Multi-parameter monitoring Venturi valve matching control system

Abstract

The invention discloses a multi-parameter monitoring venturi valve matching control system, which belongs to the technical field of venturi valves, and comprises a data construction module used for constructing a data model according to acquired food processing information and environmental data information, dividing the environment data information in the data model according to the environment data information in the food processing place and the environment data information outside the food processing place; the data analysis module is used for analyzing an association rule of the change of the environmental data information outside the food processing place to the change of the environmental data information inside the food processing place; by collecting the environmental data information inside and outside the food processing place, the change of the air inlet and outlet volume of the food processing place can be monitored according to the collected environmental data information, the change rule of the air inlet and outlet volume of the food processing place at different time periods is obtained, and the air discharge volume of the Venturi valve is corrected; therefore, the air circulation of a food processing place is in an optimal state.

Description

Technical Field

[0001] The invention relates to the technical field of venturi valves, in particular to a multi-parameter monitoring venturi valve supporting control system. Background Art

[0002] The control logic of the Venturi valve is mainly based on its working principle and characteristics. Through the adjustment of the valve core, the gas flow rate can be accurately controlled and adjusted. Its control logic is to automatically adjust the opening and closing area of ​​the valve according to the change of air volume and flow rate, so as to achieve accurate control of the air flow. In addition, the control logic of the Venturi valve also involves displacement sensors to measure the opening of the exhaust cabinet sliding door in real time, and also involves variable air volume controllers, which realize the adjustment and control of the variable air volume Venturi valve as an "actuator" through calculation to ensure the required exhaust volume value. Venturi valves are widely used and important in the food processing industry. From raw material processing to processing, to packaging and storage stages, they play an indispensable role. They can control the inlet and outlet air volume of the food processing site in real time according to production and processing needs. However, the existing control technology has the problems of single monitoring parameters, slow response speed and insufficient adjustment accuracy, which makes it difficult to meet the needs of high-precision and multi-parameter control. Summary of the invention

[0003] In view of the above problems existing in the technical field of the existing Venturi valve, the present invention is proposed.

[0004] Therefore, one of the objects of the present invention is to provide a multi-parameter monitoring venturi valve supporting control system, which collects environmental data information inside and outside the food processing site, and can monitor the changes in the inlet and outlet air volume of the food processing site according to the collected environmental data information, and obtain the changing pattern of the inlet and outlet air volume of the food processing site at different time periods, so that the system can timely correct the air volume discharge size of the venturi valve, so that the exhaust air volume value of the food processing site is consistent with the preset value, so as to ensure that the air circulation in the food processing site is in the best state.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A multi-parameter monitoring venturi valve supporting control system, comprising:

[0007] A data construction module, used to construct a data model based on the collected food processing information and environmental data information, and divide the environmental data information into environmental data information inside the food processing site and environmental data information outside the food processing site in the data model;

[0008] A data analysis module, used to analyze the correlation between the changes in the environmental data information outside the food processing site and the changes in the environmental data information inside the food processing site, and collect the changes in the environmental data information outside the food processing site by time period, obtain the change characteristics of the environmental data information outside the food processing site in each time period, upload the change characteristics to the data model, and update the data model;

[0009] A data fusion collection unit, which responds to the change characteristics of the environmental data information outside the food processing place in each time period in the data analysis module, and is used to collect the change of the air volume in the food processing place under different change characteristics, and the data fusion collection unit includes a division module, a calculation module and a collection module;

[0010] The division module is used to divide the wind volume change into ▽1, ▽2, ..., ▽ n Divide, wherein n represents the nth air volume change, and analyze the associated changes of different air volume changes on food processing under the preset processing mode, and upload the impact changes to the data model;

[0011] The calculation module is used to calculate the intensity difference of different air volume changes, and preset the air volume change intensity difference based on the preset processing mode. When the air volume change intensity difference in the food processing place exceeds the preset air volume change intensity difference, the system determines that the air volume change in the food processing place is in an abnormal state and issues an early warning. Otherwise, no determination is made.

[0012] The acquisition module is used to collect the intensity difference data of different air volume changes calculated and obtained by the calculation module, and to collect the intensity difference data that appears most frequently in the food processing site, and to analyze the correlation between the intensity difference data and the changes in the environmental data information outside the food processing site;

[0013] The monitoring terminal is used to record the control and adjustment party that matches the Venturi valve control system of the preset monitored food processing site, receive the field data uploaded by the collection monitoring point, and update the background data at the same time. When the monitored air volume change intensity difference in the food processing site exceeds the preset air volume change intensity difference, a request for obtaining information on the Venturi valve air volume change is initiated to the control and adjustment party that matches the Venturi valve control system of the preset monitored food processing site.

