Deliverables On-line sensors for SBR's GRADIENT has designed an on-line spectrophotometer, based the results of the off-line device obtained in the six previous months. It was built by the Secomam company and called STAC. After some calibration and validation assays, it was integrated for the on-line monitoring system of the SBR at the INRA in Narbonne. POLIMI has developed five titrimetric pH-stat and pH/DO-stat procedures (MODEs) for the evaluation of fundamental parameters related to both the nitrification and denitrification processes. All MODEs were experimentally validated by using the off-line titrator (MARTINA, developed in cooperation with ENEA) on sludge samples drawn from the lab-scale POLINI-SBR. Then, in cooperation with SPES, these procedures were implemented on the on-line titrator (TITAAN), which was first tested and debugged on the pilot-scale ENEA-SBR and then shipped to Narbonne to be integrated in the monitoring system of the pilot-scale INRA-SBR. Model-based software sensors for SBR's The developed software sensors are concerned with the on-line estimation of substrate and biomass concentrations from the on-line measurements of dissolved oxygen and nitrogen oxide in presence of uncertainty in the kinetics. New calibration methods based on an ITSE (Integral of the Time-weighted Squared Error of the state observation) for the software sensors have been developed that have been tested in numerical simulations and with real-life data before being implemented in the integrated supervision and control system. Event-driven control strategies for SBR's This result is concerned with the design and implementation of sub-optimal controllers called ED-TOC (Event-driven Time Optimal Control). The control strategies provided tools to minimize the reaction time and ensure high purification performances. In a second step, it allowed to increase the wastewater volume treated within a time interval. The increase of the loading rate was taken into account as constraint in order to maintain good biological activities for nutriment removal and a good settling capacity for the sludge. This last point is important in order to guarantee an optimal separation of the purified water and the biomass. The control software developed (BIOREC, acronym for BIOREeactor Control) was modified (rewritten) in order to comply with the different system specifications. The goal was to provide capabilities for integration, i.e. for using the same control software in different hardware platforms and in different high level software configurations. The ED-TOC exhibited a reliable suboptimal behaviour and long-term biological stability. Results were validated both in lab-scale and field-scale reactors for 4CP. ED-TOC�s robustness to shock loads disturbances, up to 20 times the standard load, was observed while still maintaining a suboptimal operation. The comparative analysis of the ED-TOC versus FTC shows an increase of 63% to 90% in applicable daily load, and savings in energy and in consumed air in the range of 25% to 39%. Modularity and integrability were also obtained in the controller�s hardware and software. Optimal control strategies for SBR's The objective of the control system developed in Narbonne was to design an algorithm able to drive any initial condition to a final target in a minimal time. More specifically, it is related with the development of a time optimal control strategy for the control of a batch reactor working in two modes: aerobic and anoxic. The challenge was to find the switching instants of a predefined control sequence {aerobic-anoxic-aerobic} and maintain a high nitrification and carbon removal activities. The control strategies provided tools to minimize the reaction time and ensure high purification performances. In a second step, it allowed to increase the wastewater volume treated within a time interval. The increase of the loading rate was taken into account as constraint in order to maintain good biological activities for nutriment removal and a good settling capacity for the sludge. This last point is important in order to guarantee an optimal separation of the purified water and the biomass. Supervision and control system for SBR's The EOLI supervision and control system was tested and validated at the two pilot SBR plants engaged in the project: the one located at the INRA facilities and the other one provided by the ENEA and located at the site of a full scale plant. Both plants were equipped with the EOLI hardware and software main frame. With the aim to validate the EOLI system under other architectures for the integration different from the one developed in the project, UNAM and UU own systems for the monitoring and control have been modified in order to adapt them to run and to test some EOLI software modules at two lab plants (UU) and at the full scale plant built up by IBTech, sending the data to the EOLI remote server. The EOLI remote control centre consists therefore of the lab and pilot scale plants enrolled in the EOLI system, i.e. both lab plants at UU, two pilot plants (one at INRA and one at ENEA), and one full scale plant at IBTech in Mexico. The data from these plants are available at the remote server. The whole integrated system produced at the end of the project is characterised by a high level of modularity pursued for the integration that makes it possible to configure, to enrol, to enable or to disable all the possibly numerous components. Therefore the system can be applied at plant of different size, under different sensors network