A variety of faulty radar echoes may cause serious problems with radar data applications,especially radar data assimilation and quantitative precipitation estimates.In this study,＂test pattern＂ caused by test signal...A variety of faulty radar echoes may cause serious problems with radar data applications,especially radar data assimilation and quantitative precipitation estimates.In this study,＂test pattern＂ caused by test signal or radar hardware failures in CINRAD （China New Generation Weather Radar） SA and SB radar operational observations are investigated.In order to distinguish the test pattern from other types of radar echoes,such as precipitation,clear air and other non-meteorological echoes,five feature parameters including the effective reflectivity data percentage （Rz）,velocity RF （range folding） data percentage （RRF）,missing velocity data percentage （RM）,averaged along-azimuth reflectivity fluctuation （RNr,z） and averaged along-beam reflectivity fluctuation （RNa,z） are proposed.Based on the fuzzy logic method,a test pattern identification algorithm is developed,and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm.Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed.The statistical results show that the test pattern identification algorithm performs well,since the test pattern is recognized in most cases.Besides,the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.展开更多
This paper presents modeling tools based on Boolean satisfiability (SAT) to solve problems of test generation for combinational circuits. It exploits an added layer to maintain circuit-related information and value ju...This paper presents modeling tools based on Boolean satisfiability (SAT) to solve problems of test generation for combinational circuits. It exploits an added layer to maintain circuit-related information and value justification relations to a generic SAT algorithm. It dovetails binary decision graphs (BDD) and SAT techniques to improve the efficiency of automatic test pattern generation (ATPG). More specifically, it first exploits inexpensive reconvergent fanout analysis of circuit to gather information on the local signal correlation by using BDD learning, then uses the above learned information to restrict and focus the overall search space of SAT-based ATPG. Its learning technique is effective and lightweight. The experimental results demonstrate the effectiveness of the approach.展开更多
Advancements in semiconductor technology are making gate-level test generation more challenging. This is because a large amount of detailed structural information must be processed in the search process of automatic t...Advancements in semiconductor technology are making gate-level test generation more challenging. This is because a large amount of detailed structural information must be processed in the search process of automatic test pattern generation (ATPG). In addition, ATPG needs to deal with new defects caused by process variation when IC is shrinking. To reduce the computation effort of ATPG, test generation could be started earlier at higher abstraction level, which is in line with top-down design methodology that has become more popular nowadays. In this research, we employ Chen’s high-level fault model in the high-level ATPG. Besides shorter ATPG time as shown in many previous works, our study showed that high-level ATPG also contributes to test compaction. This is because most of the high-level faults correlate with the gate-level collapsed faults especially at input/output of the modules in a circuit. The high-level ATPG prototype used in our work is mainly composed by constraint-driven test generation engine and fault simulation engine. Experimental result showed that more reduced/compact test set can be generated from the high-level ATPG.展开更多
Static compaction methods aim at finding unnecessary test patterns to reduce the size of the test set as a post-process of test generation.Techniques based on partial maximum satisfiability are often used to track man...Static compaction methods aim at finding unnecessary test patterns to reduce the size of the test set as a post-process of test generation.Techniques based on partial maximum satisfiability are often used to track many hard problems in various domains,including artificial intelligence,computational biology,data mining,and machine learning.We observe that part of the test patterns generated by the commercial Automatic Test Pattern Generation(ATPG)tool is redundant,and the relationship between test patterns and faults,as a significant information,can effectively induce the test patterns reduction process.Considering a test pattern can detect one or more faults,we map the problem of static test compaction to a partial maximum satisfiability problem.Experiments on ISCAS89,ISCAS85,and ITC99 benchmarks show that this approach can reduce the initial test set size generated by TetraMAX18 while maintaining fault coverage.展开更多
