Frame detection is important in burst communication systems for its contribu- tions in frame synchronization. It locates the information bits in the received data stream at receivers. To realize frame detection in the...Frame detection is important in burst communication systems for its contribu- tions in frame synchronization. It locates the information bits in the received data stream at receivers. To realize frame detection in the presence of additive white Gaussian noise （AWGN） and frequency offset, a constant false alarm rate （CFAR） detector is proposed through exploitation of cyclic autocorrelation feature implied in the preamble. The frame detection can be achieved prior to bit timing recovery. The threshold setting is independent of the signal level and noise level by utilizing CFAR method. Mathematical expressions is derived in AWGN channel by considering the probability of false alarm and probability of detection, separately. Given the probability of false alarm, the mathematical relationship between the frame detection performance and EJNo of received signals is established. Ex- perimental results are also presented in accor- dance with analysis.展开更多
A new flame detector with one ultraviolet and two infrared detectors is designed. The ultraviolet detector is of rapid response(≤10 μs) while the two infrared detectors usually have a response time of more than 5 ms...A new flame detector with one ultraviolet and two infrared detectors is designed. The ultraviolet detector is of rapid response(≤10 μs) while the two infrared detectors usually have a response time of more than 5 ms. The ultraviolet detector is applied to deal with the flame of large scales. When facing the flame of mid or small scales, the three detectors cooperate. Employing the high-order derivatives of the sample data of the infrared circuits to improve the sensitivity, the response speed is greatly improved. The data of the temperature sensor is used to adjust circuit parameters in real time, thus reducing the effect of temperature drift. The flame detectors are tested at different distances and the response time is as rapid as 0.65 ms. The test results show that the new flame detector has the characteristics of high speed and a low rate of false alarms.展开更多
Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A light...Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A lightweight network of two channels is bulit based on the combination of convolutional neural network(CNN)and graph convolutional network(GCN).CNNs learn feature difference maps of multitemporal images,and attention modules adaptively fuse CNN-based and graph-based features for different scales.GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels,generating change maps.Experimental evaluation on two datasets validates the efficacy of the pro-posed method in addressing false alarms.展开更多
A false alarm fault frequently appeared in antenna-servo system of the CINRAD/SA weather radar of Shanwei in the second half of 2011, so possible reasons for the false alarm fault were listed firstly using method of e...A false alarm fault frequently appeared in antenna-servo system of the CINRAD/SA weather radar of Shanwei in the second half of 2011, so possible reasons for the false alarm fault were listed firstly using method of exhaustion, and then the main reason was determined using exclusive method. That is, the fault was closely related to the signal transmission channel from the antenna mount to servo system in RDA cabinet. After ex- amining questionable nodes in the transmission channels of the alarm signal, we found that the false alarm fault might result from the interference of a burr in the temperature sensing circuit of the elevation motor. In actual operation, a filter capacitor was connected with the corresponding pin in the upper optical board to screen the interference of a burr, thereby successfully eliminating the false alarm fault in antenna-servo system of the CIN- RAD/SA radar of Shanwei.展开更多
Maintenance operations have a critical influence on power gen-eration by wind turbines(WT).Advanced algorithms must analyze large volume of data from condition monitoring systems(CMS)to determine the actual working co...Maintenance operations have a critical influence on power gen-eration by wind turbines(WT).Advanced algorithms must analyze large volume of data from condition monitoring systems(CMS)to determine the actual working conditions and avoid false alarms.This paper proposes different support vector machine(SVM)algorithms for the prediction and detection of false alarms.K-Fold cross-validation(CV)is applied to evaluate the classification reliability of these algorithms.Supervisory Control and Data Acquisition(SCADA)data from an operating WT are applied to test the proposed approach.The results from the quadratic SVM showed an accuracy rate of 98.6%.Misclassifications from the confusion matrix,alarm log and maintenance records are analyzed to obtain quantitative information and determine if it is a false alarm.The classifier reduces the number of false alarms called misclassifications by 25%.These results demonstrate that the proposed approach presents high reliability and accuracy in false alarm identification.展开更多
Diagnosing intermittent fault is an important approach to reduce built-in test（BIT） false alarms. Aiming at solving the shortcoming of the present diagnostic method of intermittent fault, and according to the merit ...Diagnosing intermittent fault is an important approach to reduce built-in test（BIT） false alarms. Aiming at solving the shortcoming of the present diagnostic method of intermittent fault, and according to the merit of support vector machines （ SVM） which can be trained with a small-sample, an SVM-based diagnostic model of 3 states that include OK state, intermittent state and faulty state is presented. With the features based on the reflection coefficients of an alarm rate （ AR ） model extracted from small vibration samples, these models are trained to diagnose intermittent faults. The experimental results show that this method can diagnose multiple intermittent faults accurately with small training samples and BIT false alarms are reduced.展开更多
