MICROexpert: an effective Professional Tool to prevent solid separation problems
MICROexpert is a knowledge based software tool for diagnosis and trouble-shooting of operational problems in activated sludge. It deals with suspended-solid systems in aerobic or in nutrient removing (N and P) processes, in CSTR (Continuous Stirred Tank Reactor) or Plug Flow reactors. The main goal of this tool is:
- Detecting, at the right time, functional instability and anomalies in progress;
- Advising on possible corrective operations to prevent solid separation problems (bulking, foaming, rising, pin point floc, etc.), and therefore,
- Avoiding failures of effluent quality.
From: MANUAL on the CAUSES and CONTROL of ACTIVATED SLUDGE BULKING and FOAMING
A holistic approach to diagnosis MICROexpert major strength is its data-fusion, which is the ability to merge consistently different type of data and information to the best diagnosis:
- Microscopic sludge analysis on microfauna, sludge biotic index (SBI), sludge floc morphology and filamentous bacterial growth;
- Laboratory physico-chemical analysis;
- Operative parameters evaluated on field;
- Visual investigation on efficiency of each wastewater treatment.
Incubation period and real-time process control MICROexpert exploits the peculiar “slow” dynamics of activated sludge and its incubation time (days before the effects of biological undesiderable anomalies) to predict diagnosis. Infact, a problem could not be promptly detect before it has occurred, by the only physico-chemical parameters. Generally, an incubation period is a considerable lapse of time… This period (sometimes weeks), has to deal with a lack of a timely diagnosis!
Free chlorine and total organic carbon sensors most successful for detecting contamination in tests using selected biological and chemical contaminants.
EPA has released Distribution System Water Quality Monitoring: Sensor Technology Evaluation Methodology and Results – A Guide for Sensor Manufacturers and Water Utilities, which summarizes the results of tests with various online (i.e., real-time) water quality sensors to see if they could provide dual use for early warning of intentional contamination, as well as monitoring general water
quality. Only sensors most commonly used by water utilities were tested.
Free chlorine and total organic carbon (TOC) sensors were the most successful in detecting a number of chemical and biological contaminants.
- Free chlorine levels noticeably dropped in the presence of various contaminants
- TOC sensors were successful in detecting carbon containing contaminants or carrier liquids
This report, titled “Distribution System Water Quality Monitoring: Sensor Technology Evaluation Methodology and Results – A Guide for Sensor Manufacturers and Water Utilities,” provides an overview of the U.S. Environmental Protection Agency’s (EPA’s) research results from investigating water quality monitoring sensor technologies that might be used to serve as a real-time contamination warning system (CWS) when a contaminant is introduced into a drinking water distribution system. EPA’s concept of CWS for protecting water distribution systems is discussed in Chapter 1.0. A principal component of such a system is online water quality monitoring.
Based on a review of available online water quality monitoring sensor technologies, an early determination was made that it was not technically feasible to accurately identify and quantify the many different types of contaminants that could potentially be introduced into the drinking water supply/distribution system. Furthermore, because online sensor technologies need to be economically suitable for mass deployment within a distribution system, EPA focused its research on identifying sensor technologies that could be used to detect anomalous changes in water quality due to contamination event(s). Once a water quality anomaly is detected, the water utility operator is alerted, and further actions (e.g., sampling and analysis) could be undertaken by the operator to identify and quantify the contaminant if necessary. This report focuses on EPA’s research on pilot-scale evaluations of available online water quality monitoring sensor instrumentation.
Business Modeling & Development (BMD) – Service
Innovation -> Value -> Quality -> Marketing
Our business deveopment approach is based on enhancing of:
- Value: quality, efficiency
- Reputation: quality, marketing
- Sales: marketing, economy
- Profit: economy, efficiency
BM = f (Value, Reputation, Sales, Profit)
Advanced Process Control & Artificial Intelligence (APC/AI) – Service
Data -> Info -> Knowledge -> Fault Detection
Process Optimization begin with a deep Knowledge and Understanding of process …
Our APC approach is based on enhancing of:
- Data Validation & Qualification (ISO/IEC 9126)
- Multivariate Data & Trend Analysis (Data Mining – Knowledge extraction)
- Process Performance Analysis (KPI) – Early Warnings (EWS)
- Fault Detection & Diagnosis (FDD) – Modeling & Forecasting
- Econometric Modeling & Optimization.
APC =f (KPI, Early Warning, Fault Detection, Modelling)
Ready to use solar generator to garantee up to 3kW Power Supply.
Designed to provide electricity in all areas of the globe not covered by a distribution grid and for all uses that require to be able to move their energy source. It can work even in the absence of sunshine offering the advantage of compactness, low noise, no fumes and fuel costs. The batteries contained in the base of only 1 m3 are recharged by the photovoltaic generator which, with its surface of 9 m2, develops a power of 1,5 kW.
Autonomy of free Electric Power for farms, agricolture, irrigation, lighting, campgrounds, etc.
- Cost Effective – no fuel needed, low maintanence costs.
- Easy to Transport – optimized Power vs Volume ratio, “folded” mode for transportation.
- Sustainable – no fumes, no pollution, no noise.
- Dlgs_152_06_agg2010 – Decreto legislativo 3 aprile 2006, n. 152 – Norme in materia ambientale (G.U. n. 88 del 14 aprile 2006)