Data-driven intelligent monitoring system for key variables in wastewater treatment process

In wastewater treatment process(WWTP), the accurate and real-time monitoring values of key variables are crucial for the operational strategies. However, most of the existing methods have difficulty in obtaining the real-time values of some key variables in the process. In order to handle this issue, a data-driven intelligent monitoring system, using the soft sensor technique and data distribution service, is developed to monitor the concentrations of effluent total phosphorous(TP) and ammonia nitrogen(NH_4-N). In this intelligent monitoring system, a fuzzy neural network(FNN) is applied for designing the soft sensor model, and a principal component analysis(PCA) method is used to select the input variables of the soft sensor model. Moreover, data transfer software is exploited to insert the soft sensor technique to the supervisory control and data acquisition(SCADA) system. Finally, this proposed intelligent monitoring system is tested in several real plants to demonstrate the reliability and effectiveness of the monitoring performance.

Online Predictive Monitoring and Prediction Model for a Periodic Process Through Multiway Non-Gaussian Modeling

A new on-line predictive monitoring and prediction model for periodic biological processes is proposed using the multiway non-Gaussian modeling. The basic idea of this approach is to use multiway non-Gaussian modeling to extract some dominant key components from daily normal operation data in a periodic process, and subsequently combining these components with predictive statistical process monitoring techniques. The proposed predictive monitoring method has been applied to fault detection and diagnosis in the biological wastewater-treatment process, which is based on strong diurnal characteristics. The results show the power and advantages of the proposed predictive monitoring of a continuous process using the multiway predictive monitoring concept, which is thus able to give very useful conceptual results for a daily monitoring process and also enables a more rapid detection of the process fault than other traditional monitoring methods.

Comparison of heavy metal removal efficiencies in four activated sludge processes

The removal efficiencies of heavy metals(As, Cr, Cu, Ni, Pb and Zn) were investigated in the 17 operating municipal wastewater treatment plants(WWTPs) and compared with those in four main activated sludge processes. Significant differences of heavy metal removal efficiencies were observed among four activated sludge processes. The removal efficiency for As(75.5%) in the oxidation ditch(OD) process is significantly higher than that in the conventional activated sludge(CAS) process(38.6%) or sequencing batch reactor(SBR) process(51.4%). The mean removal efficiencies for Cu and Ni in the OD process are 90.5% and 46.7%, respectively, while low mean removal efficiencies are observed for Cu(69.9%) and Ni(16.5%), respectively, in the SBR process. The removal efficiencies for Cu and Ni in the OD process are significantly higher than those in the anaerobic-anoxic-oxic(A2-O) process. These results highlight the differences of removal efficiencies for heavy metals in different processes and should be considered when selecting a wastewater treatment process.

A modified active disturbance rejection control for a wastewater treatment process

Waste water treatment process(WWTP)control has been attracting more and more attention.However,various undesired factors,such as disturbance,uncertainties,and strong nonlinear couplings,propose big challenges to the control of a WWTP.In order to improve the control performance of the closed-loop system and guarantee the discharge requirements of the effluent quality,rather than take the model dependent control approaches,an active disturbance rejection control(ADRC)is utilized.Based on the control signal and system output,a phase optimized ADRC(POADRC)is designed to control the dissolved oxygen and nitrate concentration in a WWTP.The phase advantage of the phase optimized extended state observer(POESO),convergence of the POESO,and stability of the closed-loop system are analyzed from the theoretical point of view.Finally,a commonly accepted benchmark simulation model no.1.(BSM1)is utilized to test the POESO and POADRC.Linear active disturbance rejection control(LADRC)and the suggested proportion-integration(PI)control are taken to make a comparative research.Both system responses and performance index values confirm the advantage of the POADRC over the LADRC and the suggested PI control.Numerical results show that,as a result of the leading phase of the total disturbance estimation,the POESO based POADRC is an effective and promising way to control the dissolved oxygen and nitrate concentration so as to ensure the effluent quality of a WWTP.

Improved SDT Process Data Compression Algorithm

Process data compression and trending are essential for improving control system performances. Swing Door Trending (SDT) algorithm is well designed to adapt the process trend while retaining the merit of simplicity. But it cannot handle outliers and adapt to the fluctuations of actual data. An Improved SDT (ISDT) algorithm is proposed in this paper. The effectiveness and applicability of the ISDT algorithm are demonstrated by computations on both synthetic and real process data. By applying an adaptive recording limit as well as outliers-detecting rules, a higher compression ratio is achieved and outliers are identified and eliminated. The fidelity of the algorithm is also improved. It can be used both in online and batch mode, and integrated into existing software packages without change.

