14 results about "Penicillin fermentation" patented technology

The invention discloses a domain adaptation width learning industrial penicillin concentration prediction method based on parameter migration, and the method is based on BLS, guarantees the calculation precision, and improves the calculation efficiency of a model. According to the method, learnable parameter conversion mapping is designed, the output parameters of the source domain and the target domain are projected into the same parameter space, and the data distribution difference under different domains is reduced to the maximum extent. A distribution alignment regular term of a source domain and a target domain is designed based on MMD, and the migration efficiency of data between the domains is improved. An output parameter regular term and a migration parameter regular term are constructed in an objective function, and overfitting and knowledge negative migration of the model are avoided. A model parameter optimization algorithm is designed, alternative optimization is carried out on output parameters and migration parameters, and optimal model parameters are calculated in a self-adaptive mode. The method is applied to soft measurement modeling of the industrial penicillin fermentation process with the multi-working-condition characteristic, and high-precision prediction of the penicillin concentration in the industrial penicillin fermentation process can be achieved.

The present invention discloses a method for predicting penicillin concentration based on local migration modeling, belonging to the field of soft sensor modeling and application for industrial fermentation production processes. The method divides source and target domain data into subdomains for the penicillin fermentation process. A partial least squares model is used to identify the sub-source domain with the highest correlation with each sub-target domain. A refined migration between subdomains is constructed based on migration component analysis, minimizing the loss of local data information during the migration process. Finally, a prediction model is established within each subdomain, and the target domain data is used to predict penicillin concentration using the established model, thereby improving prediction accuracy.

The application discloses a kind of soft measurement modeling methods of fermentation process based on time sequence diagram network, belongs to the technical field of soft measurement of fermentation process.It includes the following steps: (1) data acquisition and integration: the penicillin fermentation process under different conditions is obtained, and the data is divided, collected and integrated;(2) data selection: the data is selected, the redundant useless data is removed and the causal diagram between variables is established;(3) modeling training: algorithm model is constructed, and learning training is carried out;(4) model prediction: the trained algorithm model is used for prediction, and the prediction result is given.The application proposes a kind of soft measurement modeling method of fermentation process based on time sequence diagram network, improves the prediction accuracy of key product quality of fermentation process;The method uses graph convolution network and long short-term memory, extracts data in time and space dimensions, increases the generalization of model;The method can accurately measure the key product quality of different fermentation processes.

A fermentation process soft-sensing method based on a topologically guided temporal convolutional network belongs to the technical field of fermentation process soft-sensing. The method includes the following steps: 1) Data acquisition and integration: Using a simulation platform to acquire penicillin fermentation processes under different operating conditions, the acquired data is divided, collected, and integrated; 2) Data selection: Selecting data, removing redundant and useless data, and establishing a causal graph between variables; 3) Constructing and training a TGTCN model; and 4) Model prediction. The method adopts a fermentation process soft-sensing method based on a topologically guided temporal convolutional network. It utilizes a graph attention network and a temporal convolutional network to extract data in both temporal and spatial dimensions, increasing the generalizability of the model and enabling accurate measurement of key product quality across different fermentation processes.

The invention relates to the technical field of analysis and testing, and discloses a quality detection method for 6-aminopenicillanic acid, which can effectively detect coporphyrin I which is generated in a penicillin fermentation-enzyme method process and causes the 6-aminopenicillanic acid to become powder, and can be used for detecting the content of porphyrin in each main step of the process. The generation reasons and the effective removal steps are known, so that the technical process control is better guided; meanwhile, the chromatographic conditions can also be used for detecting the content of porphyrin in each main step of the process for producing 6-aminopenicillanic acid so as to understand the generation reasons and effective removal steps of the porphyrin, so that the process control is better guided.

This application provides a method for degrading antibiotic resistance genes in penicillin fermentation residue, comprising: Step S1, providing penicillin fermentation residue to be treated. The penicillin fermentation residue contains at least one target antibiotic resistance gene. Step S2, subjecting the penicillin fermentation residue to gamma ray irradiation treatment. This application addresses the problems of low removal rate of antibiotic resistance genes (ARGs), easy rebound, high treatment cost, and high risk of secondary pollution in existing penicillin fermentation residue treatment technologies by subjecting the penicillin fermentation residue to gamma ray irradiation treatment.

The application discloses a fermentation process soft measurement method based on convolution ONLSTM and self-attention, and belongs to the technical field of soft measurement. The method considers the redundant information in the fermentation process variables, proposes a convolutional ordered neuron long short-term memory network (ONLSTM) multilayer time series prediction model with a self-attention mechanism, first extracts local features of input variables in the fermentation process by using a CNN and reduces the dimensionality; then inputs the extracted features into a multilayer ONLSTM network for time series feature extraction, judges the importance of each input variable through a level, and filters the redundant information in the characteristic variables; finally, the feature weights are dynamically adjusted in combination with the self-attention mechanism, the internal dependency relationship between the input variables is utilized, high weight is given to the high correlation variables, the full connection layer activation function is optimized, high-precision prediction of the dominant variables in the fermentation process is realized, and the method is verified to have high-precision prediction on the penicillin concentration by taking the penicillin fermentation process as an example.

