EXPERT SYSTEM FOR DIAGNOSIS & REMEDIATION OF ACTIVATED SLUDGE PROBLEMS BASED ON MICRO

BIOLOGICAL TROUBLE-SHOOTING METHODS

__INDEX____________________________________________

1 Keywords

1.2 Abstract

1.3 Introduction

1.4 Activated Sludge Process and Solid Separation Problems

2 MICROexpert System Structure

2.1 Data Input

2.2 Fuzzy “MQC” Inferential Engine and Knowledge b ase

2.3 Applicability and benefits

2.4 Hardware & Software required

3 Registration

4 New / Open Plant

4.1 Open / Save data

4.2 Menu Edit

5 Sample transport and storage

5.1 Examination Frequency

5.2 Microscopic examination procedure

5.3 Abundance rating

EXPERT SYSTEM FOR DIAGNOSIS & REMEDIATION OF ACTIVATED SLUDGE PROBLEMS

BASED ON MICRO BIOLOGICAL TROUBLE-SHOOTING METHODS

1 KEYWORDS

Activated sludge process, microscopic examination, filamentous bacteria, protozoa, operational parameters, Sludge Biotic Index, solids separation problems, expert system, knowledge base, biological trouble-shooting methods, certainty quantification, fuzzy logic, Fuzzy MQC inferential engine. 1.2 ABSTRACT

A software package MICROexpert, realized with the application of the last generation of expert system technology, has been performed to support the solving of the complex activated sludge problems, in waste water treatment plants. It is mainly based on microscopic examination data related to activated sludge floc structure (filamentous bacteria, protozoa, etc.), and his aim is to reproduce the complex reasoning exhibited by expert biologists getting process failure diagnosis. MICROexpert make use of a last revisions of the results reported in the scientific literature carried out with the collaboration of the Water Research Institute "CNR/Irsa" and "La Sapienza" University of Rome. The new SBI approach (Sludge Biotic Index) is used to define the biological quality of the process, in spite also to a possible availableness of specific physico-chemical parameters. Operational parameters are optionally proposed to confirm the truth of diagnosis, particularly when a problem related to operational conditions occurs. MICROexpert suggests opportune remedies according to the sludge problems just diagnosed, using his knowledge base formed on practical experience and reported studies informations. MICROexpert has been developed on PC / IBM MS-DOS compatible platform. 1.3 INTRODUCTION

To contribute to a more large diffusion of appropriate and cheaper trouble-shooting expert systems in wastewater biological treatment field, and to support opportune diagnosis & remediation of activated sludge problems, ANOVA R&D has developed the software application MICROexpert. It is an extremely compact and powerful Knowledge-Based System, working on common personal computers (IBM/compatible) and using an original fuzzy reasoning inferential approach within also certainty quantification methodology (12). MICROexpert's knowledge is in conformity of the scientific experience of the Water Research Institute "CNR/Irsa" and "La Sapienza" University of Rome based on a revision work (13) of the results reported in scientific literature, combining also the practical human expertise in wastewater treatment management. MICROexpert's knowledge is mainly based on micro biological trouble-shooting methods related to microscopic examination of activated sludge (1-9), although he is able to use operational parameters too. It should be noted that the "slow" peculiar dynamics of wastewater biological treatment allows the physico-chemical parameters to be able to detect the possible sludge problems only when the same are displayed, generally after a considerable lapse of time (valuable for diagnosis): likewise, a sensible long period (sometimes weeks) needs to cope with a lack of timely diagnosis! It is very important to detect sludge problems by observing micro-biological eco-system that yields informations related to the trend of behaviour of sludge in solids separation and solids handling processes: "...to see the small is to understand the large...".

1.4 ACTIVATED SLUDGE PROCESS AND SOLID SEPARATION PROBLEMS

Biological treatment processes are typically divided into suspended-growth systems and fixed-film systems. The first one are more commonly and represents the target of MICROexpert with the following variations:

- Aerobic treatment plants or nutrient removing (N and P) treatment plants - CSTR (Continuous Stirred Tank Reactor) reactor or Plug Flow reactor.