[0014] As a preferred solution of the present invention, in the data construction module, the food processing information includes the required processing time and processing method, the processing method includes freezing processing, drying processing, grinding processing and smoking processing, and the food processing objects and processing methods of the preset food processing place are obtained; the environmental data information includes the temperature, humidity and air pressure in the preset food processing place.

[0015] As a preferred solution of the present invention, in the data analysis module, while obtaining the change characteristics of the environmental data information outside the processing site in each time period, the geographical location information of the preset food processing site is obtained, and the change characteristics of the environmental data information outside the processing site are collected in different time periods, including obtaining the change characteristics of the environmental data information outside the processing site in different seasons, and analyzing the change characteristics of the temperature, humidity and air pressure outside the processing site in different seasons.

[0016] As a preferred solution of the present invention, in which: in the division module, the impact change also includes obtaining the processing time corresponding to the preset processing method, dividing the processing time into early processing, mid-processing and late processing, and obtaining the impact changes of different air volume changes during the three processing periods on food processing.

[0017] As a preferred embodiment of the present invention, the food processing steps corresponding to the early processing, mid-processing and late processing are obtained, and the air volume values ​​entering and leaving the food processing place are preset based on different processing steps, and the changes of the exhaust air volume values ​​due to different incoming air volume values ​​are collected, and the changes are divided into low-level changes, medium-level changes and high-level changes in a step-by-step manner. At the same time, a critical threshold is preset with the low-level changes. When the exhaust air volume value change monitored in the food processing place exceeds the critical threshold, the system determines that the exhaust air volume of the food processing place is in an abnormal state and issues an early warning, and at the same time corrects the exhaust air volume of the Venturi valve in the food processing place. Otherwise, no determination is made.

[0018] As a preferred solution of the present invention, the duration of the exhaust air volume value monitored in the food processing site exceeding the critical threshold value is obtained by statistics, and a data set based on the duration is generated. Among them, n represents the nth time duration data obtained, and the external environmental data information of the food processing site corresponding to different time durations is obtained. When the exhaust air volume value obtained in the future time period under the same external environmental data information of the food processing site changes beyond the original time duration, the system determines that the Venturi valve is in an abnormal state and issues an early warning, and at the same time stops the air intake program of the Venturi valve. Otherwise, no determination is made.

[0019] As a preferred solution of the present invention, big data technology is used to capture the correlation between the change in the external environmental data information of the food processing site and the change in the acquired exhaust air volume value exceeding the critical threshold time, and the captured text is cleaned and segmented, and the correlation change data is divided into several evaluation indicators, and the weight of each evaluation indicator is calculated.

[0020] As a preferred solution of the present invention, wherein: in the data set In the present invention, the Monte Carlo method is used to collect the change characteristics of the environmental data information in the food processing place at different exhaust air volume values, the change characteristics are distinguished, and the weights of different change characteristics in different exhaust air volume values ​​are calculated.

[0021] As a preferred solution of the present invention, data cleaning technology and standardization processing are used in the calculated weight data to generate a cleaned data set, and a test set, a training set and a validation set based on the characteristics of changes in environmental data information in the food processing site are generated in the data set to construct a prediction model for changes in environmental data information in the food processing site including different weather conditions and degrees of microbial contamination.

[0022] Beneficial effects:

[0023] The present invention collects environmental data information inside and outside the food processing site, and can monitor the changes in the inlet and outlet air volume of the food processing site according to the collected environmental data information, obtain the changing rules of the inlet and outlet air volume of the food processing site at different time periods, and preset the exhaust air volume value of the food processing site based on the processed products and their processing methods. When it is monitored that the exhaust air volume value of the food processing site is in an abnormal state, the system promptly corrects the air volume exhaust size of the Venturi valve to make the exhaust air volume value of the food processing site consistent with the preset value. In addition, the present invention collects the correlation between the change of the inlet air volume of the Venturi valve and the exhaust air volume, and can further adjust the exhaust air volume of the food processing site according to the inlet air volume to ensure that the air circulation of the food processing site is in the best state. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0025] Figure 1 It is a schematic diagram of the modular structure of a control system supporting a multi-parameter monitoring venturi valve according to an embodiment of the present invention;

