CN113190068A

CN113190068A - Temperature and humidity detection control method and system for raw materials for feed production

Info

Publication number: CN113190068A
Application number: CN202110498481.3A
Authority: CN
Inventors: 江广添; 盘义元
Original assignee: Foshan Sanshui Jintai Feed Co ltd
Current assignee: Foshan Sanshui Jintai Feed Co ltd
Priority date: 2021-05-08
Filing date: 2021-05-08
Publication date: 2021-07-30

Abstract

The invention relates to the technical field of temperature and humidity detection and control, in particular to a temperature and humidity detection and control method and system for raw materials for feed production. According to the invention, temperature and humidity influence attribute recognition is carried out on the current environment control behavior data and the current environment configuration data based on a pre-configured temperature and humidity detection control unit, so that corresponding target environment related influence data are obtained based on different temperature and humidity influence attributes, and a temperature and humidity detection control curve is further generated so as to determine the temperature and humidity detection control behavior of the temperature and humidity detection controller. According to the method, the characteristic detail change between the target environment related influence data under different temperature and humidity influence attributes can be considered, so that the obtained target environment related influence data can be matched with the characteristics of the actual raw material storage stage for feed production, and the accurate temperature and humidity control operation can be realized conveniently in the follow-up process.

Description

Temperature and humidity detection control method and system for raw materials for feed production

Technical Field

The invention relates to the technical field of temperature and humidity detection and control, in particular to a temperature and humidity detection and control method and system for raw materials for feed production.

Background

The granulator is important equipment in the modern feed processing industry, and is widely applied to feed processing in animal husbandry, poultry breeding industry, fishery and the like. Domestic feed production enterprises develop vigorously along with the adjustment of national economic structures, and technical equipment is upgraded accordingly. Therefore, domestic enterprises for research and production of feed processing equipment develop rapidly, and control systems based on advanced automation technology also start to gradually enter the feed processing enterprises.

The quality degree of the raw materials for feed production directly influences the growth of the cultured objects and the economic benefit of culture service providers. The raw materials for feed production processed and produced in the prior art need to be stored in a fresh-keeping way, and in order to ensure that nutrients of the raw materials for feed production do not lose in the storage process, the raw materials for feed production need to be kept in a low-temperature drying environment, so that the nutrition and the flavor of the feed are ensured, and the temperature and the humidity of the raw materials for feed production need to be detected and controlled.

Disclosure of Invention

In order to overcome at least the above disadvantages in the prior art, an object of the present invention is to provide a temperature and humidity detection control method and system for raw materials for feed production, which can consider characteristic detail changes between target environment-related influence data under different temperature and humidity influence attributes, and further ensure that the obtained target environment-related influence data can match with the characteristics of the actual raw materials for feed production in the storage stage, so as to facilitate the subsequent implementation of accurate temperature and humidity control operation.

In a first aspect, the invention provides a temperature and humidity detection control method for a raw material for feed production, which is applied to a server, and the method comprises the following steps:

acquiring current environment control behavior data and current environment configuration data extracted by a temperature and humidity detection controller in a storage stage of raw materials for feed production to be reached, and inputting the current environment control behavior data and the current environment configuration data into a temperature and humidity detection control unit;

performing temperature and humidity influence attribute identification on the current environment control behavior data and the current environment configuration data through the temperature and humidity detection control unit to acquire temperature and humidity influence attributes corresponding to the current environment control behavior data and the current environment configuration data;

and acquiring corresponding target environment related influence data from the current environment control behavior data and the current environment configuration data according to the temperature and humidity influence attributes, generating a temperature and humidity detection control curve according to the temperature and humidity influence attributes and the target environment related influence data, and determining the temperature and humidity detection control behavior of the temperature and humidity detection controller according to the temperature and humidity detection control curve.

In an embodiment of the first aspect, the temperature and humidity detection control unit includes a feature extraction structure and a classification output structure; the temperature and humidity influence attribute identification of the current environment control behavior data and the current environment configuration data through the temperature and humidity detection control unit to acquire the temperature and humidity influence attribute corresponding to the current environment control behavior data and the current environment configuration data includes:

inputting the current environment control behavior data and the current environment configuration data into the feature extraction structure for feature extraction and temperature and humidity influence attribute mapping so as to obtain feature extraction information of temperature and humidity influence attributes corresponding to the current environment control behavior data and the current environment configuration data;

inputting the feature extraction information of the temperature and humidity influence attribute into the classification output structure to perform temperature and humidity influence attribute classification output so as to obtain an influence feature component of the temperature and humidity influence attribute feature;

and determining the temperature and humidity influence attribute corresponding to the current environment control behavior data and the current environment configuration data according to a first preset influence characteristic component and the influence characteristic component of the temperature and humidity influence attribute characteristic.

In an embodiment of the first aspect, the inputting the current environmental control behavior data and the current environmental configuration data into the feature extraction structure to perform feature extraction and temperature and humidity influence attribute mapping, so as to obtain feature extraction information of the temperature and humidity influence attribute corresponding to the current environmental control behavior data and the current environmental configuration data includes:

segmenting and clustering all environment temperature and humidity sensing data in the current environment control behavior data and the current environment configuration data into environment temperature and humidity sensing data components;

performing temperature and humidity influence attribute identification on the current environment control behavior data and the current environment configuration data, and performing description feature extraction on temperature and humidity influence attribute contents corresponding to the acquired identification vectors to acquire temperature and humidity influence attribute description features;

cascading the environmental temperature and humidity sensing data components and the temperature and humidity influence attribute description characteristics corresponding to the environmental temperature and humidity sensing data to obtain a temperature and humidity influence attribute cluster corresponding to the environmental temperature and humidity sensing data;

and determining feature extraction information of the temperature and humidity influence attributes corresponding to the current environment control behavior data and the current environment configuration data according to the temperature and humidity influence attribute clusters corresponding to all environment temperature and humidity sensing data in the current environment control behavior data and the current environment configuration data.