Carbon monoxide can cause serious illness or even death if the functionality of smoke alarms fails in the residential home and, in fact, more than 350 persons die every year due to the leak of carbon monoxide. However...Carbon monoxide can cause serious illness or even death if the functionality of smoke alarms fails in the residential home and, in fact, more than 350 persons die every year due to the leak of carbon monoxide. However, vulnerabilities and threats to smoke/CO alarms have not been well-studied. In this paper, through interconnect, a power replay attack has been studied in order to trigger a false alarm. The experimental results demonstrate the smoke alarm can be manipulated. This paper also concentrates on providing a sequence of security methods to defend the smoke alarm system. In future, how to protect smart detectors against attacks will be studied as this can force them to leave high-quality mode of operations.展开更多
As oil and gas exploration continues to progress into deeper and unconventional reservoirs,the likelihood of kick risk increases,making kick warning a critical factor in ensuring drilling safety and efficiency.Due to ...As oil and gas exploration continues to progress into deeper and unconventional reservoirs,the likelihood of kick risk increases,making kick warning a critical factor in ensuring drilling safety and efficiency.Due to the scarcity of kick samples,traditional supervised models perform poorly,and significant fluctuations in field data lead to high false alarm rates.This study proposes an unsupervised graph autoencoder(GAE)-based kick warning method,which effectively reduces false alarms by eliminating the influence of field engineer operations and incorporating real-time model updates.The method utilizes the GAE model to process time-series data during drilling,accurately identifying kick risk while overcoming challenges related to small sample sizes and missing features.To further reduce false alarms,the weighted dynamic time warping(WDTW)algorithm is introduced to identify fluctuations in logging data caused by field engineer operations during drilling,with real-time updates applied to prevent normal conditions from being misclassified as kick risk.Experimental results show that the GAE-based kick warning method achieves an accuracy of 92.7%and significantly reduces the false alarm rate.The GAE model continues to operate effectively even under conditions of missing features and issues kick warnings 4 min earlier than field engineers,demonstrating its high sensitivity and robustness.After integrating the WDTW algorithm and real-time updates,the false alarm rate is reduced from 17.3%to 5.6%,further improving the accuracy of kick warnings.The proposed method provides an efficient and reliable approach for kick warning in drilling operations,offering strong practical value and technical support for the intelligent management of future drilling operations.展开更多
The intrusion of obstacles onto railway tracks presents a significant threat to train safety,characterized by sudden and unpredictable occurrences.With China leading the world in high-speed rail mileage,ensuring railw...The intrusion of obstacles onto railway tracks presents a significant threat to train safety,characterized by sudden and unpredictable occurrences.With China leading the world in high-speed rail mileage,ensuring railway security is paramount.The current laser monitoring technologies suffer from high false alarm rates and unreliable intrusion identification.This study addresses these issues by investigating high-resolution laser monitoring technology for railway obstacles,focusing on key parameters such as monitoring range and resolution.We propose an enhanced non-uniform laser scanning method,developing a laser monitoring system that reduces the obstacle false alarm rate to 2.00%,significantly lower than the 20%standard(TJ/GW135-2015).This rate is the best record for laser monitoring systems on China Railway.Our system operates seamlessly in all weather conditions,providing superior accuracy,resolution,and identification efficiency.It is the only 3D LiDAR system certified by the China State Railway Group Co.,Ltd.(Certificate No.[2023]008).Over three years,our system has been deployed at numerous points along various lines managed by the China State Railway Group,accumulating a dataset of 300,000 observations.This extensive deployment has significantly enhanced railway safety.The development and implementation of our railway laser monitoring system represent a substantial advancement in railway safety technology.Its low false alarm rate(2.00%),high accuracy(20 cm×20 cm×20 cm),and robust performance in diverse conditions underscore its potential for widespread adoption,promising to enhance railway safety in China and internationally.展开更多
A novel spectrum hole detection mechanism is proposed to improve the detection probability in cognitive radio networks for several typical scenarios. By removing the influence of the spatial false alarm （SFA）, the s...A novel spectrum hole detection mechanism is proposed to improve the detection probability in cognitive radio networks for several typical scenarios. By removing the influence of the spatial false alarm （SFA）, the spectrum hole detection probability of the secondary user under path loss and multi-path fading is derived. Meanwhile, the spectrum hole detection probability of multi-users cooperative sensing and that of single-user sensing in multi-bands are derived for comparison. Theoretical analyses and simulation results show that the spectrum hole detection probability of the proposed mechanism is inversely proportional to the sampling times and the area of the sensing region. The detection performance of the multi-users sensing is better than that of single-user sensing when with the AND ~ogic fusion rule but worse when with the OR logic fusion rule. The detection probability is further decreased in the Rayleigh fading channel but it is greatly increased in multi-bands.展开更多