[0026] Figure 2 It is a schematic diagram of the process structure of an embodiment of the present invention;

[0027] Numbers in the figure: 110 - data construction module; 120 - data analysis module; 130 - data fusion acquisition unit; 1301 - division module; 1302 - calculation module; 1303 - acquisition module; 140 - monitoring module. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0029] The existing control technology for the air volume in and out of the Venturi valve has problems such as single monitoring parameters, slow response speed and insufficient adjustment accuracy, which makes it difficult to meet the needs of high-precision, multi-parameter control.

[0030] Based on this, the present invention proposes a multi-parameter monitoring venturi valve supporting control system, which collects environmental data information inside and outside the food processing site, and can monitor the changes in the inlet and outlet air volume of the food processing site according to the collected environmental data information, and obtain the changing pattern of the inlet and outlet air volume of the food processing site at different time periods, so that the system can timely correct the air volume discharge size of the venturi valve, so that the exhaust air volume value of the food processing site is consistent with the preset value, so as to ensure that the air circulation in the food processing site is in the best state.

[0031] The present invention is further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0032] Reference Figure 1 to Figure 2 , is an embodiment of the present invention, which provides a multi-parameter monitoring venturi valve supporting control system, including:

[0033] The data construction module 110 is used to construct a data model based on the collected food processing information and environmental data information, and divide the environmental data information into environmental data information inside the food processing site and environmental data information outside the food processing site in the data model;

[0034] It should be noted that the food processing information of this embodiment includes the required processing time and processing method, the processing method includes freezing processing, drying processing, grinding processing and smoking processing, and obtaining the food processing objects and processing methods of the preset food processing place; the environmental data information includes the temperature, humidity and air pressure in the preset food processing place;

[0035] The data analysis module 120 is used to analyze the correlation between the changes in the environmental data information outside the food processing site and the changes in the environmental data information inside the food processing site, collect the changes in the environmental data information outside the food processing site by time period, obtain the change characteristics of the environmental data information outside the food processing site in each time period, upload the change characteristics to the data model, and update the data model;

[0036] Specifically, in this embodiment, while obtaining the change characteristics of the environmental data information outside the processing site in each time period, the geographical location information of the preset food processing site is obtained, and the change characteristics of the environmental data information outside the processing site are collected in different time periods, including obtaining the change characteristics of the environmental data information outside the processing site in different seasons, and analyzing the change characteristics of the temperature, humidity and air pressure outside the processing site in different seasons;

[0037] The data fusion collection unit 130 responds to the change characteristics of the external environmental data information of the food processing place in each time period in the data analysis module 120, and is used to collect the change of the air volume in the food processing place under different change characteristics, and the data fusion collection unit 130 includes a division module 1301, a calculation module 1302 and a collection module 1303;

[0038] The division module 1301 is used to divide the air volume change into ▽1, ▽2, ..., ▽ n Divide, where n represents the nth air volume change, and analyze the associated changes of different air volume changes on food processing under the preset processing mode, and upload the impact changes to the data model;

[0039] It should be emphasized in this embodiment that the influence change also includes obtaining the processing time corresponding to the preset processing mode, dividing the processing time into early processing, mid-processing and late processing, and obtaining the influence change of different air volume changes in the three processing periods on food processing;

[0040] This embodiment further obtains food processing steps corresponding to the early stage processing, the middle stage processing and the late stage processing, and presets the air volume values ​​entering and exiting the food processing place based on different processing steps, collects the changes of the exhaust air volume values ​​due to different incoming air volume values, and divides the changes into low-degree changes, medium-degree changes and high-degree changes in a step-by-step manner, and presets a critical threshold value with a low-degree change. When the exhaust air volume value change monitored in the food processing place exceeds the critical threshold value, the system determines that the exhaust air volume of the food processing place is in an abnormal state and issues an early warning, and at the same time corrects the exhaust air volume of the Venturi valve in the food processing place, otherwise, no determination is made;

[0041] Based on the above, this embodiment obtains the duration of the exhaust air volume value monitored in the food processing site exceeding the critical threshold value, and generates a data set based on the duration. Wherein, n represents the nth time length data obtained, and the external environmental data information of the food processing site corresponding to different time lengths is obtained. When the exhaust air volume value obtained in the future time period under the same external environmental data information of the food processing site changes beyond the original time length, the system determines that the Venturi valve is in an abnormal state and issues an early warning, and stops the air intake program of the Venturi valve at the same time. Otherwise, no determination is made;