Kissing bonds are defects in the adhesive bonds with intimate contact of touching surface but considerably lowered shear strength. Their detection specifically in the aerospace area is so not satisfactory. Usually, ki...Kissing bonds are defects in the adhesive bonds with intimate contact of touching surface but considerably lowered shear strength. Their detection specifically in the aerospace area is so not satisfactory. Usually, kissing bonds are inconspicuous in ultrasonic C-scans. However, the determination of attributes in the time domain and the frequency domain of an ultrasound signal provides the opportunity to derive a pattern for bonded area. Deviations from the pattern found in inconspicuous bonding areas indicate kissing bonds. The survey described here deals with the manufacturing of adhesively joint samples that purposefully include kissing bonds, as well as potential solutions for detecting them through ultrasonic testing combined with pattern recognition. The properties of the epoxy-based adhesive were varied by changing the mixing ratios between resin and hardener. Samples with a mixing ratio far apart from the manufacturer’s recommendation with an inconspicuous appearance in a C-scan, but low shear strength values were taken for further evaluation. After a definition and learning phase, a 100 percent hit rate to separate good bondings from kissing bonds could be derived in a blind test. The discriminating feature found is due to the frequency shift between good and kissing bonds as well as the relative amplitude of the second peak.展开更多
In order to accurately predict the single event upsets （SEU） rate of on-orbit proton, the influence of the proton energy distribution, incident angle, supply voltage, and test pattern on the height, width, and posit...In order to accurately predict the single event upsets （SEU） rate of on-orbit proton, the influence of the proton energy distribution, incident angle, supply voltage, and test pattern on the height, width, and position of SEU peak of low energy protons （LEP） in 65 nm static random access memory （SRAM） are quantitatively evaluated and analyzed based on LEP testing data and Monte Carlo simulation. The results show that different initial proton energies used to degrade the beam energy will bring about the difference in the energy distribution of average proton energy at the surface and sensitive region of the device under test （DUT）, which further leads to significant differences including the height of SEU peak and the threshold energy of SEU. Using the lowest initial proton energy is extremely important for SEU testing with low energy protons. The proton energy corresponding to the SEU peak shifts to higher average proton energies with the increase of the tilt angle, and the SEU peaks also increase significantly. The reduction of supply voltage lowers the critical charge of SEU, leading to the increase of LEP SEU cross section. For standard 6-transitor SRAM with bit-interleaving technology, SEU peak does not show clear dependence on three test patterns of logical checkerboard 55H, all＂ 1＂, and all ＂0＂. It should be noted that all the SEUs in 65 nm SRAM are single cell upset in LEP testing due to proton＇s low linear energy transfer （LET） value.展开更多
基金supported by the National Key Program for Developing Basic Sciences under Grant 2012CB417202the National Natural Science Foundation of China under Grant No. 41175038, No. 41305088 and No. 41075023+4 种基金the Meteorological Special Project "Radar network observation technology and QC"the CMA Key project "Radar Operational Software Engineering"the Chinese Academy of Meteorological Sciences Basic ScientificOperational Projects "Observation and retrieval methods of micro-physics and dynamic parameters of cloud and precipitation with multi-wavelength Remote Sensing"Project of the State Key Laboratory of Severe Weather grant 2012LASW-B04
文摘A variety of faulty radar echoes may cause serious problems with radar data applications,especially radar data assimilation and quantitative precipitation estimates.In this study,＂test pattern＂ caused by test signal or radar hardware failures in CINRAD （China New Generation Weather Radar） SA and SB radar operational observations are investigated.In order to distinguish the test pattern from other types of radar echoes,such as precipitation,clear air and other non-meteorological echoes,five feature parameters including the effective reflectivity data percentage （Rz）,velocity RF （range folding） data percentage （RRF）,missing velocity data percentage （RM）,averaged along-azimuth reflectivity fluctuation （RNr,z） and averaged along-beam reflectivity fluctuation （RNa,z） are proposed.Based on the fuzzy logic method,a test pattern identification algorithm is developed,and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm.Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed.The statistical results show that the test pattern identification algorithm performs well,since the test pattern is recognized in most cases.Besides,the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.
基金Supported by Joint Research Fund for Overseas Chinese Young Scholars (No. 50128503) and National Natural Science Foundation of China (No. 50390060)
文摘This paper presents modeling tools based on Boolean satisfiability (SAT) to solve problems of test generation for combinational circuits. It exploits an added layer to maintain circuit-related information and value justification relations to a generic SAT algorithm. It dovetails binary decision graphs (BDD) and SAT techniques to improve the efficiency of automatic test pattern generation (ATPG). More specifically, it first exploits inexpensive reconvergent fanout analysis of circuit to gather information on the local signal correlation by using BDD learning, then uses the above learned information to restrict and focus the overall search space of SAT-based ATPG. Its learning technique is effective and lightweight. The experimental results demonstrate the effectiveness of the approach.