configurations. The experience from the installation, running and maintenance at two different pilot plants, the ENEA and the INRA ones, confirm this result. The full customisability, that was a key requirement for the development of the system, is a consequence of this high and reliable modularity. The core, both at the remote control centre and at the local plant, is a relational database and it is used to store all the data gathered (measurements), generated (commands), transferred and managed by the EOLI system. At the local plant level, the main frame software is organized in modules. Software modules can be enrolled into the system to implement features and functionalities. The EOLI software architecture is based on the client/server technology in which different modules implemented for different purposes, can share the same resources using a relational database management system (DBMS) that is introduced to replace the limitations of the file sharing architecture: the client/server technology is a versatile, message-based and modular infrastructure that is intended to improve usability, flexibility, interoperability and scalability. Supervision system for SBR's Within the framework of the project, the local database in at the INRA, Narbonne, France while the decentralized one is at SPES location, Fabriano, Italy. The supervision system is supposed to act on the long term, the immediate decision and optimal functioning being, by definition, left to the control system (cf. WP5). The role of the supervision system is thus rather to decide on the long term if the actual control algorithm works well. The decision was then taken to analyse the state of the system with one cycle delay: at the instant t, we analyse the last cycle, which is already finished. In addition, our attention was focused on the part of a total cycle period, which includes the maximum of information, that is the aerobic period of the SBR cycle. Given these predefined objectives, two different systems were developed depending on the available sensors: - Case 1: a Decision Support System (DSS) for a configuration involving a low instrumentation process - Case 2: a DSS for a configuration involving a process equipped with an advanced instrumentation For the low instrumentation configuration, two subcases were investigated : - Case 1.1: model-based approach - Case 1.2: databased approach. Fault detection and isolation system for SBR's The results take into account the following tasks : to get a redundancy relation which is necessary to solve a FDI issue with analytical methods; to establish the causal model for the POLIMI reactor, participants of WP6 established a communication with POLIMI; to propose together with POLIMI a possible solution to the excessive nitrite outflow problem. To the diagnosis of faults in the DOx sensor the procedure was tested by simulation changing the parameter associated to the thickness to emulate a fouling membrane. The simulator used for the test includes a screen in which the operator can be trained how the detector must be managed. The results shown that temperature disturbances and sporadic sensor calibration affect the accuracy of the diagnosis; systematic test at the same environmental conditions are suggested. The disadvantage of this design is the addition of specific electronic hardware in the device for each market devise and that the operator has to select manually when the test is carried out. The validation of the detector of faults in the servo-valve was made using the data available by the DAMADICS project for the 3 considered faults. In all the cases the on-line adaptive standardization of data reduced the false alarms and yielded a satisfactory performance as fault detector. To test the classification methods using the respiration, a comparison of the diagnosis results by simulation for three sets of classes was made and shown that the percentage of correct diagnosis is above 95% for all tested cases indicating that the features contain enough system information for the diagnosis and then both classifiers achieve satisfactory performance. The code of the system in MATLAB software is available in the annex. The experiments related to the nitrites build up issue show that diverse situations can produce this abnormal condition. Then a simple monitoring system is recommended which evaluates the corresponding process signals and indicates the operator if some of the conditions that could cause nitrite build-up occur. Validated dynamical models of SBR'S Two different models have been selected in order to capture the dynamics of the involved processes in the most general way. These have been called EM1 and EM2, and are related to one substrate removal case (UNAM process) and the case involving nitrifying/denitrifying activities (other partners processes), respectively. UCL, INRA and UNAM have been working on the parameter identification based on two selected models by using the data provided by the experiments, and validated models are available for the different processes. The identification has been performed by the UCL in conjunction with INRA and UNAM. The complete identification results includes calibration and validation of the parameter identification, statistical analysis of the obtained results via the computation of the confidence intervals for each parameters, as well as an detailed sensitivity of the model parameters and an exhaustive simulation study. Searching for OpenAIRE data... There was an error trying to search data from OpenAIRE No results available