In an embodiment of the first aspect, the temperature and humidity detection control unit is configured based on cyclic reference environment control behavior data, a cyclic reference environment configuration data set and a temperature and humidity influence reference data, where the cyclic reference environment control behavior data and the cyclic reference environment configuration data set are reference environment control behavior data and a cyclic reference environment configuration data set in which the number of positive environment influence attributes and the number of negative environment influence attributes are inconsistent; the temperature and humidity influence reference data are determined according to an influence curve of a temperature and humidity influence attribute and an influence curve of a global temperature and humidity influence attribute, wherein the influence curve of the global temperature and humidity influence attribute is an influence curve of a global temperature and humidity influence attribute corresponding to each reference environment control behavior data and circulation reference environment configuration data in the circulation reference environment control behavior data and circulation reference environment configuration data set, the influence curve of the temperature and humidity influence attribute is an influence curve of a temperature and humidity influence attribute corresponding to the reference environment control behavior data and circulation reference environment configuration data acquired by the temperature and humidity detection control unit, and the temperature and humidity influence reference data include a first temperature and humidity influence reference object, a second temperature and humidity influence reference object and a reference object range, and the method further includes:

acquiring the cyclic reference environment control behavior data and a cyclic reference environment configuration data set and an influence curve of global temperature and humidity influence attributes corresponding to the cyclic reference environment control behavior data and the cyclic reference environment configuration data set;

and performing parameter optimization on a reference temperature and humidity detection control unit according to the cyclic reference environment control behavior data, the cyclic reference environment configuration data set and the influence curve of the global temperature and humidity influence attribute to obtain the temperature and humidity detection control unit.

In an embodiment of the first aspect, the reference environment control behavior data and cyclic reference environment configuration data set includes a plurality of reference environment control behavior data and cyclic reference environment configuration data, and the reference temperature and humidity detection control unit includes a reference feature extraction structure and a reference classification output structure; the performing parameter optimization on a reference temperature and humidity detection control unit according to the reference environment control behavior data, the cyclic reference environment configuration data set and the influence curve of the global temperature and humidity influence attribute to obtain the temperature and humidity detection control unit includes:

performing feature extraction and humiture influence attribute mapping on the reference environment control behavior data and the cyclic reference environment configuration data through the reference feature extraction structure to obtain feature extraction information indexes of humiture influence attributes corresponding to the reference environment control behavior data and the cyclic reference environment configuration data;

carrying out classified output on the temperature and humidity influence attribute on the characteristic extraction information indexes of the temperature and humidity influence attribute through the reference classified output structure so as to obtain an influence curve of the temperature and humidity influence attribute;

and determining the temperature and humidity influence reference data according to the temperature and humidity influence attribute influence curve and the global temperature and humidity influence attribute influence curve corresponding to the reference environment control behavior data and the cyclic reference environment configuration data, and updating the weight parameters of the reference temperature and humidity detection control unit according to the temperature and humidity influence reference data until the unit evaluation index of the temperature and humidity influence reference data is smaller than the set unit evaluation index or the optimization of the preset times is completed.

In an embodiment of the first aspect, the determining, according to an influence curve of a temperature and humidity influence attribute and an influence curve of a global temperature and humidity influence attribute corresponding to each of the reference environment control behavior data and the cyclic reference environment configuration data, the temperature and humidity influence reference data includes:

determining first optimization information according to the influence curve of the temperature and humidity influence attribute corresponding to each reference environment control behavior data and the cyclic reference environment configuration data, the unit evaluation index of the temperature and humidity influence attribute in the influence curve of the global temperature and humidity influence attribute, and a second preset influence characteristic component;

determining second optimization information according to the time delay temperature and humidity influence attribute of the first optimization information;

and generating the temperature and humidity influence reference data according to the second optimization information, the influence curve of the temperature and humidity influence attribute, the unit evaluation index of the temperature and humidity influence attribute, the environmental control time domain parameter of the positive environmental influence attribute, the environmental control frequent item parameter and the reference object range.

In an embodiment of the first aspect, the generating the temperature and humidity influence reference data according to the second optimization information, the influence curve of the temperature and humidity influence attribute, the unit evaluation index of the temperature and humidity influence attribute, the environmental control time domain parameter of the positive environmental influence attribute, the environmental control frequent item parameter, and the reference object range includes:

generating the first temperature and humidity influence reference object according to the second optimization information, the influence curve of the temperature and humidity influence attribute, the unit evaluation index of the temperature and humidity influence attribute and the environment control time domain parameter of the positive environment influence attribute;

generating a second temperature and humidity influence reference object according to the second optimization information, the influence curve of the temperature and humidity influence attribute, the unit evaluation index of the temperature and humidity influence attribute, the environmental control time domain parameter of the positive environmental influence attribute and the environmental control frequent item parameter;

and generating the temperature and humidity influence reference data according to the first temperature and humidity influence reference object, the second temperature and humidity influence reference object and the reference object range.