[0042] It should be emphasized in this embodiment that the big data technology is used to capture the correlation change of the external environmental data information of the food processing site and the obtained exhaust air volume value change exceeding the critical threshold time, and the captured text is cleaned and word segmented, and the correlation change data is divided into several evaluation indicators, and the weight of each evaluation indicator is calculated;

[0043] At the same time, this embodiment further, in the data set In this paper, the Monte Carlo method is used to collect the change characteristics of the environmental data information in the food processing place at different exhaust air volume values, distinguish the change characteristics, and calculate the weights of different change characteristics in different exhaust air volume values;

[0044] On the basis of the above, this embodiment further uses data cleaning technology and standardization processing in the calculated weight data to generate a cleaned data set, and generates a test set, a training set and a validation set based on the characteristics of environmental data information changes in food processing places in the data set, and constructs a prediction model for environmental data information changes in food processing places including different weather conditions and microbial contamination levels;

[0045] The calculation module 1302 is used to calculate the intensity difference of different air volume changes, and preset the air volume change intensity difference based on the preset processing mode. When the air volume change intensity difference in the food processing place exceeds the preset air volume change intensity difference, the system determines that the air volume change in the food processing place is in an abnormal state and issues an early warning. Otherwise, no determination is made.

[0046] The acquisition module 1303 is used to acquire the intensity difference data of different air volume changes calculated by the calculation module 1302, and to acquire the intensity difference data that appears most frequently in the food processing site, and to analyze the correlation between the intensity difference data and the changes in the environmental data information outside the food processing site;

[0047] The monitoring terminal 140 is used to record the control and adjustment party that matches the Venturi valve control system of the preset monitored food processing site, receive the field data uploaded by the collection monitoring point, and update the background data at the same time. When the air volume change intensity difference in the monitored food processing site exceeds the preset air volume change intensity difference, a request for obtaining information on the Venturi valve air volume change is initiated to the control and adjustment party that matches the Venturi valve control system of the preset monitored food processing site.

[0048] To sum up, by collecting environmental data information inside and outside the food processing site, the changes in the inlet and outlet air volume of the food processing site can be monitored according to the collected environmental data information, the changing pattern of the inlet and outlet air volume of the food processing site in different time periods can be obtained, and the exhaust air volume value of the food processing site can be preset based on the processed products and their processing methods. When it is monitored that the exhaust air volume value of the food processing site is in an abnormal state, the system will promptly correct the air volume discharge size of the Venturi valve to make the exhaust air volume value of the food processing site consistent with the preset value. In addition, the present invention can further adjust the exhaust air volume of the food processing site according to the incoming air volume by collecting the correlation between the change of the incoming air volume of the Venturi valve and the exhaust air volume, so as to ensure that the air circulation in the food processing site is in the best state.

[0049] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A multi-parameter monitoring venturi valve supporting control system, characterized in that: include: A data construction module, used to construct a data model based on the collected food processing information and environmental data information, and divide the environmental data information into environmental data information inside the food processing site and environmental data information outside the food processing site in the data model; A data analysis module, used to analyze the correlation between the changes in the environmental data information outside the food processing site and the changes in the environmental data information inside the food processing site, and collect the changes in the environmental data information outside the food processing site by time period, obtain the change characteristics of the environmental data information outside the food processing site in each time period, upload the change characteristics to the data model, and update the data model; A data fusion collection unit, which responds to the change characteristics of the environmental data information outside the food processing place in each time period in the data analysis module, and is used to collect the change of the air volume in the food processing place under different change characteristics, and the data fusion collection unit includes a division module, a calculation module and a collection module; The division module is used to divide the wind volume change into ▽1, ▽2, ..., ▽ n Divide, wherein n represents the nth air volume change, and analyze the associated changes of different air volume changes on food processing under the preset processing mode, and upload the impact changes to the data model; The calculation module is used to calculate the intensity difference of different air volume changes, and preset the air volume change intensity difference based on the preset processing mode. When the air volume change intensity difference in the food processing place exceeds the preset air volume change intensity difference, the system determines that the air volume change in the food processing place is in an abnormal state and issues an early warning. Otherwise, no determination is made. The acquisition module is used to collect the intensity difference data of different air volume changes calculated and obtained by the calculation module, and to collect the intensity difference data that appears most frequently in the food processing site, and to analyze the correlation between the intensity difference data and the changes in the environmental data information outside the food processing site; The monitoring terminal is used to record the control and adjustment party that matches the Venturi valve control system of the preset monitored food processing site, receive the field data uploaded by the collection monitoring point, and update the background data at the same time. When the monitored air volume change intensity difference in the food processing site exceeds the preset air volume change intensity difference, a request for obtaining information on the Venturi valve air volume change is initiated to the control and adjustment party that matches the Venturi valve control system of the preset monitored food processing site.

