concrete dams based on measured entropy

The integrity and safety of concrete darns are seriously affected by the existing cracks in dam bodies, and some serious cracks may cause dam failure or disaster. The propagation of cracks in concrete dams is accompanied by changes in energy distribution, which can be represented by changes in the structure＇s system entropy. Therefore, the entropy theory can be used in analyzing the behavior of dam cracks. Due to the randomness and locality of crack propagation, it is difficult to predict the loca- tion of cracks by traditional monitoring methods. To solve this problem, the influence of spatial positions of monitoring points on inspection zones is represented by a weight index, and the weight index is determined by the distance measure method proposed in this paper. Through the weighted linear fusion method, the entropy of multiple monitoring points is obtained for analyzing the behavior of dam cracks in the selected zones. Meanwhile, the catastrophe theory is used as the variation criterion of an entropy sequence in order to predict the instability time of dam cracks. Case studies are put forward on a high arch darn, and the fusion entropy is calculated according to the monitoring data from strain gauges. Results show that the proposed method can effectively predict the occurrence time and location of dam cracks regardless of the layout of monitoring instruments, and it is a new way to analyze the occurrence and propagation of dam cracks.

Evaluation of health benefit using Ben MAP-CE with an integrated scheme of model and monitor data during Guangzhou Asian Games

Guangzhou is the capital and largest city（land area：7287 km2）of Guangdong province in South China.The air quality in Guangzhou typically worsens in November due to unfavorable meteorological conditions for pollutant dispersion.During the Guangzhou Asian Games in November 2010,the Guangzhou government carried out a number of emission control measures that significantly improved the air quality.In this paper,we estimated the acute health outcome changes related to the air quality improvement during the 2010 Guangzhou Asian Games using a next-generation,fully-integrated assessment system for air quality and health benefits.This advanced system generates air quality data by fusing model and monitoring data instead of using monitoring data alone,which provides more reliable results.The air quality estimates retain the spatial distribution of model results while calibrating the value with observations.The results show that the mean PM2.5concentration in November 2010 decreased by 3.5μg/m^3 compared to that in 2009 due to the emission control measures.From the analysis,we estimate that the air quality improvement avoided 106 premature deaths,1869 cases of hospital admission,and 20,026 cases of outpatient visits.The overall cost benefit of the improved air quality is estimated to be 165 million CNY,with the avoided premature death contributing 90%of this figure.The research demonstrates that Ben MAP-CE is capable of assessing the health and cost benefits of air pollution control for sound policy making.