In an embodiment of the first aspect, acquiring, according to the temperature and humidity influence attribute, corresponding target environment-related influence data from the current environment control behavior data and the current environment configuration data includes:

acquiring first key environmental influence data and second key environmental influence data corresponding to current environmental control behavior data and current environmental configuration data according to an influence target corresponding to the temperature and humidity influence attribute, wherein the first key environmental influence data comprise environmental influence change data which do not comprise an environmental control behavior tag in the current environmental control behavior data and the current environmental configuration data, and the second key environmental influence data comprise environmental influence change data which comprise the environmental control behavior tag in the current environmental control behavior data and the current environmental configuration data;

scheduling control node extraction is carried out on the first key environment influence data, and a non-scheduling control target corresponding to the first key environment influence data is obtained; performing scheduling control node extraction on the second key environment influence data to obtain a scheduling control target corresponding to the second key environment influence data;

cascading the scheduling control target and the non-scheduling control target based on a scheduling dimension value to obtain environment control updating information corresponding to the current environment control behavior data and the current environment configuration data; clustering the environment control updating information to obtain clustering information corresponding to the current environment control behavior data and the current environment configuration data; under the condition that the clustering information meets a preset condition, acquiring key environment influence data matched with the clustering category from the current environment control behavior data and the current environment configuration data through the clustering category indicated by the clustering information as the target environment related influence data;

acquiring first key environment influence data and second key environment influence data corresponding to current environment control behavior data and current environment configuration data according to the influence targets corresponding to the temperature and humidity influence attributes, wherein the acquiring comprises the following steps:

according to an influence target corresponding to the temperature and humidity influence attribute, performing environment control behavior execution detection on the current environment control behavior data and the current environment configuration data to obtain first environment influence change data which do not contain an environment control behavior label in the current environment control behavior data and the current environment configuration data, and performing data cascade aiming at the environment control behavior category on the first environment influence change data in the current environment control behavior data and the current environment configuration data to serve as the first key environment influence data; obtaining second environmental influence data containing an environmental control behavior label in the current environmental control behavior data and the current environmental configuration data according to the first environmental influence change data, and performing data cascade aiming at the environmental control behavior category on the second environmental influence data in the current environmental control behavior data and the current environmental configuration data to serve as second key environmental influence data;

the extracting of the scheduling control node for the first key environmental impact data to obtain the non-scheduling control target corresponding to the first key environmental impact data includes:

scheduling control node extraction is carried out on the first key environment influence data, and a non-scheduling control target corresponding to the first key environment influence data is obtained;

the extracting of the scheduling control node for the second key environmental impact data to obtain the scheduling control target corresponding to the second key environmental impact data includes:

performing scheduling control node extraction on the second key environment influence data to obtain a scheduling control target corresponding to the second key environment influence data;

wherein, the cascading of the scheduling control target and the non-scheduling control target based on the scheduling dimension value to obtain the environment control update information corresponding to the current environment control behavior data and the current environment configuration data includes:

cascading the scheduling control target and the non-scheduling control target based on a scheduling dimension value to obtain environment control updating information corresponding to the current environment control behavior data and the current environment configuration data;

wherein the clustering the environmental control update information to obtain clustering information corresponding to the current environmental control behavior data and the current environmental configuration data includes:

clustering the environment control updating information to obtain clustering information corresponding to the current environment control behavior data and the current environment configuration data.

In an embodiment of the first aspect, generating a temperature and humidity detection control curve according to the temperature and humidity influence attribute and the target environment related influence data, so as to determine a temperature and humidity detection control behavior of the temperature and humidity detection controller according to the temperature and humidity detection control curve, includes:

acquiring positive feedback adjustment rule information and negative feedback adjustment rule information in the target environment related influence data according to the environment control rule information corresponding to the temperature and humidity influence attribute;

performing feedback curve analysis on the positive feedback adjustment rule information and the negative feedback adjustment rule information in the target environment-related influence data based on adjustment synchronization information between the positive feedback adjustment rule information and the negative feedback adjustment rule information in the target environment-related influence data to obtain feedback curve analysis information;

determining negative feedback adjustment rule information of linkage nodes existing in feedback curve analysis as reference negative feedback adjustment rule information, and determining regulation time sequence information matched with the reference negative feedback adjustment rule information according to curve change information between the negative feedback adjustment rule information in the feedback curve analysis information and the reference negative feedback adjustment rule information; performing feedback curve analysis on the adjusting time sequence information matched with the reference negative feedback adjustment rule information and the reference negative feedback adjustment rule information to obtain feedback curve instruction analysis information; according to the feedback curve instruction analysis information and the feedback curve analysis information, determining a temperature and humidity detection control curve in the target environment related influence data and a temperature and humidity control sequence corresponding to the temperature and humidity detection control curve; the temperature and humidity control sequence comprises different temperature and humidity control instruction information corresponding to the temperature and humidity detection control curve;

and obtaining the temperature and humidity detection control behavior according to the temperature and humidity detection control curve information and the temperature and humidity control sequence corresponding to the temperature and humidity detection control curve information.

In a second aspect, an embodiment of the present invention further provides a temperature and humidity detection control apparatus for a raw material for feed production, which is applied to a server in communication with a temperature and humidity detection controller, and includes:

the acquisition module is used for acquiring current environment control behavior data and current environment configuration data extracted by the temperature and humidity detection controller in a storage stage of raw materials for feed production to be reached and inputting the current environment control behavior data and the current environment configuration data into the temperature and humidity detection control unit;

the identification module is used for identifying the temperature and humidity influence attributes of the current environment control behavior data and the current environment configuration data through the temperature and humidity detection control unit so as to acquire the temperature and humidity influence attributes corresponding to the current environment control behavior data and the current environment configuration data;

and the generating module is used for acquiring corresponding target environment related influence data from the current environment control behavior data and the current environment configuration data according to the temperature and humidity influence attributes, generating a temperature and humidity detection control curve according to the temperature and humidity influence attributes and the target environment related influence data, and determining the temperature and humidity detection control behavior of the temperature and humidity detection controller according to the temperature and humidity detection control curve.