This invention provides a method and system for controlling the liquid level in penicillin fermentation based on visual recognition. By introducing visual AI detection technology into the field of penicillin fermentation production and combining it with the characteristics of fermentation liquid level, a complete set of reference standard selection schemes is innovatively constructed. It also proposes key indicators with specificity and innovation, such as "liquid level value", "rate value" and "fuzzy value", to provide quantitative basis for accurate identification and control of penicillin fermentation liquid level. It is linked with the control system to achieve automatic control, realizing accurate, stable and automated closed-loop control of penicillin fermentation liquid level.

The present invention relates to an efficient penicillin fermentation extraction method and application, comprising: performing coarse filtration, a two-stage ultrafiltration process, continuous extraction, purification, alkalinization dilution, and crystallization on the penicillin fermentation broth; the two-stage ultrafiltration process includes a first-stage ultrafiltration and a second-stage ultrafiltration; the first-stage ultrafiltration is to concentrate the concentrated liquid to a transmittance of 5-10%; the second-stage ultrafiltration is to concentrate the concentrated liquid obtained by the first-stage ultrafiltration to a transmittance of less than 1%; the continuous extraction comprises: combining the dialysates obtained by the first-stage ultrafiltration and the second-stage ultrafiltration to form a two-stage membrane dialysate; and mixing the two-stage membrane dialysate, butyl acetate, and dilute sulfuric acid by flow addition, and simultaneously extracting and centrifuging. The present invention utilizes a two-stage ultrafiltration and continuous extraction process to achieve continuous penicillin production, effectively reducing impurity content while improving production efficiency and penicillin yield. Furthermore, the amount of demulsifier and activated carbon used can be reduced.

This application relates to the technical field of wastewater treatment, specifically disclosing a sludge fermentation method for municipal wastewater treatment, comprising the following steps: mixing sludge, fermentation compound agent, pest control compound agent, and water evenly and stirring for 15-18 hours, followed by filtration to obtain fermented sludge; the pest control compound agent includes bactericides, insecticides, and heavy metal removal agents, wherein the bactericides include a hyperbranched polyester bactericide and penicillin in a weight ratio of (2.5-3):(1.2-1.5), and the fermentation compound agent includes *Trichoderma reesei*, *Candida*, *Aspergillus*, cellulase, and pectinase. The method of this application can be used to treat municipal wastewater, and has the advantages of reducing the harmful content of fermented sludge, realizing sludge recycling and reuse, and having a simple procedure.

The invention relates to the technical field of fermentation process monitoring in the biopharmaceutical industry, in particular to a multi-index prediction method and device for penicillin fermentation and a terminal. The method comprises the following steps: collecting near infrared spectrum data in a penicillin fermentation process, and synchronously measuring multi-index measured values of corresponding penicillin fermentation liquor to form a sample set; preprocessing the sample set to obtain spectral features and measured values; a PLSTM-MTGF model is constructed, and the PLSTM-MTGF model is trained by adopting the spectral characteristics and the actual measurement values; and inputting a spectral feature to be predicted into the trained PLSTM-MTGF model to obtain a multi-index real-time prediction value. The problems that only a single target can be fitted and the real-time performance is poor when multiple indexes of penicillin fermentation are detected in the prior art, and a static model cannot meet the dynamic characteristics of the fermentation process can be solved.

The invention relates to the technical field of fermentation, in particular to an efficient penicillin fermentation process, penicillium chrysogenum HLPG-21 is adopted as a fermentation strain, and the whole fermentation process is sequentially subjected to primary fermentation, secondary fermentation and tertiary fermentation; in the primary fermentation stage, a composite nutrient source is adopted to construct a culture medium; in the second-stage fermentation, a specially modified phenylacetic acid derivative is introduced as a precursor substance; nano-scale titanium dioxide is introduced into the third-stage fermentation to regulate and control the fermentation microenvironment, and finally penicillin is obtained; according to the efficient penicillin fermentation process, the fermentation efficiency and purity of penicillin are remarkably improved through cooperation of all the steps.

The invention provides a preparation method and application of a beta-mannase preparation. The beta-mannase preparation is prepared from beta-mannase, metal ion salt, an acid-base regulator and a stabilizer. When the beta-mannase preparation is added in a penicillin fermentation production process, the formation of penicillium chrysogenum mycelium pellets can be effectively inhibited, the mass transfer and oxygen transfer efficiency in a culture system is improved, the demand on air is reduced, the energy consumption is reduced, and meanwhile, the beta-mannase preparation has no toxic effect on thalli and does not influence the normal growth of the thalli. The penicillin fermentation titer is improved by 15.7% in shake flask fermentation and is improved by 6.8% in fermentation tank fermentation, the production efficiency and economic benefits are remarkably improved, an efficient and reliable novel method is provided for industrial fermentation production of penicillin, and the method has wide industrial application prospects.