Unlike the existing resonance region radar systems （RRRS ） that transmit the orthogonal frequency division multiplexing （OFDM）multi-carrier waveform,the dense multi-carrier （DMC）radar waveform which has a narrow...Unlike the existing resonance region radar systems （RRRS ） that transmit the orthogonal frequency division multiplexing （OFDM）multi-carrier waveform,the dense multi-carrier （DMC）radar waveform which has a narrower frequency interval than the traditional OFDM waveform is proposed.Therefore,in the same frequency bandwidth,the DMC waveform contains more sub-carriers and provides more frequency diversity.Additionally,to further improve detection performance,a novel optimal weight accumulation target detection （OWATD）method is proposed,where the echo electromagnetic waves at different frequencies are accumulated with the optimal weight coefficients.Then,with the signal-to-noise ratio （SNR）of echo waveform approaching infinity,the asymptotic detection performance is analyzed, and the condition that the OWATD method with the DMC outperforms the matched filter with the OFDM is presented.Simulation results show that the DMC outperforms the OFDM in the target detection performance,and the OWATD method can further improve the detection performance of the traditional methods with both the OFDM and DMC radar waveform.展开更多
Associating environmental stresses （ESs） with built-in test （BIT） output is an important means to help diagnose intermittent faults （IFs）. Aiming at low efficiency in association of traditional time stress measu...Associating environmental stresses （ESs） with built-in test （BIT） output is an important means to help diagnose intermittent faults （IFs）. Aiming at low efficiency in association of traditional time stress measurement device （TSMD）, an association model is built. Thereafter, a novel approach is given to evaluate the integrated environmental stress （IES） level. Firstly, the selection principle and approach of main environmental stresses （MESs） and key characteristic parameters （KCPs） are presented based on fault mode, mechanism, and ESs analysis （FMMEA）. Secondly, reference stress events （RSEs） are constructed by dividing IES into three stress levels according to its impact on faults; and then the association model between integrated environmental stress event （IESE） and BIT output is built. Thirdly, an interval grey association approach to evaluate IES level is proposed due to the interval number of IES value. Consequently, the association output can be obtained as well. Finally, a case study is presented to demonstrate the proposed approach. Results show the proposed model and approach are effective and feasible. This approach can be used to guide ESs measure, record, and association. It is well suited for on-line assistant diagnosis of faults, especially IFs.展开更多
For global navigation satellite system （GNSS） signals in Gaussian and Rayleigh fading channel, a novel signal detection algorithm is proposed. Under the low frequency uncertainty case, after performing discrete cosi...For global navigation satellite system （GNSS） signals in Gaussian and Rayleigh fading channel, a novel signal detection algorithm is proposed. Under the low frequency uncertainty case, after performing discrete cosine transform （DCT） to the outputs of the partial matched filter （PMF） for every antenna, the high order com- ponents in the transforming domain will be filtered, then the equalgain （EG） combination for the inverse discrete cosine transform （IDCT） reconstructed signal would be done subsequently. Thus, due to the different frequency distribution characteristics between the noise and signals, after EG combination, the energy of signals has almost no loss and the noise energy is greatly reduced. The theoretical analysis and simulation results show that the detection algorithm can effectively improve the signal-to-noise ratio of the captured signal and increase the probability of detection under the same false alarm probability. In addition, it should be pointed out that this method can also be applied to Rayleigh fading channels with moving antenna.展开更多
In order to eliminate false alarms,issued by gas sensors in coal mining,caused by Electromagnetic Interference(EMI),both computer simulation and field measurements were introduced to analyze the underground EMI distri...In order to eliminate false alarms,issued by gas sensors in coal mining,caused by Electromagnetic Interference(EMI),both computer simulation and field measurements were introduced to analyze the underground EMI distribution.A simplified model of a sensor with metal enclosure was established and the effects of shielding properties about the enclosure aperture were studied.Because the haulage motor is the moving EMI source,varying with time,the onsite flameproof measuring instruments cannot accomplish synchronous measurements of electromagnetic field vectors.To simplify the field measurements,two sensors,one with a lead and the other without a lead,were chosen to conduct the contrasting measurements.The EMI current caused by the perforation lead was comparatively strong and therefore nickel zinc ferrite beads were used to cut off the EMI propagation paths.The peak value of the interference current was reduced by 20%-70% with the beads.After switching on the sensor power,the sen-sors still occasionally gave false alarms when the switch of nearby large-scale electric equipment was operated.A complex EMI filter was used and the EMI attenuated markedly.The running results demonstrated that false alarms had been eliminated.We con-clude that the improved shielding and filtering are highly significant in enhancing the immunity of the gas sensor.展开更多
A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homo...A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homogeneity in CFAR reference windows is indicated by a VI-CFAR detector, a switching- CFAR detector is introduced to optimize the performance of the VI-CFAR detector in homogeneous, multiple targets and clutter edge backgrounds. The structure and parameters selection method of the SVI-CFAR detector is presented. Comparisons with classic CFAR detectors and recently proposed detectors are also given. Theoretical analysis and simulation results show that SVICFAR detector maintains the good performance of the VI-CFAR detector in homogeneous and clutter edge backgrounds, while greatly improving the capacity of anti-multi targets.展开更多
A novel adaptive detector for airborne radar space-time adaptive detection （STAD） in partially homogeneous environments is proposed. The novel detector combines the numerically stable Krylov subspace technique and d...A novel adaptive detector for airborne radar space-time adaptive detection （STAD） in partially homogeneous environments is proposed. The novel detector combines the numerically stable Krylov subspace technique and diagonal loading technique, and it uses the framework of the adaptive coherence estimator （ACE）. It can effectively detect a target with low sample support. Compared with its natural competitors, the novel detector has higher proba- bility of detection （PD）, especially when the number of the training data is low. Moreover, it is shown to be practically constant false alarm rate （CFAR）.展开更多