文摘Advancements in semiconductor technology are making gate-level test generation more challenging. This is because a large amount of detailed structural information must be processed in the search process of automatic test pattern generation (ATPG). In addition, ATPG needs to deal with new defects caused by process variation when IC is shrinking. To reduce the computation effort of ATPG, test generation could be started earlier at higher abstraction level, which is in line with top-down design methodology that has become more popular nowadays. In this research, we employ Chen’s high-level fault model in the high-level ATPG. Besides shorter ATPG time as shown in many previous works, our study showed that high-level ATPG also contributes to test compaction. This is because most of the high-level faults correlate with the gate-level collapsed faults especially at input/output of the modules in a circuit. The high-level ATPG prototype used in our work is mainly composed by constraint-driven test generation engine and fault simulation engine. Experimental result showed that more reduced/compact test set can be generated from the high-level ATPG.
基金supported by the National Natural Science Foundation of China(Nos.61672261 and 61872159)。
文摘Static compaction methods aim at finding unnecessary test patterns to reduce the size of the test set as a post-process of test generation.Techniques based on partial maximum satisfiability are often used to track many hard problems in various domains,including artificial intelligence,computational biology,data mining,and machine learning.We observe that part of the test patterns generated by the commercial Automatic Test Pattern Generation(ATPG)tool is redundant,and the relationship between test patterns and faults,as a significant information,can effectively induce the test patterns reduction process.Considering a test pattern can detect one or more faults,we map the problem of static test compaction to a partial maximum satisfiability problem.Experiments on ISCAS89,ISCAS85,and ITC99 benchmarks show that this approach can reduce the initial test set size generated by TetraMAX18 while maintaining fault coverage.
文摘Kissing bonds are defects in the adhesive bonds with intimate contact of touching surface but considerably lowered shear strength. Their detection specifically in the aerospace area is so not satisfactory. Usually, kissing bonds are inconspicuous in ultrasonic C-scans. However, the determination of attributes in the time domain and the frequency domain of an ultrasound signal provides the opportunity to derive a pattern for bonded area. Deviations from the pattern found in inconspicuous bonding areas indicate kissing bonds. The survey described here deals with the manufacturing of adhesively joint samples that purposefully include kissing bonds, as well as potential solutions for detecting them through ultrasonic testing combined with pattern recognition. The properties of the epoxy-based adhesive were varied by changing the mixing ratios between resin and hardener. Samples with a mixing ratio far apart from the manufacturer’s recommendation with an inconspicuous appearance in a C-scan, but low shear strength values were taken for further evaluation. After a definition and learning phase, a 100 percent hit rate to separate good bondings from kissing bonds could be derived in a blind test. The discriminating feature found is due to the frequency shift between good and kissing bonds as well as the relative amplitude of the second peak.
基金Project supported by the Major Program of the National Natural Science Foundation of China(Grant Nos.11690040 and 11690043)
文摘In order to accurately predict the single event upsets （SEU） rate of on-orbit proton, the influence of the proton energy distribution, incident angle, supply voltage, and test pattern on the height, width, and position of SEU peak of low energy protons （LEP） in 65 nm static random access memory （SRAM） are quantitatively evaluated and analyzed based on LEP testing data and Monte Carlo simulation. The results show that different initial proton energies used to degrade the beam energy will bring about the difference in the energy distribution of average proton energy at the surface and sensitive region of the device under test （DUT）, which further leads to significant differences including the height of SEU peak and the threshold energy of SEU. Using the lowest initial proton energy is extremely important for SEU testing with low energy protons. The proton energy corresponding to the SEU peak shifts to higher average proton energies with the increase of the tilt angle, and the SEU peaks also increase significantly. The reduction of supply voltage lowers the critical charge of SEU, leading to the increase of LEP SEU cross section. For standard 6-transitor SRAM with bit-interleaving technology, SEU peak does not show clear dependence on three test patterns of logical checkerboard 55H, all＂ 1＂, and all ＂0＂. It should be noted that all the SEUs in 65 nm SRAM are single cell upset in LEP testing due to proton＇s low linear energy transfer （LET） value.
