A process for the extraction of waste animal and vegetable fats

Abstract

A process for extracting waste animal and vegetable oils and fats, the characteristic data of the raw materials are collected by a sensor network, and the data processing technology is used for denoising, normalization and outlier correction, and the process characteristics are extracted and transmitted to the optimization platform. The optimization platform combines the characteristics of the raw materials with the historical process data, optimizes the process parameters in real time through the expert rule model, and generates optimization instructions to transmit to the execution module. The execution module adjusts in real time according to the optimization instructions, and further optimizes in combination with the real-time feedback of the equipment operation parameters. Through the multi-stage filtering and precision filtering system, high-purity decolorized and purified oil is finally obtained, realizing efficient utilization and environmental protection treatment of waste oil.

Description

Technical Field

[0001] This invention relates to the field of oil processing technology, and more specifically to a process for refining waste animal and vegetable oils. Background Technology

[0002] Waste edible oils, including animal and vegetable oils, are a series of oily waste products that have lost their edible value during the processing of natural vegetable oils and animal fats and oils. The main components of waste edible oils are fatty acids, glycerol, free fatty acids, and other carbon-containing organic matter. Although these waste oils have lost their edible value due to contamination or spoilage, they are rich in fatty acids and other organic chemical components, possessing high recycling value. With proper treatment and refining, they can be converted into valuable biodiesel, industrial lubricants, fertilizers, and other chemical raw materials.

[0003] Existing waste oil refining technologies rely on manual operation or fixed process parameters, failing to achieve real-time adjustments based on raw material characteristics and environmental changes. The treatment effectiveness of traditional methods varies significantly, especially when processing waste oils from different sources, with varying properties and impurities. Particularly when processing waste oils with high water content and numerous impurities, the recovery rate and the quality of the refined oil often fail to meet industrial application requirements. Therefore, a new refining process for waste animal and vegetable oils is needed to address these issues. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a refining process for waste animal and vegetable oils. A specific technical solution for this refining process is as follows: A refining process for waste animal and vegetable oils includes the following steps: S1: The raw material feature acquisition system extracts data features of raw materials as initial process features through a sensor network; S2: The data processing system performs noise removal, data normalization, and outlier correction on the collected initial process data, and extracts process feature data. S3: The data processing system transmits the preprocessed process feature data to the process optimization platform and saves it in the industrial database. S4: The process optimization platform optimizes the heating temperature of the sedimentation device, the rotation speed of the horizontal screw centrifuge, and the process parameters of the delivery pump in real time based on raw material characteristic data and historical process data through an expert rule model, and generates optimization instructions. S5: The process optimization platform transmits optimization instructions to the execution control module and saves them in the industrial database; S6: After receiving the optimization instruction, the execution control module adjusts the following process parameters in real time based on the optimization results: Heating temperature of the settling device; The rotational speed of the horizontal decanter centrifuge; The flow rate of the transfer pump; S7: The equipment feature acquisition system collects the temperature inside the sedimentation device, the vibration amplitude of the drum of the horizontal screw centrifuge, and the liquid level height of the feeding system in real time through a sensor network. The execution control module adjusts in real time based on the parameters collected by the equipment feature acquisition system. S8: The filtration device decolorizes the oil phase obtained by centrifugation, adds 1%-3% of the oil weight of decolorizing white clay, stirs evenly at 90°C for 15 to 30 minutes, and then removes the white clay and fine impurities by filtration to obtain decolorized and purified oil. S9: The decolorized and purified oil is further filtered through a precision filtration device to remove residual particles and is collected into the finished product storage tank.

[0005] To better realize the present invention, it can be further described that: noise is removed in S2 by a low-pass filter, and the filter frequency is set to 0.5Hz; Data normalization is achieved by normalizing the data to the range of 0 to 1 based on the maximum value. The 3σ rule is used to remove outlier data that exceeds the specified range, thus achieving outlier detection and correction.

[0006] Furthermore: In S7, the decolorization process takes 15-30 minutes.