In a third aspect, an embodiment of the present invention further provides a server, where the server includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is used for being communicatively connected to at least one temperature and humidity detection controller, the machine-readable storage medium is used for storing a program, an instruction, or a code, and the processor is used for executing the program, the instruction, or the code in the machine-readable storage medium to execute the temperature and humidity detection control method for the raw material for feed production in any one of the first aspect or the first aspect.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where instructions are stored, and when the instructions are executed, the computer executes the method for controlling temperature and humidity detection of a raw material for feed production in the first aspect or any one of the first aspects.

Based on any one of the above aspects, in the embodiment of the present invention, based on a pre-configured temperature and humidity detection control unit, temperature and humidity influence attribute recognition is performed on current environment control behavior data and current environment configuration data, so as to obtain corresponding target environment related influence data based on different temperature and humidity influence attributes, and further generate a temperature and humidity detection control curve, so as to determine a temperature and humidity detection control behavior of the temperature and humidity detection controller. By the design, the characteristic detail change between the target environment related influence data under different temperature and humidity influence attributes can be considered, so that the obtained target environment related influence data can be matched with the actual characteristics of the raw material storage stage for feed production, and the follow-up accurate temperature and humidity control operation is conveniently realized.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

Fig. 1 is a schematic view of an application scenario of a temperature and humidity detection control system for raw materials for feed production according to an embodiment of the present invention;

fig. 2 is a schematic flow chart of a temperature and humidity detection control method for raw materials for feed production according to an embodiment of the present invention;

fig. 3 is a functional module schematic diagram of a temperature and humidity detection control device for raw materials for feed production according to an embodiment of the present invention;

fig. 4 is a block diagram schematically illustrating a structure of a server for implementing the temperature and humidity detection control method for raw materials for feed production according to an embodiment of the present invention.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

It should be understood that "system", "device", "unit" and/or "module" as used in this specification is a method for distinguishing different components, elements, parts or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.

As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Flow charts are used in this description to illustrate operations performed by a system according to embodiments of the present description. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.

Fig. 1 is an interactive schematic view of a temperature and humidity detection control system 10 for raw materials for feed production according to an embodiment of the present invention. The temperature and humidity detection control system 10 for raw materials for feed production may include a server 100 and a temperature and humidity detection controller 200 communicatively connected to the server 100. The temperature and humidity detection control system 10 for raw materials for feed production shown in fig. 1 is only one possible example, and in other possible embodiments, the temperature and humidity detection control system 10 for raw materials for feed production may also include only one of the components shown in fig. 1 or may also include other components.

In this embodiment, the server 100 and the temperature and humidity detection controller 200 in the temperature and humidity detection control system 10 for raw materials for feed production may execute the temperature and humidity detection control method for raw materials for feed production described in the following method embodiment in a matching manner, and the detailed description of the following method embodiment may be referred to in the execution steps of the server 100 and the temperature and humidity detection controller 200.

To solve the technical problems in the background art, fig. 2 is a schematic flow chart of a method for detecting and controlling temperature and humidity of raw materials for feed production according to an embodiment of the present invention, and the method for detecting and controlling temperature and humidity of raw materials for feed production according to the embodiment may be executed by the server 100 shown in fig. 1, and the method for detecting and controlling temperature and humidity of raw materials for feed production is described in detail below.

Step S110, acquiring current environment control behavior data and current environment configuration data, and inputting the current environment control behavior data and the current environment configuration data into a temperature and humidity detection control unit.

In this embodiment, the current environment control behavior data and the current environment configuration data may be obtained from the temperature and humidity detection controller. Before the server acquires the current environment control behavior data and the current environment configuration data from the temperature and humidity detection controller, the server can firstly obtain the data authority authorization of the temperature and humidity detection controller, and the server cannot participate in the temperature and humidity detection control behavior of the temperature and humidity detection controller. That is, the server is only used for making decisions on the critical environmental impact data of the temperature and humidity detection controller, and does not participate in actual control. Further, the current environment control behavior data and the current environment configuration data include various data of the temperature and humidity detection controller during the temperature and humidity detection control behavior, which are not listed here.

Further, the current environmental control behavior data and the current environmental configuration data may be real-time critical environmental impact data of the temperature and humidity detection controller.

In this embodiment, the temperature and humidity detection control unit may be an artificial intelligence network configured in advance, and a network parameter adjustment process of the configuration process may be adjusted according to actual service requirements, for example, a corresponding configuration set is selected in advance for parameter optimization, and for example, a convergence condition of a network model is set in advance. It can be understood that the temperature and humidity detection control unit is used for performing cyclic and real-time temperature and humidity influence attribute identification on the current environment control behavior data and the current environment configuration data so as to ensure the timeliness of the subsequent temperature and humidity detection control.

Further, an embodiment of the present invention further provides a configuration process for a temperature and humidity detection control unit, where the temperature and humidity detection control unit is configured based on cyclic reference environment control behavior data and a cyclic reference environment configuration data set and temperature and humidity influence reference data, and the cyclic reference environment control behavior data and the cyclic reference environment configuration data set are reference environment control behavior data and a cyclic reference environment configuration data set in which the number of positive environment influence attributes and the number of negative environment influence attributes are inconsistent; and the temperature and humidity influence reference data is determined according to an influence curve of the temperature and humidity influence attribute and an influence curve of the global temperature and humidity influence attribute.