Mutagenic and Estrogenic Effects of Organic Compounds in Water Treated by Different Processes: A Pilot Study

Objective In this study, a pilot-scale investigation was conducted to examine and compare the biotoxicity of the organic compounds in effluents from five treatment processes (P1-P5) where each process was combination of preoxidation (O3), coagulation, sedimentation, sand filtration, ozonation, granular activated carbon, biological activated carbon and chlorination (NaClO). Methods Organic compounds were extracted by XAD-2 resins and eluted with acetone and dichlormethane (DCM). The eluents were evaporated and redissolved with DMSO or DCM. The mutagenicity and estrogenicity of the extracts were assayed with the Ames test and yeast estrogen screen (YES assay), respectively. The organic compounds were detected by GC-MS. Results The results indicated that the mutation ratio (MR) of organic compounds in source water was higher than that for treated water. GC-MS showed that more than 48 organic compounds were identified in all samples and that treated water had significantly fewer types and concentrations of organic compounds than source water. Conclusion To different extents, all water treatment processes could reduce both the mutagenicity and estrogenicity, relative to source water. P2, P3, and P5 reduced mutagenicity more effectively, while P1 reduced estrogenicity, most effectively. Water treatment processes in this pilot plant had weak abilities to remove Di-n-butyl phthalate or 1, 2-Benzene dicarboxylic acid.

Protective Effects of Six PPTs on Hypoxia/Reoxygenation Induced Cardiomyocyte Injury by Different Treatments

[Objectives]To detect the protective effects of six protopanaxatriols(PPTs)on hypoxia/reoxygenation(H/R)induced cardiomyocyte injury by different treatments.[Methods]The 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide(MTT)assay was used for detecting the protective effects of six PPTs including ginsenoside Rg1,Re,Rf,Rg2,(R)Rh1 and(S)Rh1 on cell viability reduced by H/R in different treatments.And the adenosine triphosphate(ATP)content and mitochondrial membrane potential(MMP)were used for detecting the mitochondrial function change during PPTs treatment.[Results]Among six PPTs,ginsenoside Rg1,Re,Rf,Rg2 and(R)Rh1 at the concentration of 12.5μM significantly increased the cell survival when treated before and during H/R.These five PPTs also significantly increased the ATP content and MMP reduced by H/R in the same manner.In comparison,only Rg1 significantly increased the cell viability compared with H/R group by pretreating and treating the cells during hypoxia process.[Conclusions]Different treatments affect the protective effects of PPTs.When treated before and during H/R,ginsenoside Rg1,Re,Rf,Rg2 and(R)Rh1 protect the cardiomyocyte against H/R injury mitochondrial function,and only ginsenoside Rg1 has protective effects when treated before and during hypoxia process.

Mutagenicity and Genotoxicity of Organic Extracts from Finished Water with Different Treatment Process

Purification of surface water is widely practiced with conventional water treatment processes like coagulation-flocculation, sedimentation, filtration,and disinfection. Some reports have specified that conventional wastewater purification processes do not effectively remove many chemical contaminants,

Posterior articular process approach for the treatment of upper lumbar disc herniation

Objective To investigate the feasibility and surgical effects of posterior articular process approach for the treatment of L1-L3 lumbar disc herniation.Methods A retrospective study,of17patients with upper lumbar intervertebml disc

ANALYSIS AND IMPROVEMENT ON LANDFILL LEACHATE TREATMENT PROCESS OF MUNICIPAL SOLID WASTE

According to different mechanism of microbial degradation of organics, this article divided the treatment processes of garbage landfill into four kinds, analyzed each kind of the treatment leachate process and presented a better improved process. (Author abstract) 4 Refs.