Acoustic array sensor device for partial discharge detection is widely used in power equipment inspection with the advantages of non-contact and precise positioning compared with partial discharge detection methods su...Acoustic array sensor device for partial discharge detection is widely used in power equipment inspection with the advantages of non-contact and precise positioning compared with partial discharge detection methods such as ultrasonic method and pulse current method.However,due to the sensitivity of the acoustic array sensor and the influence of the equipment operation site interference,the acoustic array sensor device for partial discharge type diagnosis by phase resolved partial discharge(PRPD)map might occasionally presents incorrect results,thus affecting the power equipment operation and maintenance strategy.The acoustic array sensor detection device for power equipment developed in this paper applies the array design model of equal-area multi-arm spiral with machine learning fast fourier transform clean(FFT-CLEAN)sound source localization identification algorithm to avoid the interference factors in the noise acquisition system using a single microphone and conventional beam forming algorithm,improves the spatial resolution of the acoustic array sensor device,and proposes an acoustic array sensor device based on the acoustic spectrogram.The analysis and diagnosis method of discharge type of acoustic array sensor device can effectively reduce the system misjudgment caused by factors such as the resolution of the acoustic imaging device and the time domain pulse of the digital signal,and reduce the false alarm rate of the acoustic array sensor device.The proposed method is tested by selecting power cables as the object,and its effectiveness is proved by laboratory verification and field verification.展开更多
Chemical process variables are always driven by random noise and disturbances. The closed-loop con-trol yields process measurements that are auto and cross correlated. The influence of auto and cross correlations on s...Chemical process variables are always driven by random noise and disturbances. The closed-loop con-trol yields process measurements that are auto and cross correlated. The influence of auto and cross correlations on statistical process control (SPC) is investigated in detail by Monte Carlo experiments. It is revealed that in the sense of average performance, the false alarms rates (FAR) of principal component analysis (PCA), dynamic PCA are not affected by the time-series structures of process variables. Nevertheless, non-independent identical distribution will cause the actual FAR to deviate from its theoretic value apparently and result in unexpected consecutive false alarms for normal operating process. Dynamic PCA and ARMA-PCA are demonstrated to be inefficient to remove the influences of auto and cross correlations. Subspace identification-based PCA (SI-PCA) is proposed to improve the monitoring of dynamic processes. Through state space modeling, SI-PCA can remove the auto and cross corre-lations efficiently and avoid consecutive false alarms. Synthetic Monte Carlo experiments and the application in Tennessee Eastman challenge process illustrate the advantages of the proposed approach.展开更多
A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the cl...A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the clutter PDF in the reference window are estimated by the non-parametric density estimation. The target detector is defined as the mean square error （MSE） distance between the two PDFs. The CFAR detection in SAR images having multiplicative noise is achieved by adaptive kernel bandwidth proportional to the clutter level. In addition, for obtaining a threshold with respect to a given probability of false alarm （PFA）, an unsupervised null distribution fitting method with outlier rejection is proposed. The effectiveness of the proposed target detector is demonstrated by the experiment result using the RADATSAT-2 SAR image.展开更多
Quantized fault detection for sensor/actuator faults of networked control systems （NCSs） with time delays both in the sensor-to-controller channel and controller-to-actuator channel is concerned in this paper. A fau...Quantized fault detection for sensor/actuator faults of networked control systems （NCSs） with time delays both in the sensor-to-controller channel and controller-to-actuator channel is concerned in this paper. A fault model is set up based on the possible cases of sensor/atuator faults. Then, the model predictive control is used to compensate the time delay. When the sensors and actuators are healthy, an H stability criterion of the state predictive observer is obtained in terms of linear matrix inequality. A new threshold computational method that conforms to the actual situation is proposed. Then, the thresholds of the false alarm rate （FAR） and miss detection rate （MDR） are presented by using our proposed method, which are also compared with the ones given in the existin~ literatures. Finally, some numerical simulations are shown to demonstrate the effectiveness of the proposed method.展开更多
基金supported by National Science Foundation of China under Grant No.61401205
文摘Frame detection is important in burst communication systems for its contribu- tions in frame synchronization. It locates the information bits in the received data stream at receivers. To realize frame detection in the presence of additive white Gaussian noise （AWGN） and frequency offset, a constant false alarm rate （CFAR） detector is proposed through exploitation of cyclic autocorrelation feature implied in the preamble. The frame detection can be achieved prior to bit timing recovery. The threshold setting is independent of the signal level and noise level by utilizing CFAR method. Mathematical expressions is derived in AWGN channel by considering the probability of false alarm and probability of detection, separately. Given the probability of false alarm, the mathematical relationship between the frame detection performance and EJNo of received signals is established. Ex- perimental results are also presented in accor- dance with analysis.