[0007] Furthermore: In the S8, the precision filtration device controls the filtration accuracy to 1-3 microns to remove tiny impurity particles.

[0008] Furthermore: The filtration device comprises a multi-stage filtration system consisting of a primary filtration component, a secondary filtration component, and a precision filtration component, wherein the secondary filtration uses a ceramic membrane filtration component.

[0009] Furthermore: The raw material characteristics collected by the raw material characteristic acquisition system include the viscosity of the oil, the specific gravity of the oil, the type of impurities, the concentration of impurities, and the acid value of the oil.

[0010] The beneficial effects of this invention are as follows: This invention achieves automated control of the entire refining process of waste animal and vegetable oils by combining a raw material characteristic acquisition system, a data processing system, and a process optimization platform. By employing an expert rule model, process parameters such as heating temperature and centrifuge speed can be automatically adjusted in real time according to the characteristics of the raw materials. This not only addresses changes in raw materials but also achieves optimal processing for different batches of oil. By real-time monitoring of oil viscosity, acid value, specific gravity, etc., and combining this with historical data, the process optimization platform can precisely adjust the operating parameters of key equipment such as sedimentation devices and horizontal screw centrifuges. This ensures that every step of the oil refining process is carried out under optimal process conditions, thereby ensuring the quality stability of the final product, improving refining efficiency, and effectively saving energy. Attached Figure Description

[0011] Figure 1 This is a process diagram of the present invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0013] like Figure 1 As shown: A refining process for waste animal and vegetable oils includes the following steps: S1: The raw material feature acquisition system extracts data features of the raw materials as initial process features through a sensor network. The raw material features acquired by the raw material feature acquisition system include the viscosity, specific gravity, type and concentration of impurities, and acid value of the oil.

[0014] Specifically, the flow resistance of the raw material oil is measured in real time using an online viscometer.

[0015] The relative density of oil and water is detected by a specific gravity sensor.

[0016] The proportions of fine particles, colloids, and moisture were identified by measuring with a spectrometer and a suspended solids concentration sensor. The results were then calculated using an online sensing device employing acid-base titration.

[0017] S2: The data processing system performs noise removal, data normalization, and outlier correction on the collected initial process data, and extracts process feature data. Specifically, in S2, a low-pass filter is used to process the sensor signal, with the filtering frequency set to 0.5Hz, in order to eliminate the interference of high-frequency noise signals on feature extraction.

[0018] Data normalization is achieved by normalizing the data to the range of 0 to 1 based on the maximum value. The 3σ rule is used to remove outlier data that exceeds the specified range, thus achieving outlier detection and correction.

[0019] S3: The pre-processed process feature data is transmitted from the data processing system to the process optimization platform and stored in the industrial database. The data storage structure includes timestamps, raw material characteristics, data dimensions and processing methods. S4: The process optimization platform optimizes the heating temperature of the sedimentation device, the rotation speed of the horizontal screw centrifuge, and the process parameters of the delivery pump in real time based on raw material characteristic data and historical process data through an expert rule model, and generates optimization instructions. Specifically, the expert rule model optimizes parameters through a fuzzy logic rule base. For example, if the acid value is high, the heating temperature of the sedimentation device is increased; if the viscosity is low and the impurity concentration is high, the centrifuge speed is increased.

[0020] S5: The process optimization platform transmits optimization instructions to the execution control module and saves them in the industrial database; S6: After receiving the optimization instruction, the execution control module adjusts the following process parameters in real time based on the optimization results: Heating temperature of the settling device; The rotational speed of the horizontal screw centrifuge; The flow rate of the transfer pump; S7: The equipment feature acquisition system collects data in real time from the temperature inside the sedimentation device, the vibration amplitude of the centrifuge drum, and the liquid level in the feeding system via a sensor network. The execution control module adjusts in real time based on the parameters collected by the equipment feature acquisition system. In S7, the decolorization treatment time is 15-30 minutes. Specifically, the temperature sensor inside the sedimentation device has a range of 50°C to 100°C, the centrifuge drum vibration sensor has a detection range of 0.01-1 mm, and the liquid level sensor in the feeding system has a range of 10 cm to 2 m.