Multi-timescale feature extraction method of wastewater treatment process based on adaptive entropy

In wastewater treatment systems,extracting meaningful features from process data is essential for effective monitoring and control.However,the multi-time scale data generated by different sampling frequencies pose a challenge to accurately extract features.To solve this issue,a multi-timescale feature extraction method based on adaptive entropy is proposed.Firstly,the expert knowledge graph is constructed by analyzing the characteristics of wastewater components and water quality data,which can illustrate various water quality parameters and the network of relationships among them.Secondly,multiscale entropy analysis is used to investigate the inherent multi-timescale patterns of water quality data in depth,which enables us to minimize information loss while uniformly optimizing the timescale.Thirdly,we harness partial least squares for feature extraction,resulting in an enhanced representation of sample data and the iterative enhancement of our expert knowledge graph.The experimental results show that the multi-timescale feature extraction algorithm can enhance the representation of water quality data and improve monitoring capabilities.

疫情期间非定点医院急诊管理的实践与思考

基于危机管理4R理论进行文献检索,结合医院的实际情况梳理管理难点,制定疫情期间非定点救治综合医院的急诊管理策略和流程。从急诊管理的组织架构、空间划分、诊疗流程、人员管理、院感防控、志愿服务等环节完善优化急诊管理流程,并在具体应用过程中不断调整。2022年3月28日-6月1日上海本轮疫情期间,复旦大学附属中山医院多次单日急诊接诊量超1000人,抢救室留观患者170余人,接诊救护车100余辆。2022年1-4月救护车接诊总量位列上海市第一。疫情期间中山医院在遵守上级部门不同阶段疫情防控相关要求的同时,优化急诊管理策略和流程,很好地保障和满足了急诊患者的就医需求。

Methods for Improving Volume Stability of Steel Slag as Fine Aggregate

Suitable methods for enhancing the volume stability of steel slag utilized as fine aggregate were determined. The effects of steam treatment at 100 ℃ and autoclave treatment under 2.0 MPa on the soundness of steel slag sand were investigated by means of powder ratio, linear expansion, compressive and flexural strength. DTA, EDX, XRD and ethylene glycol methods were employed to analyze both the treated slags and susceptible expansion grains. Experimental results indicate that powder ratio, content of free lime and rate of linear expansion can express the improvement in volume stability of different treated methods. Steam treatment process cannot ultimately prevent specimens from cracking and decrease of strength, but mortar made from autoclave treated slag keeps integration subjected to hot water of 80℃ until 28 d and its strength do not show significant decrement. The hydration of over-burn free lime and periclase phase are the main cause for the disintegration or crack of untreated and steam treated steel slag＇s specimens. Autoclave treatment process is more effective than steam treatment process on enhancement of volume stability of steel slag.

Modeling of Energy Consumption and Effluent Quality Using Density Peaks-based Adaptive Fuzzy Neural Network

Modeling of energy consumption(EC) and effluent quality(EQ) are very essential problems that need to be solved for the multiobjective optimal control in the wastewater treatment process(WWTP). To address this issue, a density peaks-based adaptive fuzzy neural network(DP-AFNN) is proposed in this study. To obtain suitable fuzzy rules, a DP-based clustering method is applied to fit the cluster centers to process nonlinearity.The parameters of the extracted fuzzy rules are fine-tuned based on the improved Levenberg-Marquardt algorithm during the training process. Furthermore, the analysis of convergence is performed to guarantee the successful application of the DPAFNN. Finally, the proposed DP-AFNN is utilized to develop the models of EC and EQ in the WWTP. The experimental results show that the proposed DP-AFNN can achieve fast convergence speed and high prediction accuracy in comparison with some existing methods.

A sludge volume index (SVI) model based on the multivariate local quadratic polynomial regression method

In this study, a multivariate local quadratic polynomial regression(MLQPR) method is proposed to design a model for the sludge volume index(SVI). In MLQPR, a quadratic polynomial regression function is established to describe the relationship between SVI and the relative variables, and the important terms of the quadratic polynomial regression function are determined by the significant test of the corresponding coefficients. Moreover, a local estimation method is introduced to adjust the weights of the quadratic polynomial regression function to improve the model accuracy. Finally, the proposed method is applied to predict the SVI values in a real wastewater treatment process(WWTP). The experimental results demonstrate that the proposed MLQPR method has faster testing speed and more accurate results than some existing methods.