基金Project of Special Zone for National Defense Science and Technology Innovation(No.Y7GW04C001)
文摘A new flame detector with one ultraviolet and two infrared detectors is designed. The ultraviolet detector is of rapid response(≤10 μs) while the two infrared detectors usually have a response time of more than 5 ms. The ultraviolet detector is applied to deal with the flame of large scales. When facing the flame of mid or small scales, the three detectors cooperate. Employing the high-order derivatives of the sample data of the infrared circuits to improve the sensitivity, the response speed is greatly improved. The data of the temperature sensor is used to adjust circuit parameters in real time, thus reducing the effect of temperature drift. The flame detectors are tested at different distances and the response time is as rapid as 0.65 ms. The test results show that the new flame detector has the characteristics of high speed and a low rate of false alarms.
基金This work was supported by the Natural Science Foundation of Heilongjiang Province(LH2022F049).
文摘Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A lightweight network of two channels is bulit based on the combination of convolutional neural network(CNN)and graph convolutional network(GCN).CNNs learn feature difference maps of multitemporal images,and attention modules adaptively fuse CNN-based and graph-based features for different scales.GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels,generating change maps.Experimental evaluation on two datasets validates the efficacy of the pro-posed method in addressing false alarms.
文摘A false alarm fault frequently appeared in antenna-servo system of the CINRAD/SA weather radar of Shanwei in the second half of 2011, so possible reasons for the false alarm fault were listed firstly using method of exhaustion, and then the main reason was determined using exclusive method. That is, the fault was closely related to the signal transmission channel from the antenna mount to servo system in RDA cabinet. After ex- amining questionable nodes in the transmission channels of the alarm signal, we found that the false alarm fault might result from the interference of a burr in the temperature sensing circuit of the elevation motor. In actual operation, a filter capacitor was connected with the corresponding pin in the upper optical board to screen the interference of a burr, thereby successfully eliminating the false alarm fault in antenna-servo system of the CIN- RAD/SA radar of Shanwei.
基金supported financially by the Ministerio de Ciencia e Innovación(Spain)and the European Regional Development Fund under the Research Grant WindSound Project(Ref.:PID2021-125278OB-I00).
文摘Maintenance operations have a critical influence on power gen-eration by wind turbines(WT).Advanced algorithms must analyze large volume of data from condition monitoring systems(CMS)to determine the actual working conditions and avoid false alarms.This paper proposes different support vector machine(SVM)algorithms for the prediction and detection of false alarms.K-Fold cross-validation(CV)is applied to evaluate the classification reliability of these algorithms.Supervisory Control and Data Acquisition(SCADA)data from an operating WT are applied to test the proposed approach.The results from the quadratic SVM showed an accuracy rate of 98.6%.Misclassifications from the confusion matrix,alarm log and maintenance records are analyzed to obtain quantitative information and determine if it is a false alarm.The classifier reduces the number of false alarms called misclassifications by 25%.These results demonstrate that the proposed approach presents high reliability and accuracy in false alarm identification.
文摘Diagnosing intermittent fault is an important approach to reduce built-in test（BIT） false alarms. Aiming at solving the shortcoming of the present diagnostic method of intermittent fault, and according to the merit of support vector machines （ SVM） which can be trained with a small-sample, an SVM-based diagnostic model of 3 states that include OK state, intermittent state and faulty state is presented. With the features based on the reflection coefficients of an alarm rate （ AR ） model extracted from small vibration samples, these models are trained to diagnose intermittent faults. The experimental results show that this method can diagnose multiple intermittent faults accurately with small training samples and BIT false alarms are reduced.