[0021] S8: The filtration device decolorizes the oil phase obtained from centrifugation by adding 1%-3% of the oil's weight in decolorizing clay. After stirring at 90°C for 15-30 minutes, the clay and fine impurities are removed by filtration, yielding decolorized and purified oil. The filtration device comprises a multi-stage filtration system consisting of a primary filtration component, a secondary filtration component, and a precision filtration component. This system removes large particulate impurities with a filtration accuracy of 10-50 micrometers. The secondary filtration uses a ceramic membrane filter with a filtration accuracy of 5-10 micrometers. The precision filtration device uses a polytetrafluoroethylene (PTFE) filter with a filtration accuracy of 1-3 micrometers to remove tiny impurity particles.

[0022] S9: The decolorized and purified oil is further filtered through a precision filtration device to remove residual particles and is collected into the finished product storage tank.

[0023] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0024] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A process for refining waste animal and vegetable oils, characterized in that: Includes the following steps: S1: The raw material feature acquisition system extracts data features of raw materials as initial process features through a sensor network; S2: The data processing system performs noise removal, data normalization, and outlier correction on the collected initial process data, and extracts process feature data. S3: The data processing system transmits the preprocessed process feature data to the process optimization platform and saves it in the industrial database. S4: The process optimization platform optimizes the heating temperature of the sedimentation device, the rotation speed of the horizontal screw centrifuge, and the process parameters of the delivery pump in real time based on raw material characteristic data and historical process data through an expert rule model, and generates optimization instructions. S5: The process optimization platform transmits optimization instructions to the execution control module and saves them in the industrial database; S6: After receiving the optimization instruction, the execution control module adjusts the following process parameters in real time based on the optimization results: Heating temperature of the settling device; The rotational speed of the horizontal decanter centrifuge; The flow rate of the transfer pump; S7: The equipment feature acquisition system collects the temperature inside the sedimentation device, the vibration amplitude of the drum of the horizontal screw centrifuge, and the liquid level height of the feeding system in real time through a sensor network. The execution control module adjusts in real time based on the parameters collected by the equipment feature acquisition system. S8: The filtration device decolorizes the oil phase obtained by centrifugation, adds 1%-3% of the oil weight of decolorizing white clay, stirs evenly at 90°C for 15 to 30 minutes, and then removes the white clay and fine impurities by filtration to obtain decolorized and purified oil. S9: The decolorized and purified oil is further filtered through a precision filtration device to remove residual particles and is collected into the finished product storage tank.

2. The process for refining waste animal and vegetable oils according to claim 1, characterized in that: In S2, noise is denoised using a low-pass filter with a filter frequency set to 0.5Hz; Data normalization is achieved by normalizing the data to the range of 0 to 1 based on the maximum value. The 3σ rule is used to remove outlier data that exceeds the specified range, thus achieving outlier detection and correction.

3. The process for refining waste animal and vegetable oils according to claim 2, characterized in that: In S7, the decolorization process takes 15-30 minutes.

4. The refining process for waste animal and vegetable oils according to claim 3, characterized in that: In the S8, the precision filtration device controls the filtration accuracy to 1-3 microns to remove tiny impurity particles.

5. The process for refining waste animal and vegetable oils according to claim 4, characterized in that: The filtration device comprises a multi-stage filtration system consisting of a primary filtration component, a secondary filtration component, and a precision filtration component, wherein the secondary filtration uses a ceramic membrane filtration component.

6. The process for refining waste animal and vegetable oils according to claim 5, characterized in that: The raw material characteristics collected by the raw material characteristic acquisition system include the viscosity of the oil, the specific gravity of the oil, the type of impurities, the concentration of impurities, and the acid value of the oil.

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