A basic activated sludge process consists of two liquid stream processing units: the aeration basin (biological reactor) and the secondary clarifier. Often there is also a primary clarifier in the flow sheet. The aeration basin provides an environmental for the removal and transformation of both soluble and particulate pollutants by a mixed and variable consortium of micro- and macro-organisms called activated sludge. The secondary clarifier provides a quiescent environment which allows the activated sludge solids to separate by flocculation and gravity sedimentation from the treated wastewater. The objective of this basin is to provide a clarified overflow called the secondary effluent (low suspended solids (SS), low turbidity) and a thickened underflow called the return activated sludge (RAS). The quality of an activated sludge treatment plant effluent and the process efficiency depends on the proper working of the various treatment units and especially on the ability of the activated sludge to settle and be separated properly in the secondary clarifier (solid separation problems). This function can be seriously hindered when the activate sludge contains large amount of filamentous bacteria that can cause Bulking or biological Foaming (6-7) The identification and evaluation of these types of microorganisms is important for their control and their classification is carried out on a morphological basis by microscopic observations (1). Numerous international research (1-4-6-8-9) have pointed out the correlation between kinds and biological activity of micro-organisms in activated sludge and the operational physico-chemical parameters, giving to the presence/absence of particular micro-organisms an extremely important informative source as for an opportune diagnosis. The structure of the microfauna (protozoa) is a valid indicator of purification plant performance (4-9), such as floc strength or its absence (Dispersed growth), bacterial diversity, the presence of specific microorganisms indicative of growth conditions, and the presence of other higher life forms. High suspended solids concentrations in setter effluents can be caused by Rising sludge, which is the effect of flotation of solids by nitrogen gas resulting from biological denitrification. Rising sludge develops in the bottom layer of the settler, where the solids concentration is high and where the water has stayed in the settler for a prolonged period.

Activated sludge solids separation problems can be summarized (1) so in several types: • Dispersed growth of microorganisms • Non-filamentous Bulking • Filamentous Bulking • Fungal Bulking • Pin Point floc • Blanket Rising • Foaming and scum formation.

2 MICROexpert SYSTEM STRUCTURE An expert system will be defined as a computer system designed to exhibit expert level reasoning within a narrowly defined domain. Typically this system consists of an inferential engine, a knowledge base and a user interface. The software package MICROexpert has been realized using an original fuzzy reasoning inferential engine within certainty quantification methodology "Fuzzy MQC" (12), as it is detailed forward. The goal is the capability to reproduce the complex reasoning exhibited by expert biologists getting process failure diagnosis and so to support the solving of the activated sludge problems, in wastewater treatment plants. The development of the knowledge base of MICROexpert has required a knowledge engineering process during which the last results reported in the scientific literature (1-7-8-9) have been reviewed and performed to develop trouble-shooting methods of diagnosis & remediation (13). The user interface has been developed in a PC/DOS common tool, written in C programming language. In the following figure n.1 is represented the MICROexpert system structure.

PLANT CHARACTERIZATION

PRELIMINARY ASSESSMENT

FILAMENTOUS BACTERIA

OPERATIONAL PARAMETERS

PROTOZOA [SBI] KEYGROUPS

PROTOZOA SPECIES

FUZZY MQC

Efficiency DIAGNOSIS

Sludge Problems DIAGNOSIS

REMEDIES

Certain Quantification Matrixes

INFERENTIAL ENGINE KNOWLEDGE-BASEMQC

DATA INPUT

DATA OUTPUT

MICROexpert

USER INTERFACEINTERFACEMan-Machine

Fig. 1. Schematic diagram of MICROexpert system structure

2.1 DATA INPUT

The microscopic examination of activated sludge, combined with observations of plant operation and the conduct of a few additional tests, can yield much informations on why an activated sludge has problems. Before going consultation, MICROexpert must be set in accordance with the plant physical characteristics and so with the following different positions: > CSTR reactor or Plug Flow reactor; > Aerobic treatment or Nutrient Removal treatment. The system data input requires: - preliminary assessment (survey data on micro- macroscopic points: i.e. filamentous abundance, floc size.../ floating sludge, presence of scum,...); - filamentous microorganism species (if their abundance >3 [Jenkins])