文摘Carbon monoxide can cause serious illness or even death if the functionality of smoke alarms fails in the residential home and, in fact, more than 350 persons die every year due to the leak of carbon monoxide. However, vulnerabilities and threats to smoke/CO alarms have not been well-studied. In this paper, through interconnect, a power replay attack has been studied in order to trigger a false alarm. The experimental results demonstrate the smoke alarm can be manipulated. This paper also concentrates on providing a sequence of security methods to defend the smoke alarm system. In future, how to protect smart detectors against attacks will be studied as this can force them to leave high-quality mode of operations.
基金Youth Foundation of National Natural Science Foundation of China (No. 52204020)Distinguished Young Foundation of National Natural Science Foundation of China (No. 52125401).
文摘As oil and gas exploration continues to progress into deeper and unconventional reservoirs,the likelihood of kick risk increases,making kick warning a critical factor in ensuring drilling safety and efficiency.Due to the scarcity of kick samples,traditional supervised models perform poorly,and significant fluctuations in field data lead to high false alarm rates.This study proposes an unsupervised graph autoencoder(GAE)-based kick warning method,which effectively reduces false alarms by eliminating the influence of field engineer operations and incorporating real-time model updates.The method utilizes the GAE model to process time-series data during drilling,accurately identifying kick risk while overcoming challenges related to small sample sizes and missing features.To further reduce false alarms,the weighted dynamic time warping(WDTW)algorithm is introduced to identify fluctuations in logging data caused by field engineer operations during drilling,with real-time updates applied to prevent normal conditions from being misclassified as kick risk.Experimental results show that the GAE-based kick warning method achieves an accuracy of 92.7%and significantly reduces the false alarm rate.The GAE model continues to operate effectively even under conditions of missing features and issues kick warnings 4 min earlier than field engineers,demonstrating its high sensitivity and robustness.After integrating the WDTW algorithm and real-time updates,the false alarm rate is reduced from 17.3%to 5.6%,further improving the accuracy of kick warnings.The proposed method provides an efficient and reliable approach for kick warning in drilling operations,offering strong practical value and technical support for the intelligent management of future drilling operations.
基金financially supported by the National Natural Science Foundation of China(Nos.62275244,62375258,62225507,U2033211,62175230,and 62175232)the CAS Project for Young Scientists in Basic Research(No.YSBR-065)+2 种基金Scientific Instrument Developing Project of the Chinese Academy of Sciences(No.YJKYYQ20200001)National Key R&D Program of China(No.2022YFB3607800,No.2022YFB3605800,and No.2022YFB4601501)Key Program of the Chinese Academy of Sciences(ZDBS-ZRKJZ-TLC018)。
文摘The intrusion of obstacles onto railway tracks presents a significant threat to train safety,characterized by sudden and unpredictable occurrences.With China leading the world in high-speed rail mileage,ensuring railway security is paramount.The current laser monitoring technologies suffer from high false alarm rates and unreliable intrusion identification.This study addresses these issues by investigating high-resolution laser monitoring technology for railway obstacles,focusing on key parameters such as monitoring range and resolution.We propose an enhanced non-uniform laser scanning method,developing a laser monitoring system that reduces the obstacle false alarm rate to 2.00%,significantly lower than the 20%standard(TJ/GW135-2015).This rate is the best record for laser monitoring systems on China Railway.Our system operates seamlessly in all weather conditions,providing superior accuracy,resolution,and identification efficiency.It is the only 3D LiDAR system certified by the China State Railway Group Co.,Ltd.(Certificate No.[2023]008).Over three years,our system has been deployed at numerous points along various lines managed by the China State Railway Group,accumulating a dataset of 300,000 observations.This extensive deployment has significantly enhanced railway safety.The development and implementation of our railway laser monitoring system represent a substantial advancement in railway safety technology.Its low false alarm rate(2.00%),high accuracy(20 cm×20 cm×20 cm),and robust performance in diverse conditions underscore its potential for widespread adoption,promising to enhance railway safety in China and internationally.
基金The National Science and Technology Major Project( No. 2011ZX03005-004-03)the National Natural Science Foundation of China ( No. 61171081, 60872004 )the Natural Science Foundation of Guangxi Province ( No. 2011GXNSFB018075)
文摘A novel spectrum hole detection mechanism is proposed to improve the detection probability in cognitive radio networks for several typical scenarios. By removing the influence of the spatial false alarm （SFA）, the spectrum hole detection probability of the secondary user under path loss and multi-path fading is derived. Meanwhile, the spectrum hole detection probability of multi-users cooperative sensing and that of single-user sensing in multi-bands are derived for comparison. Theoretical analyses and simulation results show that the spectrum hole detection probability of the proposed mechanism is inversely proportional to the sampling times and the area of the sensing region. The detection performance of the multi-users sensing is better than that of single-user sensing when with the AND ~ogic fusion rule but worse when with the OR logic fusion rule. The detection probability is further decreased in the Rayleigh fading channel but it is greatly increased in multi-bands.
