Biomedical subjects

J Harmand

Publications and source records attributed to J Harmand.

9 recordsLinked to original sources

PubMed2006

On-line supervision and control of an aerobic SBR process.

This paper presents a new software developed in MATLAB for analyzing on-line data of an aerobic SBR, detecting faults and, in this case, proposing the most probable causes of fault. Process diagnosis is achieved using a statistical method divided in two main phases: off-line model building and on-line data diagnosis. The off-line model identifies the correct working conditions of the system (standard operative conditions). It includes the characterization of the deviation of the system from these standard conditions in the case of changing in the biomass properties or carbon and nitrogen load characteristics. The on-line diagnosis aims at collecting and analyzing all the available data available through industrial sensors, and at classifying the behavior of each treatment cycle. The diagnosis performance of the proposed method is tested using a data set of an aerobic SBR pilot plant.

Bacteria, Aerobic↗

PubMed2006

The microbial signature of drinking waters: myth or reality?

This paper presents a new software developed for analyzing single strand conformation polymorphism (SSCP) electrophoresis patterns delivered by the genetic analyzer ABI310 (Applied Biosystems). SSCP is a molecular typing technique based on the PCR amplification of microbial 16S rDNA and used for the monitoring of complex microbial ecosystems dynamics. The software--a home-made MATLAB toolbox called MODIMECO--developed for the analysis of SSCP patterns is presented. MODIMECO includes a number of basic signal processing abilities as well as largely used statistical tools such as the well known principal component analysis. The use of the SSCP for assessing the hypothesis of the existence of a microbial signature of drinking waters illustrates the typical advantages of using such software tools. Results are discussed and conclusions drawn.

DNA, Bacterial↗

PubMed2005

Robust interval-based regulation for anaerobic digestion processes.

A robust regulation law is applied to the stabilization of a class of biochemical reactors exhibiting partially known highly nonlinear dynamic behavior. An uncertain environment with the presence of unknown inputs is considered. Based on some structural and operational conditions, this regulation law is shown to exponentially stabilize the aforementioned bioreactors around a desired set-point. This approach is experimentally applied and validated on a pilot-scale (1 m3) anaerobic digestion process for the treatment of raw industrial wine distillery wastewater where the objective is the regulation of the chemical oxygen demand (COD) by using the dilution rate as the manipulated variable. Despite large disturbances on the input COD and state and parametric uncertainties, this regulation law gave excellent performances leading the output COD towards its set-point and keeping it inside a pre-specified interval.

Bacteria, Anaerobic↗

PubMed2002

Software sensors for highly uncertain WWTPs: a new approach based on interval observers.

This paper presents the practical implementation of a new robust interval observer on a 1 m3 continuous fixed bed anaerobic reactor used for the treatment of industrial wine distillery wastewater. This interval observer is able to generate guaranteed intervals for the unmeasured variables (i.e. acidogenic and methanogenic bacteria, alkalinity and chemical oxygen demand) from few on-line measurements (i.e. input liquid flow rate, CO2 gaseous flow rate, volatile fatty acids and total inorganic carbon). The main advantage of this approach is its independance with respect to disturbances and uncertainty in the initial conditions, in the kinetics and, last but not least, in the process inputs.

Automation↗

PubMed2002

Model based prediction of the clogging of an anaerobic fixed bed reactor.

This paper presents the use of nonlinear constrained optimization techniques in order to detect and evaluate the degree of clogging in an anaerobic fixed bed reactor. First, experimental results show that the validity of a mass balance model can degrade over the time. Using the available model of the process and nonlinear constrained optimization tools, it is established that these changes can be due to the decrease of the liquid volume into the reactor while the mean values of biomass concentrations increase, leading to the clogging of the reactor. These theoretical results are confirmed experimentally in evaluating the hydraulic retention time of the reactor using a tracer.

Anaerobiosis↗

PubMed2002

On-line measurements of COD, TOC, VFA, total and partial alkalinity in anaerobic digestion processes using infra-red ectrometry.

This paper describes the use of a Fourier Transform Infra-Red (FT-IR) spectrometer as an on-line sensor to measure Chemical Oxygen Demand (COD), Total Organic Carbon (TOC), Volatile Fatty Acids (VFA), and Partial and Total Alkalinity (PA and TA) in anaerobic digestion processes for the treatment of industrial wastewaters. Comparison with manual off-line analysis and with an on-line industrial TOC analyser and an on-line titrimetric sensor (for the measurements of VFA, TA and PA) are provided to demonstrate the interest of spectral analysis in the mid infra-red domain for the monitoring of anaerobic digestion processes. In order to further illustrate the advantages of using such a technique, on-line measurements recorded during an accident of the pH regulation in the input (pH in the reactor went above 11 and biomass activity stopped) are shown. They demonstrate that, if carefully performed, the calibration can be extended outside its range while being still compatible with requirements of wastewater treatment processes.

Bacteria, Anaerobic↗

PubMed2001

Software sensor design for COD estimation in an anaerobic fluidized bed reactor.

In this paper, a method for unknown input estimation in stochastic system is presented. A key problem in bioprocess systems is the absence, in some cases, of reliable on-line measurements for real time monitoring applications. In this paper, a software sensor for an anaerobic digester is presented. Unmeasured components of the influent are estimated from available on-line measurements. Unknown input Kalman filter is discussed to estimate the state and unknown input of the process. First, the theory of unknown inputs optimal filtering in the stochastic case is exposed and a design procedure is proposed. The observer is applied to an anaerobic fluidized bed reactor to estimate the variations in Chemical Oxygen Demand (COD) concentration and experimental results are presented.

Anaerobiosis↗

PubMed2001

Advanced monitoring and control of anaerobic wastewater treatment plants: fault detection and isolation.

In this paper, a fault detection and isolation approach using fuzzy logic is described for on-line analysis of problems occurring in anaerobic digestion processes. The measurements available on the process are preprocessed to build a vector of fault residuals indicating the magnitude of the problems. This vector is classified into a prespecified category (i.e., a class) which is a state of the system, according to discrimination fuzzy rules. Three different types of classes were defined in a hierarchical structure: sensors faults, sub-process faults and process faults. This approach was developed to handle in real time both technical and biological problems. Demonstration of the practical interest of this study was made using real life experiments and large improvement of the reliability and safety of the process was obtained, thus optimizing the overall wastewater treatment.

Algorithms↗

PubMed2001

A systematic approach to error isolation in computerized wastewater simulation models.

Activated sludge models are used extensively in the study of wastewater treatment processes. While various commercial implementations of these models are available, there are many people who need to code models themselves using the simulation packages available to them. Quality assurance of such models is difficult. While benchmarking problems have been developed and are available, the comparison of simulation data with that of commercial models leads only to the detection, not the isolation of errors. To identify the errors in the code is time-consuming. In this paper, we address the problem by developing a systematic and largely automated approach to the isolation of coding errors. There are three steps: firstly, possible errors are classified according to their place in the model structure and a feature matrix is established for each class of errors. Secondly, an observer is designed to generate residuals, such that each class of errors imposes a subspace, spanned by its feature matrix, on the residuals. Finally, localising the residuals in a subspace isolates coding errors. The algorithm proved capable of rapidly and reliably isolating a variety of single and simultaneous errors in a case study using the ASM1 activated sludge model. In this paper a newly coded model was verified against a known implementation. The method is also applicable to simultaneous verification of any two independent implementations, hence is useful in commercial model development.

Automation↗