Furthermore, the influence curve of the global temperature and humidity influence attribute is an influence curve of a global temperature and humidity influence attribute corresponding to each reference environment control behavior data and cyclic reference environment configuration data in the cyclic reference environment control behavior data and cyclic reference environment configuration data set, the influence curve of the temperature and humidity influence attribute is an influence curve of a temperature and humidity influence attribute corresponding to the reference environment control behavior data and cyclic reference environment configuration data acquired by the temperature and humidity detection control unit, and the temperature and humidity influence reference data includes a first temperature and humidity influence reference object, a second temperature and humidity influence reference object, and a reference object range.

Based on the above, before step S110, the parameter optimization may be performed on the temperature and humidity detection control unit in advance, and the configuration process of the temperature and humidity detection control unit may include the following steps a and b.

Step a, acquiring the cyclic reference environment control behavior data and the cyclic reference environment configuration data set and an influence curve of global temperature and humidity influence attributes corresponding to the cyclic reference environment control behavior data and the cyclic reference environment configuration data set.

And b, performing parameter optimization on a reference temperature and humidity detection control unit according to the cyclic reference environment control behavior data, the cyclic reference environment configuration data set and the influence curve of the global temperature and humidity influence attribute to obtain the temperature and humidity detection control unit.

On the basis of the above, the reference environment control behavior data and the cyclic reference environment configuration data set include a plurality of reference environment control behavior data and cyclic reference environment configuration data, the reference temperature and humidity detection control unit includes a reference feature extraction structure and a reference classification output structure, and step b can also be implemented in the following manner: performing feature extraction and humiture influence attribute mapping on the reference environment control behavior data and the cyclic reference environment configuration data through the reference feature extraction structure to obtain feature extraction information indexes of humiture influence attributes corresponding to the reference environment control behavior data and the cyclic reference environment configuration data; carrying out classified output on the temperature and humidity influence attribute on the characteristic extraction information indexes of the temperature and humidity influence attribute through the reference classified output structure so as to obtain an influence curve of the temperature and humidity influence attribute; and determining the temperature and humidity influence reference data according to the temperature and humidity influence attribute influence curve and the global temperature and humidity influence attribute influence curve corresponding to the reference environment control behavior data and the cyclic reference environment configuration data, and updating the weight parameters of the reference temperature and humidity detection control unit according to the temperature and humidity influence reference data until the unit evaluation index of the temperature and humidity influence reference data is smaller than the set unit evaluation index or the optimization of the preset times is completed.

In this embodiment, the influence curve of the temperature and humidity influence attribute may be presented in different forms, and the unit evaluation index is used to represent the loss condition of the prediction result of the temperature and humidity influence reference data in the training process. The reference environment control behavior data and the cyclic reference environment configuration data can represent specific behavior data of the temperature and humidity detection control behavior.

On the basis of the above, the determining the temperature and humidity influence reference data according to the temperature and humidity influence attribute influence curve and the global temperature and humidity influence attribute influence curve corresponding to each reference environment control behavior data and the cyclic reference environment configuration data includes: determining first optimization information according to the influence curve of the temperature and humidity influence attribute corresponding to each reference environment control behavior data and the cyclic reference environment configuration data, the unit evaluation index of the temperature and humidity influence attribute in the influence curve of the global temperature and humidity influence attribute, and a second preset influence characteristic component; determining second optimization information according to the time delay temperature and humidity influence attribute of the first optimization information; and generating the temperature and humidity influence reference data according to the second optimization information, the influence curve of the temperature and humidity influence attribute, the unit evaluation index of the temperature and humidity influence attribute, the environmental control time domain parameter of the positive environmental influence attribute, the environmental control frequent item parameter and the reference object range.

In this embodiment, the optimization information may be understood as a network parameter of a model network, the environmental control time domain parameter may be a time-dependent weight, and the unit evaluation index of the temperature and humidity influence attribute may be used to represent the influence of different temperature and humidity influence attributes on other temperature and humidity influence attributes.

Further, the generating the temperature and humidity influence reference data according to the second optimization information, the influence curve of the temperature and humidity influence attribute, the unit evaluation index of the temperature and humidity influence attribute, the environmental control time domain parameter of the positive environmental influence attribute, the environmental control frequent item parameter, and the reference object range includes: generating the first temperature and humidity influence reference object according to the second optimization information, the influence curve of the temperature and humidity influence attribute, the unit evaluation index of the temperature and humidity influence attribute and the environment control time domain parameter of the positive environment influence attribute; generating a second temperature and humidity influence reference object according to the second optimization information, the influence curve of the temperature and humidity influence attribute, the unit evaluation index of the temperature and humidity influence attribute, the environmental control time domain parameter of the positive environmental influence attribute and the environmental control frequent item parameter; and generating the temperature and humidity influence reference data according to the first temperature and humidity influence reference object, the second temperature and humidity influence reference object and the reference object range.

In this embodiment, the temperature and humidity affecting reference object may be a parameter item corresponding to a temperature and humidity detection control behavior, and relevant control information of the environment control real-time control process recorded in the temperature and humidity affecting reference object is not described herein again.

It can be understood that, by implementing the contents described in the above steps a and b, the configuration of the temperature and humidity detection control unit can be realized in advance, so as to ensure the accuracy of the operation of the temperature and humidity detection control unit.

And step S120, performing temperature and humidity influence attribute identification on the current environment control behavior data and the current environment configuration data through the temperature and humidity detection control unit to acquire temperature and humidity influence attributes corresponding to the current environment control behavior data and the current environment configuration data.

In this embodiment, there are a plurality of temperature and humidity affecting attributes corresponding to the current environment control behavior data and the current environment configuration data, which are not limited herein, and it can be understood that, under different temperature and humidity affecting attributes, target environment related affecting data may be different, and by performing identification on different temperature and humidity affecting attributes on the to-be-processed service data, different target environment related affecting data can be distinguished as far as possible, so that a decision on a temperature and humidity detection control curve is comprehensively implemented.