基金The National Natural Science Foundation of China(No.61271204)the National Key Technology R&D Program during the 12th Five-Year Plan Period(No.2012BAH15B00)
文摘Unlike the existing resonance region radar systems （RRRS ） that transmit the orthogonal frequency division multiplexing （OFDM）multi-carrier waveform,the dense multi-carrier （DMC）radar waveform which has a narrower frequency interval than the traditional OFDM waveform is proposed.Therefore,in the same frequency bandwidth,the DMC waveform contains more sub-carriers and provides more frequency diversity.Additionally,to further improve detection performance,a novel optimal weight accumulation target detection （OWATD）method is proposed,where the echo electromagnetic waves at different frequencies are accumulated with the optimal weight coefficients.Then,with the signal-to-noise ratio （SNR）of echo waveform approaching infinity,the asymptotic detection performance is analyzed, and the condition that the OWATD method with the DMC outperforms the matched filter with the OFDM is presented.Simulation results show that the DMC outperforms the OFDM in the target detection performance,and the OWATD method can further improve the detection performance of the traditional methods with both the OFDM and DMC radar waveform.
基金co-supported by National Natural Science Foundation of China (No. 51175502)National Defence Pre-research Foundation (No. 9140A17060411KG01)
文摘Associating environmental stresses （ESs） with built-in test （BIT） output is an important means to help diagnose intermittent faults （IFs）. Aiming at low efficiency in association of traditional time stress measurement device （TSMD）, an association model is built. Thereafter, a novel approach is given to evaluate the integrated environmental stress （IES） level. Firstly, the selection principle and approach of main environmental stresses （MESs） and key characteristic parameters （KCPs） are presented based on fault mode, mechanism, and ESs analysis （FMMEA）. Secondly, reference stress events （RSEs） are constructed by dividing IES into three stress levels according to its impact on faults; and then the association model between integrated environmental stress event （IESE） and BIT output is built. Thirdly, an interval grey association approach to evaluate IES level is proposed due to the interval number of IES value. Consequently, the association output can be obtained as well. Finally, a case study is presented to demonstrate the proposed approach. Results show the proposed model and approach are effective and feasible. This approach can be used to guide ESs measure, record, and association. It is well suited for on-line assistant diagnosis of faults, especially IFs.
基金supported by the National Natural Science Foundation of China(61172138)the Natural Science Basic Research Plan in Shaanxi Province of China(2013JQ8040)+1 种基金the Fundamental Research Funds for the Central Universities(K5051302015K5051302040)
文摘For global navigation satellite system （GNSS） signals in Gaussian and Rayleigh fading channel, a novel signal detection algorithm is proposed. Under the low frequency uncertainty case, after performing discrete cosine transform （DCT） to the outputs of the partial matched filter （PMF） for every antenna, the high order com- ponents in the transforming domain will be filtered, then the equalgain （EG） combination for the inverse discrete cosine transform （IDCT） reconstructed signal would be done subsequently. Thus, due to the different frequency distribution characteristics between the noise and signals, after EG combination, the energy of signals has almost no loss and the noise energy is greatly reduced. The theoretical analysis and simulation results show that the detection algorithm can effectively improve the signal-to-noise ratio of the captured signal and increase the probability of detection under the same false alarm probability. In addition, it should be pointed out that this method can also be applied to Rayleigh fading channels with moving antenna.
基金Project 50674093 supported by the National Natural Science Foundation of China
文摘In order to eliminate false alarms,issued by gas sensors in coal mining,caused by Electromagnetic Interference(EMI),both computer simulation and field measurements were introduced to analyze the underground EMI distribution.A simplified model of a sensor with metal enclosure was established and the effects of shielding properties about the enclosure aperture were studied.Because the haulage motor is the moving EMI source,varying with time,the onsite flameproof measuring instruments cannot accomplish synchronous measurements of electromagnetic field vectors.To simplify the field measurements,two sensors,one with a lead and the other without a lead,were chosen to conduct the contrasting measurements.The EMI current caused by the perforation lead was comparatively strong and therefore nickel zinc ferrite beads were used to cut off the EMI propagation paths.The peak value of the interference current was reduced by 20%-70% with the beads.After switching on the sensor power,the sen-sors still occasionally gave false alarms when the switch of nearby large-scale electric equipment was operated.A complex EMI filter was used and the EMI attenuated markedly.The running results demonstrated that false alarms had been eliminated.We con-clude that the improved shielding and filtering are highly significant in enhancing the immunity of the gas sensor.
基金supported by the National Natural Science Foundation of China(61102158)the China Postdoctoral Science Foundation(2011M500667)
文摘A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homogeneity in CFAR reference windows is indicated by a VI-CFAR detector, a switching- CFAR detector is introduced to optimize the performance of the VI-CFAR detector in homogeneous, multiple targets and clutter edge backgrounds. The structure and parameters selection method of the SVI-CFAR detector is presented. Comparisons with classic CFAR detectors and recently proposed detectors are also given. Theoretical analysis and simulation results show that SVICFAR detector maintains the good performance of the VI-CFAR detector in homogeneous and clutter edge backgrounds, while greatly improving the capacity of anti-multi targets.