- operational parameters (proposed by the system according to the case: i.e. OUR, ORP, F/M, DO, SVI, etc.); - protozoa keygroups for SBI (Sludge Biotic Index) calculation and protozoa species too (9); MICROexpert doesn't simultaneously require all kind of data above written : he requires just the same (less too) of quali-quantitative data that would be necessary to a expert biologist to get diagnosis. Starting by a preliminary survey data, the system leads the user in data input by proposing appropriate schemes of data, according to the particular case study. In the following figure n.2 is represented the MICROexpert consultation flow chart.

Start

Preliminary AssessmentSurvey Data

Microscopic points

Macroscopic pointsData

Plant Characterization

CSTR reactor

Plug Flow reactor

Aerobic Treatment

Nutrient Removal TreatmentData

Filamentous DataProtozoa [SBI] DataOperational Parameters

Data

?

enoughdata for Diagnosis?

additional

data

Diagnosisprocess efficiency sludge problems

End

Remedies

Fig. 2. General consultation flow chart of the system

2.2 FUZZY "MQC" INFERENTIAL ENGINE AND KNOWLEDGE BASE

The fuzzy reasoning inferential engine carried out in MICROexpert is a logical integration between two methods of handle quantitative/qualitative informations: Fuzzy Logic and Certainty Quantification (11-12). The method has been developed on the concept by which, in a diagnosis reasoning process, every elementary information (data) contributes to the final cause/effect conclusion (diagnosis) through a series of intermediate steps that have to be synthesised and yielded congruent with reference to certainty quantification. For each one groups of homogeneous informations, correlated with each one the possible diagnoses, it has been built a kind of matrix of cause/effect. Its elements are fuzzy membership functions of certainty correlated to the knowledge base of the system and to a predefined fuzzy sets. Every matrix produces a list of congruent partial conclusions. These ones become new data for others matrixes that lead the system near to the final cause/effect conclusion, and so on, until he gets the diagnosis formulation. The knowledge base of the system is compound by conventional rules (if..then..) and is related to scientific informations of the biological domain.

Fuzzy MQC behaviour is similar to neural network, but his knowledge maintenance is more easy and appropriate, also because each elementary informations have its own address, and this kind of biological field is too undefined to be handled by a learning neural network. 2.3 APPLICABILITY AND BENEFITS

MICROexpert can be applied to the wastewater treatment management when there is an activated sludge process, whether aerobic or nutrient removal treatment, whether continuous stirred tank or plug flow reactor. He is a useful support tool for those corporations that deals with wastewater and environment protection management. Since 1993 MICRO- systems have been tested on real activated sludge processes and up to now it is possible to verify the following benefits:

- Opportune diagnosis and consequently reduction of the maintenance costs due to a lack of a timely sludge problems recognition;

- Operational efficiency recovery through a decrease of diagnosis/remediations elaboration time;

- High ratio of quality/price of the process management system;

- Reduction of the base skill required to the operators to assign to microscopic examinations. 2.4 HARDWARE AND SOFTWARE REQUIRED Hardware:

- Pentium Processor - 16 MB of Ram - CD-Rom drive - 15 MB of free hard disk space - SVGA card

Software:

- Operating system MS Windows ‘95/98/NT - Internet Explorer 4.1 or higher to support HTML Guide

3 REGISTRATION The downloaded software starts in DEMO version. You need to register a password in order to activate the full functioning of MICROexpert. The password procedure is as follows: Start the Demo version of MICROexpert: The program now shows the opening window. Under the help option ‘?’ on the main menu you will find the register item. Click on this item and a dialog box opens showing the MICROexpert ID number and a field in which you should fill in your password.