A data-derived soft-sensor method for monitoring effluent total phosphorus

The effluent total phosphorus(ETP) is an important parameter to evaluate the performance of wastewater treatment process(WWTP). In this study, a novel method, using a data-derived soft-sensor method, is proposed to obtain the reliable values of ETP online. First, a partial least square(PLS) method is introduced to select the related secondary variables of ETP based on the experimental data. Second, a radial basis function neural network(RBFNN) is developed to identify the relationship between the related secondary variables and ETP. This RBFNN easily optimizes the model parameters to improve the generalization ability of the soft-sensor. Finally, a monitoring system, based on the above PLS and RBFNN, named PLS-RBFNN-based soft-sensor system, is developed and tested in a real WWTP. Experimental results show that the proposed monitoring system can obtain the values of ETP online and own better predicting performance than some existing methods.

Air cushion furnace technology for heat treatment of high quality aluminum alloy auto body sheet

The process characteristics of heat treatment of aluminum alloy auto body sheet and the working principle of air cushion furnace were introduced.The process position and irreplaceable role of air cushion furnace in the aluminum alloy auto body sheet production was pointed out after the difficulty and key points in the whole production process of auto body sheet were studied.Then the development process of air cushion furnace line of aluminum alloy sheet was reviewed,summarized and divided to two stages.Based on the research of air cushion furnace,the key technology of it was analyzed,then the key points on process,equipment and control models of air cushion furnace for aluminum alloy auto body sheet in future were put forward.With the rapid development of automotive industry,there will be certainly a new upsurge of research and application of air cushion furnace for heat treatment of aluminum alloy auto body sheet.

Effect of Wet Surface Treated Nano-SiO_2 on Mechanical Properties of Polypropylene Composite

Nano-SiO2/polypropylene composite was prepared by melt-blending process. The nano-SiO2 particles were organized by wet process surface treatment with silane coupling agent KH-570. The effect of mass fraction of nano-SiO2 particles and dosage of KH-570 on the toughening and strengthening of PP matrix were investigated based on the fractography of impact notch and the analysis of crystal structure by X-ray and dispersive structure of nano-SiO2 by TEM. Results show that the impact and flexural strength and modulus of the composite are improved obviously with low loading of nano-SiO2 （3 wt%-5 wt%）, and the izod impact strength of PP increases twice with 4 wt% nano-SiO2. The nano-SiO2 particles treated can disperse into the matrix resin, which has evident heterogeneous nucleation effects on the crystallization of PP. The optimal toughening and strengthening effects of PP matrix can be obtained when the content of nano-SiO2 and KH-570 are 4 wt% and 3 wt%, respectively.

Method for grinding and delaminating muscovite

A method of dry grinding muscovite based on the use of knife-mills is reported.It was possible to produce mica with a particle size below 100 and 45μm.After grinding,the samples were submitted to sonication treatment,which promoted delamination of the material.The particle size distribution shows that sonicated mica has more particles in the size range 10-50μm than does non-sonicated mica have. This also indicates a decrease in the average particle size.Characterization of the treated muscovite by scanning electron microscopy revealed a highly delaminated material with a plate-like structure.The products were characterized by chemical analysis and X-ray diffraction,too.This mica has already been used for the synthesis of pearlescent pigments.

Cost-effective integrated strategy for the fabrication of hard-magnet barium hexaferrite powders from low-grade barite ore

Ultrafine barium hexaferrite（BaFe12O19） powders were synthesized from the metallurgical extracts of low-grade Egyptian barite ore via a co-precipitation route. Hydrometallurgical treatment of barite ore was systematically studied to achieve the maximum dissolution efficiency of Fe（～99.7%） under the optimum conditions. The hexaferrite precursors were obtained by the co-precipitation of BaS produced by the reduction of barite ore with carbon at 1273 K and then dissolved in diluted HCl and FeCl3 solution at pH 10 using NaOH as a base; the product was then annealed at 1273 K in an open atmosphere. The effect of Fe^3＋/Ba^2＋ molar ratio and the addition of hydrogen peroxide（H2O2） on the phase structure, crystallite size, morphology, and magnetic properties were investigated by X-ray diffraction, scanning electron microscopy, and vibrating sample magnetometry. Single-phase BaFe（12）O（19） powder was obtained at an Fe^3＋/Ba^2＋ molar ratio of 8.00. The formed powders exhibited a hexagonal platelet-like structure. Good maximum magnetization（48.3 A×m^2×kg^–1） was achieved in the material prepared at an Fe^3＋/Ba^2＋ molar ratio of 8.0 in the presence of 5% H2O2 as an oxidizer and at 1273 K because of the formation of a uniform, hexagonal-shaped structure.