In this embodiment, the temperature and humidity detection control unit includes a feature extraction structure and a classification output structure, where the feature extraction structure and the classification output structure may be a functional network layer in the temperature and humidity detection control unit, and further, step S120 may be implemented by: inputting the current environment control behavior data and the current environment configuration data into the feature extraction structure for feature extraction and temperature and humidity influence attribute mapping so as to obtain feature extraction information of temperature and humidity influence attributes corresponding to the current environment control behavior data and the current environment configuration data; inputting the feature extraction information of the temperature and humidity influence attribute into the classification output structure to perform temperature and humidity influence attribute classification output so as to obtain an influence feature component of the temperature and humidity influence attribute feature; and determining the temperature and humidity influence attribute corresponding to the current environment control behavior data and the current environment configuration data according to a first preset influence characteristic component and the influence characteristic component of the temperature and humidity influence attribute characteristic.

In this embodiment, the feature extraction information of the temperature and humidity influence attribute may be a component formed by segmenting and clustering according to a time sequence order, the influence feature component is information recorded by the description vector set and used for describing the temperature and humidity influence attribute feature, the traceability of the temperature and humidity influence attribute feature can be ensured by recording the temperature and humidity influence attribute information by using the description vector set, and the first preset influence feature component may be determined according to a historical temperature and humidity influence attribute. By means of the design, through the mutual matching between the feature extraction structure and the classification output structure, different temperature and humidity influence attributes corresponding to the current environment control behavior data and the current environment configuration data can be accurately and completely determined.

It can be understood that the feature extraction structure may further include a plurality of functional units corresponding to the functional units with logical continuity, and based on this, the inputting the current environmental control behavior data and the current environmental configuration data into the feature extraction structure for feature extraction and temperature and humidity influence attribute mapping to obtain the feature extraction information of the temperature and humidity influence attribute corresponding to the current environmental control behavior data and the current environmental configuration data includes: segmenting and clustering all environment temperature and humidity sensing data in the current environment control behavior data and the current environment configuration data into environment temperature and humidity sensing data components; performing temperature and humidity influence attribute identification on the current environment control behavior data and the current environment configuration data, and performing description feature extraction on temperature and humidity influence attribute contents corresponding to the acquired identification vectors to acquire temperature and humidity influence attribute description features; cascading the environmental temperature and humidity sensing data components and the temperature and humidity influence attribute description characteristics corresponding to the environmental temperature and humidity sensing data to obtain a temperature and humidity influence attribute cluster corresponding to the environmental temperature and humidity sensing data; and determining feature extraction information of the temperature and humidity influence attributes corresponding to the current environment control behavior data and the current environment configuration data according to the temperature and humidity influence attribute clusters corresponding to all environment temperature and humidity sensing data in the current environment control behavior data and the current environment configuration data.

In the above, the temperature and humidity influence attribute content is used to distinguish different temperature and humidity influence attributes. In practical implementation, the temperature and humidity influence attribute cluster can be further determined by segmenting and clustering the environmental temperature and humidity sensing data, then identifying the temperature and humidity influence attributes of the current environmental control behavior data and the current environmental configuration data in parallel, and further acquiring corresponding temperature and humidity influence attribute description characteristics, wherein the temperature and humidity influence attribute cluster can be realized based on a Kmeans clustering algorithm. By the design, the independence of the feature extraction information of the temperature and humidity influence attribute can be ensured.

Step S130, acquiring corresponding target environment related influence data from the current environment control behavior data and the current environment configuration data according to the temperature and humidity influence attributes, generating a temperature and humidity detection control curve according to the temperature and humidity influence attributes and the target environment related influence data, and determining a temperature and humidity detection control behavior of the temperature and humidity detection controller according to the temperature and humidity detection control curve.

In the actual implementation process, the inventor finds that it is important for generating a temperature and humidity detection control curve and performing subsequent processing to accurately extract target environment-related influence data, and to achieve this purpose, the method for obtaining corresponding target environment-related influence data from the current environment control behavior data and the current environment configuration data according to the temperature and humidity influence attribute may include the following contents described in step S131 to step S133.

Step S131, acquiring first key environmental influence data and second key environmental influence data corresponding to current environmental control behavior data and current environmental configuration data according to an influence target corresponding to the temperature and humidity influence attribute, wherein the first key environmental influence data includes environmental influence change data which does not include an environmental control behavior tag in the current environmental control behavior data and the current environmental configuration data, and the second key environmental influence data includes environmental influence change data which includes an environmental control behavior tag in the current environmental control behavior data and the current environmental configuration data. In this embodiment, the environmental control behavior tag may be used to distinguish between different environmental control behaviors. Further, the environmental control behavior tag may also be represented by other means, and is not limited herein.

In this embodiment, obtaining the first key environmental impact data and the second key environmental impact data corresponding to the current environmental control behavior data and the current environmental configuration data according to the impact target corresponding to the temperature and humidity impact attribute further includes: according to an influence target corresponding to the temperature and humidity influence attribute, performing environment control behavior execution detection on the current environment control behavior data and the current environment configuration data to obtain first environment influence change data which do not contain an environment control behavior label in the current environment control behavior data and the current environment configuration data, and performing data cascade aiming at the environment control behavior category on the first environment influence change data in the current environment control behavior data and the current environment configuration data to serve as the first key environment influence data; and acquiring second environmental influence data containing an environmental control behavior label in the current environmental control behavior data and the current environmental configuration data according to the first environmental influence change data, and performing data cascade aiming at the environmental control behavior category on the second environmental influence data in the current environmental control behavior data and the current environmental configuration data to serve as the second key environmental influence data.