基金supported by the National Natural Science Foundation of China(609250056110216961501505)
文摘A novel adaptive detector for airborne radar space-time adaptive detection （STAD） in partially homogeneous environments is proposed. The novel detector combines the numerically stable Krylov subspace technique and diagonal loading technique, and it uses the framework of the adaptive coherence estimator （ACE）. It can effectively detect a target with low sample support. Compared with its natural competitors, the novel detector has higher proba- bility of detection （PD）, especially when the number of the training data is low. Moreover, it is shown to be practically constant false alarm rate （CFAR）.
基金This work was supported by the science and technology project of State Grid Shanghai Municipal Electric Power Company(No.52090020007F)National Key R&D Program of China(2017YFB0902800).
文摘Acoustic array sensor device for partial discharge detection is widely used in power equipment inspection with the advantages of non-contact and precise positioning compared with partial discharge detection methods such as ultrasonic method and pulse current method.However,due to the sensitivity of the acoustic array sensor and the influence of the equipment operation site interference,the acoustic array sensor device for partial discharge type diagnosis by phase resolved partial discharge(PRPD)map might occasionally presents incorrect results,thus affecting the power equipment operation and maintenance strategy.The acoustic array sensor detection device for power equipment developed in this paper applies the array design model of equal-area multi-arm spiral with machine learning fast fourier transform clean(FFT-CLEAN)sound source localization identification algorithm to avoid the interference factors in the noise acquisition system using a single microphone and conventional beam forming algorithm,improves the spatial resolution of the acoustic array sensor device,and proposes an acoustic array sensor device based on the acoustic spectrogram.The analysis and diagnosis method of discharge type of acoustic array sensor device can effectively reduce the system misjudgment caused by factors such as the resolution of the acoustic imaging device and the time domain pulse of the digital signal,and reduce the false alarm rate of the acoustic array sensor device.The proposed method is tested by selecting power cables as the object,and its effectiveness is proved by laboratory verification and field verification.
基金National Natural Foundation of China (No.60421002, No.70471052)
文摘Chemical process variables are always driven by random noise and disturbances. The closed-loop con-trol yields process measurements that are auto and cross correlated. The influence of auto and cross correlations on statistical process control (SPC) is investigated in detail by Monte Carlo experiments. It is revealed that in the sense of average performance, the false alarms rates (FAR) of principal component analysis (PCA), dynamic PCA are not affected by the time-series structures of process variables. Nevertheless, non-independent identical distribution will cause the actual FAR to deviate from its theoretic value apparently and result in unexpected consecutive false alarms for normal operating process. Dynamic PCA and ARMA-PCA are demonstrated to be inefficient to remove the influences of auto and cross correlations. Subspace identification-based PCA (SI-PCA) is proposed to improve the monitoring of dynamic processes. Through state space modeling, SI-PCA can remove the auto and cross corre-lations efficiently and avoid consecutive false alarms. Synthetic Monte Carlo experiments and the application in Tennessee Eastman challenge process illustrate the advantages of the proposed approach.
基金supported by the National Natural Science Foundation of China (40871157 41171317)the Foundation of Advance Research of Science and Technology for Chinese National Defence(9140C620201902)
文摘A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the clutter PDF in the reference window are estimated by the non-parametric density estimation. The target detector is defined as the mean square error （MSE） distance between the two PDFs. The CFAR detection in SAR images having multiplicative noise is achieved by adaptive kernel bandwidth proportional to the clutter level. In addition, for obtaining a threshold with respect to a given probability of false alarm （PFA）, an unsupervised null distribution fitting method with outlier rejection is proposed. The effectiveness of the proposed target detector is demonstrated by the experiment result using the RADATSAT-2 SAR image.
基金supported by National Natural Science Foundation of China(No.61074065)Natural Science Foundation of Hebei Province(No.F2012203184)Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20111333120009)
文摘Quantized fault detection for sensor/actuator faults of networked control systems （NCSs） with time delays both in the sensor-to-controller channel and controller-to-actuator channel is concerned in this paper. A fault model is set up based on the possible cases of sensor/atuator faults. Then, the model predictive control is used to compensate the time delay. When the sensors and actuators are healthy, an H stability criterion of the state predictive observer is obtained in terms of linear matrix inequality. A new threshold computational method that conforms to the actual situation is proposed. Then, the thresholds of the false alarm rate （FAR） and miss detection rate （MDR） are presented by using our proposed method, which are also compared with the ones given in the existin~ literatures. Finally, some numerical simulations are shown to demonstrate the effectiveness of the proposed method.
