4 results about "Sludge volume index" patented technology

Active sludge sieving granulation process, device and use method, relate to the technical field of sewage biochemical treatment, including screen component, screen component includes at least one sieve plate, sieve plate surface is provided with sieve hole, and the lower portion of sieve plate is provided with base;Aeration turbulent component, aeration turbulent component includes aeration pipe installed on the upper surface of base, aeration pipe surface is uniformly provided with aeration disc mounting seat, aeration disc mounting seat is provided with aeration disc above, and aeration pipe interface is installed at the end of aeration pipe;Local turbulent stirring component, local turbulent stirring device includes at least one stirring component, stirring component is arranged on any one side of sieve plate and above aeration disc;Multi-stage sieve hole is used, sieve plate is divided into upper, middle and lower three areas, aperture decreases in turn, can be accurately graded and intercepted according to particle size, aeration disc releases small bubbles to form turbulence, shear force is generated to destroy flocculent sludge structure, to promote microorganism to secrete EPS and accelerate particle densification, sludge volume index is reduced.

The invention relates to the technical field of sewage treatment, in particular to an intelligent activated sludge detection method and system based on multi-modal image recognized.The method comprises the steps that a plurality of sewage samples are obtained through sampling equipment, the sample placement moment is automatically captured through a pressure sensor to serve as starting time, and in the detection process, the sample placement moment is calculated; a camera shoots sample images according to a preset detection time sequence, an AI image processing model in a server analyzes the images, automatically extracts multi-dimensional data such as sludge volume, supernate clarity, rolling felt degree and compaction degree, forms a plurality of feature mean value sequences, constructs a feature mean value curve graph, and meanwhile, obtains a feature mean value curve graph. According to the method, a sludge volume index is obtained by performing mixing and drying operation on a sample, and finally, a system synthesizes multi-dimensional data such as a plurality of characteristic mean value curve graphs, the sludge volume index, the roll felt degree and the compaction degree, and generates a comprehensive sludge comprehensive diagnosis report in combination with an expert case library and an AI diagnosis analysis model. The intelligent degree and accuracy of activated sludge sewage treatment can be improved.

This application discloses an optimization method for regulating the SVI (Sludge Volume Index) of activated sludge based on algae control. The method includes: real-time monitoring of the SVI value in the aerobic activated sludge tank; adding algae at a set ratio to the aerobic activated sludge tank with abnormal SVI values, where abnormal SVI values ​​include both excessively low and excessively high values; for excessively low SVI values ​​(20-60 mL / g), adding algae to maintain the algae concentration in the aerobic tank at 150-250 mg / L to improve the sludge floc structure; for excessively high SVI values ​​(130-200 mL / g), adding algae to maintain the algae concentration in the aerobic tank at 50-150 mg / L to compress the sludge volume. This application achieves targeted regulation and long-term stability of the SVI value within a target range by precisely introducing specific algae into the activated sludge system.

This invention discloses a smart wastewater treatment method and system based on data fusion, relating to the field of wastewater treatment technology. Compared with traditional monitoring methods that rely on a single indicator, this invention integrates key parameters such as pollutant type, sludge volume index, and filamentous bacteria biomass, and combines them with a dynamic normalization algorithm to generate a comprehensive pollution load index. This allows for more accurate identification of the coupling effect between organic matter impact and filamentous bacteria activity, avoiding misjudgment based on a single parameter. Furthermore, by triggering a response strategy with a preset threshold, regulation can be initiated at the initial stage of filamentous bacteria activity exceeding the standard. Compared with the traditional microscopic examination method with a lag of 4-8 hours, the response speed is effectively improved. At the same time, using the recovery of floc structure as the termination condition can avoid carbon source waste caused by over-regulation and shorten the system recovery cycle by 30%.