Step S132, scheduling control node extraction is carried out on the first key environmental impact data, and a non-scheduling control target corresponding to the first key environmental impact data is obtained; and extracting scheduling control nodes from the second key environment influence data to obtain a scheduling control target corresponding to the second key environment influence data.

In this embodiment, the performing scheduling control node extraction on the first key environmental impact data to obtain a non-scheduling control target corresponding to the first key environmental impact data includes: and performing scheduling control node extraction on the first key environment influence data to obtain a non-scheduling control target corresponding to the first key environment influence data. The extracting of the scheduling control node for the second key environmental impact data to obtain the scheduling control target corresponding to the second key environmental impact data includes: and extracting scheduling control nodes from the second key environment influence data to obtain a scheduling control target corresponding to the second key environment influence data.

Step S133, performing scheduling dimension value-based cascade connection on the scheduling control target and the non-scheduling control target to obtain environment control update information corresponding to the current environment control behavior data and the current environment configuration data; clustering the environment control updating information to obtain clustering information corresponding to the current environment control behavior data and the current environment configuration data; and under the condition that the clustering information meets a preset condition, acquiring key environment influence data matched with the clustering category from the current environment control behavior data and the current environment configuration data through the clustering category indicated by the clustering information as the target environment related influence data. In this embodiment, the scheduling dimension value can reflect the relevant information of the environmental control update information to a certain extent, and thus based on the steps S131 to S133, the target environmental relevant influence data can be accurately extracted, so as to provide an accurate data basis for the generation of the subsequent temperature and humidity detection control curve and the subsequent data mining.

In this embodiment, the cascading the scheduling control target and the non-scheduling control target based on the scheduling dimension value to obtain the environment control update information corresponding to the current environment control behavior data and the current environment configuration data includes: and calling a data cascade layer in the preset data component extraction network, and carrying out cascade connection on the scheduling control target and the non-scheduling control target based on a scheduling dimension value to obtain environment control updating information corresponding to the current environment control behavior data and the current environment configuration data.

Further, in order to quickly and flexibly determine the temperature and humidity detection control behavior of the temperature and humidity detection controller, the generating of the temperature and humidity detection control curve according to the temperature and humidity influence attribute and the target environment related influence data described in step S130 to determine the temperature and humidity detection control behavior of the temperature and humidity detection controller according to the temperature and humidity detection control curve may include the following contents: acquiring positive feedback adjustment rule information and negative feedback adjustment rule information in the target environment related influence data according to the environment control rule information corresponding to the temperature and humidity influence attribute; performing feedback curve analysis on the positive feedback adjustment rule information and the negative feedback adjustment rule information in the target environment-related influence data based on adjustment synchronization information between the positive feedback adjustment rule information and the negative feedback adjustment rule information in the target environment-related influence data to obtain feedback curve analysis information; determining negative feedback adjustment rule information of linkage nodes existing in feedback curve analysis as reference negative feedback adjustment rule information, and determining regulation time sequence information matched with the reference negative feedback adjustment rule information according to curve change information between the negative feedback adjustment rule information in the feedback curve analysis information and the reference negative feedback adjustment rule information; performing feedback curve analysis on the adjusting time sequence information matched with the reference negative feedback adjustment rule information and the reference negative feedback adjustment rule information to obtain feedback curve instruction analysis information; according to the feedback curve instruction analysis information and the feedback curve analysis information, determining a temperature and humidity detection control curve in the target environment related influence data and a temperature and humidity control sequence corresponding to the temperature and humidity detection control curve; the temperature and humidity control sequence comprises different temperature and humidity control instruction information corresponding to the temperature and humidity detection control curve; and obtaining the temperature and humidity detection control behavior according to the temperature and humidity detection control curve information and the temperature and humidity control sequence corresponding to the temperature and humidity detection control curve information.

Fig. 3 is a schematic functional module diagram of a temperature and humidity detection control apparatus 300 for raw materials for feed production according to an embodiment of the present invention, and in this embodiment, functional modules of the temperature and humidity detection control apparatus 300 for raw materials for feed production may be divided according to a method embodiment executed by the server 100, that is, the following functional modules corresponding to the temperature and humidity detection control apparatus 300 for raw materials for feed production may be used to execute each method embodiment executed by the server 100. The functions of the functional modules of the temperature and humidity detection control apparatus 300 for raw materials for feed production are explained in detail below.

The obtaining module 310 is configured to obtain current environmental control behavior data and current environmental configuration data extracted by the temperature and humidity detection controller at a storage stage of raw materials for feed production to be reached, and input the current environmental control behavior data and the current environmental configuration data into the temperature and humidity detection control unit.

The identification module 320 is configured to perform temperature and humidity influence attribute identification on the current environment control behavior data and the current environment configuration data through the temperature and humidity detection control unit, so as to obtain a temperature and humidity influence attribute corresponding to the current environment control behavior data and the current environment configuration data.

A generating module 330, configured to obtain corresponding target environment-related influence data from the current environment control behavior data and the current environment configuration data according to the temperature and humidity influence attribute, and generate a temperature and humidity detection control curve according to the temperature and humidity influence attribute and the target environment-related influence data, so as to determine a temperature and humidity detection control behavior of the temperature and humidity detection controller according to the temperature and humidity detection control curve.

It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the obtaining module 310 may be a processing element separately set up, or may be implemented by being integrated into a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and the processing element of the apparatus calls and executes the functions of the obtaining module 310. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).

Fig. 4 is a schematic diagram illustrating a hardware structure of a server 100 for implementing the temperature and humidity detection control method for raw materials for feed production according to an embodiment of the present invention, and as shown in fig. 4, the server 100 may include a processor 110, a machine-readable storage medium 120, a bus 130, and a transceiver 140.