save cancel

The MICROexpert ID# will be used to generate your password, that will unlock the full functioning mode. You will receive your password by contacting ANOVA. The password you receive is only valid for a single PC. If you want to install the software on another PC you will have to obtain another license with another different password for that PC. 4 NEW / OPEN PLANT The program starts showing a dialog box in which you can choose to open a new plant to work on a new project or an existing plant to work on a previous saved project. This option can also be chosen from the File Menu. If you choose to open a new plant a dialog box pops up to insert the new plant (new project) name. If you want to open an already existing project, then click on the option “New Plant” on the file Menu. Previous saved plants are showed. After having selected an existing project it will be opened with the last saved configuration and process data. 4.1 OPEN/SAVE DATA Previous saved input and output or previous saved configurations can be opened clicking on the “Open Data” option on the File Menu. A window will open called open/cancel data. From with you can choose previous saved data from the relative plant. Clicking on the “Save Data” option on the File Menu you can save the current configuration of data

4.2 MENU EDIT Click on ‘Control and Evaluation Parameters’ to start a new project. It allows you to load the program with: � Aerobic Plant � Nutrient Removal Plant � CSTR Completely Stirred Reactors Plant � Plug Flow Biological Reactor

“Microscopic Analysis” and “Floc Structure – Filamentous” let you edit and modify all characteristis about Filamentous Bacteria when bulking is present. You can insert each filamentous specie with a 1 to 6 abundance score (Jenkins). ‘Diagnostic and corrective Actions’ option allows you to make a diagnostic on Biologic Reactor efficiency , proposing the relative corrective actions.

Very

The Archive option allows you to: Visualize the open plant saved data or Make a trend analysis as showed below

close window

Click on ‘Graphic’ to visualize the Trend. To have a Filamentous Bacteria identification support online click on ‘Filamentous Identification Online’ option.

When you click on “Species Recognition” and then you choose a “Process Default” and an “Identification key”, you will find (clicking on “Find” button) Filamentous Bacteria list on left side. If you click on a filamentous bacteria, it will appear a schedules on right sides. So, you can click on “View Images” to visualize the images of filamentous bacteria.

5 SAMPLE TRANSPORT AND STORAGE Activated sludge mixed liquor samples should be taken at points of good mixing either from the effluent end of the aeration basin or from the mixed liquor channel between the aeration basin and the secondary clarifier. Mixed liquor samples should be taken from below the surface to exclude any foam or other floating material. When examination is onsite, several hours delay is inconsequential; more lengthy storage should be at 4°C in a refrigerator. When samples must be transported offsite for analysis, they should be sent in a sample containers in which there is an air space at least equal in volume to the sample volume to avoid septicity. A good and cheap container is a 5 mL plastic disposable transfer pipette. The bulb portion of the pipette should be filled about half full and then the tip should br heat sealed. The sample should be neither chemically preserved nor frozen since these procedures can alter the characteristics of both the flocs and filamentous organism. The longer the time that elapses between sampling and examination, the more difficult and uncertain the sample examination and data interpretation become. Samples from plants with low F/M (Food MicroOrganism) maintain their characteristics longer than samples from plants with high F/M. For low F/M samples a satisfactory examination can be obtained if the sample is examined within 7 to 10 days of sampling; for sludges from high F/M plants it is wise to examine the activated sludge within 3 to 4 days of its sampling. 5.1 EXAMINATION FREQUENCY

Sampling and examination frequency will be dictated by the circumstances and by where the samples are being examined. Daily examination can be justified for onsite examination during critical periods, e.g.:

- Bulking sludge is occurring or is anticipated - Use of RAS chlorination for bulking control - Experimental operation

To establish a Plant operating history a weekly frequency examination is enough. 5.2 MICROSCOPIC EXAMINATION PROCEDURE

Upon sample receipt, or at least within several hours prior to sample examination, spread one drop of well-mixed sample evenly over approximately 50% of the area of each of two 25 mm x 75 mm microscope slides. Allow these slides to air dry at room temperature (do not heat fix). The slides can be stored indefinitely and stained later. Withdraw one drop (approximately 50µl) of well-mixed sample with a loop or a clean, disposable Pasteur pipette and place on a 25 mm x 75 mm microscope slide. Place a glass coverslip on the drop and press down very gently on the coverslip with a blunt object. Remove the liquid that is expelled from the sides of the coverslip with a tissue. This procedure produces the thin preparation which is necessary because of the limited depth of focus of the microscope optical system. This is necessary, even though it hastens the drying out of the slide, because at high power observation, long filaments can pass in and out of focus along their length. Examine the wet mount under phase contrast illumination at 100x magnification for the following characteristics:

- the general size and shape of flocs (small<150 µm - medium 100-200 µm - large > 100 µm) - the presence and types of protozoa, rotifers, nematodes - the presence of fingered or amorphous zoogleal colonies - the presence of nonbiological organic and inorganic particles - the presence of free-floating cells in the bulk solution

5.3 ABUNDANCE RATING

An abundance rating is determined for the sample as a whole (all filament types together) and for each filamentous organism observed. Individual flamentous organism are considered dominant (and likely most responsible for solids separation problems) if they are scored “very common” or greater. Organism are considered secondary, i.e., they are present but not in sufficient abundance to account for solids separation problems, if they are scored “common” or less. This method is both rapid and suitable for establishing whether a filamentous organism is dominant or secondary and for determining their response to remedial actions. Abundance categories generally are reproducible to within ± one abundance category between observers. The next step is to determine which types of filamentous organism are present and their individual abundances. Use a microscope to the 1000x phase contrast setting and carefully characterize each filamentous organism present by looking at several filaments of each type and expressing the result as an “average”. Use filamentous organism worksheet to record and summarize individual observation.

REFERENCES

1. David Jenkins, Michael G. Richard, Glen T. Daigger (1994) - Manual on the Causes and Control of

Activated Sludge Bulking and Foaming - 2nd Edition - Lewis Publishers, INC., MI 48118. Printed in U.S.A.

2. Ichikawa, K. Simizu and K. Iwahori (1993) - Diagnosis Expert System for the Activated Sludge Process using biota observed by microscopic examination - Water Science and Technology - Vol.28, No 11-12, pp.231-237.

3. Bruce Gall and Gilles G.Patry (1989) - Knowledge-Based System for the Diagnosis of Activated Sludge Plant - Lewis Publishers, INC., MI 48118. Printed in U.S.A.

4. Curds, C.R., and Hawkes, H.A., Editors (1975) - Ecological Aspects of Used-Water Treatment, Academic Press, London, England.

5. Barnett, G.G. Patry, I. Takacs (1993) - Activated Sludge Process Bulking and Foaming Based Expert System for Diagnosis and Control Pergamon Press - New York, U.S.A.

6. Cingolani and R. Ramadori (1991) - Il Controllo del Bulking negli Impianti a Fanghi Attivi - Luigi Bazzucchi Center - Perugia, Italy

7. Jenkins, R. Ramadori & L. Cingolani (1992) - Prevention and Control of Bulking Activated Sludge - Luigi Bazzucchi Center - Perugia, Italy

8. Valter Tandoi (1994) - Composizione Microbica dei Fanghi Attivi - rappoto - CNR- Istituto di Ricerca sulle Acque - Roma, Italy

9. Paolo Madoni (1994) - A Sludge Biotic Index (SBI) for the evaluation of the biological performance of activated sludge plants based on the microfauna analysis - Water Research Vol.28, No 1, pp.67-75

10. Rolston (1991) - Sistemi Esperti - teoria e sviluppo - McGraw-Hill Libri Italia srl, Italy

11. G. Mappa, A. Sciarretta, S. Moroni and M. Allegretti (1993) - Sistema Esperto per la Gestione degli Impianti di Trattamento delle Acque Urbane - ANDIS'93 Congress - Palermo, Italy

12. Giovanni Mappa (1992) - Modello di Quantificazione della Certezza nella Interpretazione dei Dati relativi alla Struttura della Microfauna e del Fiocco di Fango Attivo nei Processi di Depurazione Biologica - SESPIM Consortium - internal report - Napoli, Italy

13. Beccari, R. Ramadori, C. Di Iaconi and G. Mappa - (1994) - Formalizzazione della Conoscenza sulle Disfunzioni legate alle Patologie del Fango Attivo finalizzata alla realizzazione di un Sistema Esperto di Diagnosi/Supporto alle Decisioni - "La Sapienza" University of Rome - SESPIM Consortium report - Napoli, Italy