2. A multi-parameter monitoring venturi valve supporting control system as claimed in claim 1, characterized in that: In the data construction module, the food processing information includes the required processing time and processing method, the processing method includes freezing processing, drying processing, grinding processing and smoking processing, and the food processing objects and processing methods of the preset food processing place are obtained; the environmental data information includes the temperature, humidity and air pressure in the preset food processing place.

3. A multi-parameter monitoring venturi valve supporting control system as claimed in claim 1, characterized in that: In the data analysis module, while obtaining the change characteristics of the environmental data information outside the processing site in each time period, the geographical location information of the preset food processing site is obtained, and the change characteristics of the environmental data information outside the processing site are collected in different time periods, including obtaining the change characteristics of the environmental data information outside the processing site in different seasons, and analyzing the change characteristics of the temperature, humidity and air pressure outside the processing site in different seasons.

4. A multi-parameter monitoring venturi valve supporting control system as claimed in claim 1, characterized in that: In the division module, the impact changes also include obtaining the processing time corresponding to the preset processing method, dividing the processing time into early processing, mid-processing and late processing, and obtaining the impact changes of different air volume changes during the three processing periods on food processing.

5. A multi-parameter monitoring venturi valve supporting control system as claimed in claim 4, characterized in that: The food processing steps corresponding to the early processing, mid-processing and late processing are obtained, and the air volume values ​​entering and exiting the food processing place are preset based on different processing steps. The changes of the exhaust air volume values ​​due to different incoming air volume values ​​are collected, and the changes are divided into low-level changes, medium-level changes and high-level changes in a step-by-step manner. At the same time, a critical threshold is preset with the low-level changes. When the exhaust air volume value change monitored at the food processing place exceeds the critical threshold, the system determines that the exhaust air volume of the food processing place is in an abnormal state and issues an early warning. At the same time, the exhaust air volume of the Venturi valve in the food processing place is corrected. Otherwise, no determination is made.

6. A multi-parameter monitoring venturi valve supporting control system as claimed in claim 5, characterized in that: Statistically obtain the duration of the exhaust air volume value monitored in the food processing site exceeding the critical threshold, and generate a data set based on the duration Among them, n represents the nth time duration data obtained, and the external environmental data information of the food processing site corresponding to different time durations is obtained. When the exhaust air volume value obtained in the future time period under the same external environmental data information of the food processing site changes beyond the original time duration, the system determines that the Venturi valve is in an abnormal state and issues an early warning, and at the same time stops the air intake program of the Venturi valve. Otherwise, no determination is made.

7. A multi-parameter monitoring venturi valve supporting control system as claimed in claim 6, characterized in that: Big data technology is used to capture the changes in the external environmental data information of the food processing site and the associated changes in the length of time that the exhaust air volume value obtained exceeds the critical threshold, and the captured text is cleaned and segmented. At the same time, the associated change data is divided into several evaluation indicators, and the weight of each evaluation indicator is calculated.

8. A multi-parameter monitoring venturi valve supporting control system as claimed in claim 6, characterized in that: In the data set In the present invention, the Monte Carlo method is used to collect the change characteristics of the environmental data information in the food processing place at different exhaust air volume values, the change characteristics are distinguished, and the weights of different change characteristics in different exhaust air volume values ​​are calculated.

9. A multi-parameter monitoring venturi valve supporting control system as claimed in claim 8, characterized in that: In the calculated weight data, data cleaning technology and standardization processing are used to generate a cleaned data set, and a test set, a training set and a validation set based on the characteristics of changes in the environmental data information in the food processing site are generated in the data set to construct a prediction model for changes in the environmental data information in the food processing site, including different weather conditions and degrees of microbial contamination.

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