In a specific implementation process, at least one processor 110 executes computer-executable instructions stored in the machine-readable storage medium 120 (for example, the obtaining module 310, the generating module 320, the determining module 330, and the adapting module 340 included in the apparatus 300 for controlling temperature and humidity detection of raw materials for feed production shown in fig. 3), so that the processor 110 can execute the method for controlling temperature and humidity detection of raw materials for feed production according to the above method embodiment, where the processor 110, the machine-readable storage medium 120, and the transceiver 140 are connected through the bus 130, and the processor 110 can be configured to control the transceiver 140 to perform transceiving actions, so as to perform data transceiving with the temperature and humidity detection controller 200.

For a specific implementation process of the processor 110, reference may be made to the above-mentioned method embodiments executed by the server 100, which implement similar principles and technical effects, and this embodiment is not described herein again.

In the embodiment shown in fig. 4, it should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.

The machine-readable storage medium 120 may comprise high-speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.

The bus 130 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus 130 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the buses in the figures of the present invention are not limited to only one bus or one type of bus.

In addition, an embodiment of the present invention further provides a readable storage medium, where a computer executing instruction is stored in the readable storage medium, and when a processor executes the computer executing instruction, the temperature and humidity detection control method for the raw materials for feed production is implemented.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.

Also, the description uses specific words to describe embodiments of the description. Such as "one embodiment," "one possible example," and/or "exemplary" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment," "one possible example," and/or "exemplary" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims

1. A temperature and humidity detection control method for raw materials for feed production is characterized by being applied to a server, wherein the server is in communication connection with a plurality of temperature and humidity detection controllers, and the method comprises the following steps:

2. The temperature and humidity detection control method of the raw materials for feed production according to claim 1, wherein the temperature and humidity detection control unit comprises a feature extraction structure and a classification output structure; the temperature and humidity influence attribute identification of the current environment control behavior data and the current environment configuration data through the temperature and humidity detection control unit to acquire the temperature and humidity influence attribute corresponding to the current environment control behavior data and the current environment configuration data includes:

3. The method for detecting and controlling temperature and humidity of raw materials for feed production according to claim 2, wherein the step of inputting the current environmental control behavior data and the current environmental configuration data into the feature extraction structure to perform feature extraction and temperature and humidity influence attribute mapping so as to obtain feature extraction information of temperature and humidity influence attributes corresponding to the current environmental control behavior data and the current environmental configuration data comprises the steps of:

4. The temperature and humidity detection control method of the raw material for feed production according to claim 1, wherein the temperature and humidity detection control unit is configured based on cycle reference environment control behavior data and a cycle reference environment configuration data set, and the temperature and humidity influence reference data set is obtained, and the cycle reference environment control behavior data and the cycle reference environment configuration data set are reference environment control behavior data and a cycle reference environment configuration data set in which the number of positive environment influence attributes and the number of negative environment influence attributes are inconsistent; the temperature and humidity influence reference data are determined according to an influence curve of a temperature and humidity influence attribute and an influence curve of a global temperature and humidity influence attribute, wherein the influence curve of the global temperature and humidity influence attribute is an influence curve of a global temperature and humidity influence attribute corresponding to each reference environment control behavior data and circulation reference environment configuration data in the circulation reference environment control behavior data and circulation reference environment configuration data set, the influence curve of the temperature and humidity influence attribute is an influence curve of a temperature and humidity influence attribute corresponding to the reference environment control behavior data and circulation reference environment configuration data acquired by the temperature and humidity detection control unit, and the temperature and humidity influence reference data include a first temperature and humidity influence reference object, a second temperature and humidity influence reference object and a reference object range, and the method further includes:

5. The method for detecting and controlling the temperature and humidity of the raw materials for the feed production according to claim 4, wherein the reference environment control behavior data and the cyclic reference environment configuration data set include a plurality of reference environment control behavior data and cyclic reference environment configuration data, and the reference temperature and humidity detection control unit includes a reference feature extraction structure and a reference classification output structure; the performing parameter optimization on a reference temperature and humidity detection control unit according to the reference environment control behavior data, the cyclic reference environment configuration data set and the influence curve of the global temperature and humidity influence attribute to obtain the temperature and humidity detection control unit includes:

6. The method for detecting and controlling temperature and humidity of raw materials for feed production according to claim 5, wherein the determining the temperature and humidity influence reference data according to the influence curve of the temperature and humidity influence attribute and the influence curve of the global temperature and humidity influence attribute corresponding to the reference environment control behavior data and the circulating reference environment configuration data comprises:

7. The method according to claim 6, wherein the generating the temperature and humidity influence reference data according to the second optimization information, the influence curve of the temperature and humidity influence attribute, the unit evaluation index of the temperature and humidity influence attribute, the environmental control time domain parameter of the positive environmental influence attribute, the environmental control frequent item parameter, and the reference object range includes:

8. The method for detecting and controlling the temperature and humidity of the raw materials for feed production according to claim 1, wherein obtaining corresponding target environment-related influence data from the current environment control behavior data and the current environment configuration data according to the temperature and humidity influence attribute comprises:

9. The method for controlling temperature and humidity detection of raw materials for feed production according to claim 8, wherein generating a temperature and humidity detection control curve according to the temperature and humidity influence attribute and the target environment-related influence data to determine a temperature and humidity detection control behavior of the temperature and humidity detection controller according to the temperature and humidity detection control curve comprises:

10. A temperature and humidity detection control system for raw materials for feed production is characterized by comprising a server and a temperature and humidity detection controller in communication connection with the server; the server is configured to: