主要论文论著
[1]Chang P*, Meng FC. Fault detection of Urban Wastewater Treatment Process Based on Combination of Deep Information and Transformer Network[J]. IEEE Transactions on Neural Networks and Learning Systems.2024,35(6),8124-8133(中科院分区1区,TOP期刊)
[2]Chang P*,Xu Y,Meng FC and Xiong WL.Fault Detection in Wastewater Treatment Process using Broad Slow Feature Neural Network with Incremental Learning Ability[J]. IEEE Transactions on Industrial Informatics. 2024,20(3):4540-4549.(中科院分区1区,TOP期刊)
[3]Chang P*, Zhang SR and Wang ZC. Soft Sensor of the Key Effluent Index in the Municipal Wastewater Treatment Process Based on Transformer[J].IEEE Transactions on Industrial Informatics, 2024,20(3):4021-4028.(中科院分区1区,TOP期刊)
[4]Chang P*, Xu Y, Hu ZQ.Industrial process monitoring based on Dynamic Overcomplete Broad Learning Network[J]. IEEE Transactions on Neural Networks and Learning Systems. 2024,35(2),1761-1772.(中科院分区1区,TOP期刊)
[5]Chang P*, Xu Ying ,Shi SQ and Fang ZY. Application of non-Gaussian feature enhancement extraction in gated recurrent neural network for fault detection in batch production processes [J]. Expert Systems with Applications, 2024,237(3): 121348.(中科院分区1区,TOP期刊)
[6]Chang P*, Xu Ying and Meng FC. Efficient fault monitoring in wastewater treatment processes with time-stacked broad learning network[J]. Expert Systems with Applications, 2023,233(12): 120958.(中科院分区1区,TOP期刊)
[7]Chang P*, Bao X, Meng FC and Lu RW. Multi-objective Pigeon-inspired Optimized feature enhancement soft-sensing model of Wastewater Treatment Process[J]. Expert Systems With Applications, 2023, 215(4):119193.(中科院分区1区,TOP期刊)
[8]Chang P*, Wang K, Zheng K and Meng FC. Monitoring of wastewater treatment process based on multi-stage variational autoencoder[J]. Expert Systems With Applications, 2022, 207(11):17919.(中科院分区1区,TOP期刊)
[9]Chang P*, Zhang RY and Ding CH. Dynamic hidden variable fuzzy broad neural network based batch process anomaly detection with incremental learning capabilities[J]. Expert Systems With Applications, 2022, 202(9):117390.(中科院分区1区,TOP期刊)
[10]Chang P*, Ding C H. Monitoring multi-domain batch process state based on Fuzzy Broad Learning System[J], Expert Systems With Applications, 2022,187(1):11581.(中科院分区1区,TOP期刊)
[11]Chang P*, Zhao L L, Meng F C and Xu Y. Soft measurement of effluent index in sewage treatment process based on overcomplete broad learning system[J], Applied Soft Computing. 2022, 115(1):108235.(中科院分区2区)
[12]Chang P*, Lu R W. Fault monitoring of batch process based on over complete broad learning network[J]. Engineering Applications of Artificial Intelligence, 2021,99 (3):104139.(中科院分区2区)
[13]Chang P*, Li Z Y. Over-complete deep recurrent neutral network based on wastewater treatment process soft sensor application[J]. Applied Soft Computing.2021,105 (3):107227.(中科院分区2区)
[14]Chang P*, Lu R W and Olivia K. Batch Process Fault Detection for Multi-Stage Broad Learning System [J]. Neural Networks, 2020,129 (9) : 298-312.(中科院分区1区)
[15]Chang P*, Le Z Y and Wang G M,. An effective deep recurrent network with high-order statistic information for fault monitoring in wastewater treatment process[J]. Expert Systems With Applications. 2021,27(10), 114141.(中科院分区1区,TOP期刊)
[16]Chang P*, Wang K. Quality relevant Over-complete Independent Component Analysis Based monitoring for Nonlinear and Non-Gaussian Batch Process[J]. Chemometrics and Intelligent Laboratory Systems, 2020, 205(10),104140.(中科院分区2区)
[17]Chang P*, Olivia K, Ding C H and Lu R W. Application of fault monitoring and diagnosis in process industry based on fourth order moment and singular value decomposition[J]. The Canadian Journal of Chemical Engineering, 2020, 98(3): 717-727.(中科院分区4区)
[18]Chang P*, Qiao J, Lu R W and Zhang X Y. Multiphase batch process monitoring based on higher order cumulant analysis[J]. The Canadian Journal of Chemical Engineering, 2020, 98(2): 513-524.(中科院分区4区)
[19]Chang P*,Ding C H and Zhao Q K. Fault diagnosis of microbial pharmaceutical fermentation process with non-Gaussian and nonlinear coexistence[J]. Chemometrics and Intelligent Laboratory Systems, 2020, 199(4),103931.(中科院分区2区)
[20]Ding C H, Chang P* and Olivia K. Enhanced high order information extraction for multiphase batch process fault monitoring [J]. The Canadian Journal of Chemical Engineering[J], 2020,98(10):2187-2204.(中科院分区4区)
专利(已授权)
(1)常鹏,丁春豪,王普.一种基于模糊宽度自适应学习模型的污水处理过程故障监测方法,2022-08-02,美国专利授权, US011403546B2
(2)常鹏,王凯,王普.一种基于过完备宽度学习模型的污水处理过程故障监测方法, 2023-06-02中国, ZL201911402093.X (专利)
(3)常鹏,卢瑞炜,张祥宇;王普.一种基于子阶段内高阶统计量构建的微生物发酵过程故障监测方法,2023-05-26,中国, ZL201911388480.2 (专利)
(4)常鹏,李泽宇,王普.一种特征自增强的循环神经网络的污水关键水质指标软测量方法,2023-05-02,中国专利授权,ZL201911298640.4 (专利)
(5)常鹏,张祥宇,卢瑞炜,王普.一种基于OICA的复杂工业过程故障监测方法, 2023-05-02,中国专利授权,ZL201910410875.1 (专利)
(6)常鹏,丁春豪,王普.一种基于多阶段OICA的间歇过程故障监测方法,2023-04-25,中国专利授权,ZL201910582671.6 (专利)
(7)王凯,常鹏,李泽宇,丁春豪.一种基于变分自编码器模型的污水处理过程故障监测方法, 2022-10-28,中国专利授权,ZL202011585643.9(专利)
(8)常鹏,卢瑞炜,张祥宇,王普.一种基于改进的多种群全局最优的自适应鸽群优化方法,2022-02-15,中国专利授权,ZL201811381008.1(专利)
(9)常鹏,卢瑞炜,张翔宇,王普.一种基于四阶矩阵奇异值分解的间歇过程故障监测方法,2021-07-02,中国专利授权,ZL201910664867.X(专利)
(10)常鹏,丁春豪,王普.一种基于模糊自适应学习模型的污水处理过程故障监测方法, 2021-02-26,中国专利授权ZL201911225929.3(专利)
(11)王普,卢瑞炜,常鹏,张祥宇.一种基于宽度学习系统的间歇过程故障监测与诊断方法, 2020-08-28,中国, ZL201910136910.5 (专利)