Full-automatic gas cylinder cabinet control system

Abstract

The invention relates to a full-automatic gas cylinder cabinet control system, and belongs to the technical field of automation control. According to the system, gas cylinder cabinet data are collected through a sensor, a gas cylinder cabinet variable cooperation model is established through a principal component analysis method to obtain a gas cylinder cabinet abnormal information set, and a gas cylinder cabinet abnormal mapping value set is obtained through reverse mapping according to the gas cylinder cabinet abnormal information set. Generating a gas cylinder cabinet independent control instruction value set according to the gas cylinder cabinet abnormal mapping value set; a gas cylinder cabinet regulation and control information set is generated according to the gas cylinder cabinet independent control instruction value set, gas cylinder cabinet parameters are dynamically adjusted through a closed-loop feedback system, and a gas cylinder cabinet maintenance prediction model is obtained through random forest algorithm training and testing according to a gas cylinder cabinet historical data set; according to the gas cylinder cabinet data, a gas cylinder cabinet fault state label is obtained through the gas cylinder cabinet maintenance prediction model, a gas cylinder cabinet maintenance reminding instruction is generated, and the functions of intelligent gas cylinder cabinet parameter adjustment and predictive maintenance reminding are achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of automatic control, and in particular relates to a full-automatic gas cylinder cabinet control system. Background Art

[0002] Gas cylinder cabinet control systems are mainly used in laboratories, industrial production and other fields to store, distribute and manage gases in gas cylinders. With the continuous development of science and technology, gas cylinder cabinet control systems have achieved certain technical results, but the following problems still exist: relying on manual intervention to adjust and monitor gas cylinder cabinet parameters, resulting in high labor costs and low efficiency; lack of intelligent parameter adjustment function, unable to achieve automated management, complex operation and low efficiency; in addition, gas cylinder cabinet maintenance work often relies on operators to actively discover and solve problems, lack of active early warning mechanism, making it impossible to respond to the maintenance needs of gas cylinder cabinets in real time, which can easily lead to gas supply interruption and even cause safety problems. Summary of the invention

[0003] In order to solve the above problems existing in the prior art, the present invention provides a fully automatic gas cylinder cabinet control system, which intelligently analyzes the abnormal information of the gas cylinder cabinet by building a gas cylinder cabinet variable collaborative model according to real-time gas cylinder cabinet data and generates independent control instructions for the gas cylinder cabinet through gas cylinder cabinet abnormal mapping, thereby realizing dynamic adjustment of gas cylinder cabinet parameters, reducing manual intervention and labor costs, while improving the accuracy and reliability of gas cylinder cabinet control, and realizing efficient automatic gas cylinder cabinet management; at the same time, the predictive maintenance function of the gas cylinder cabinet is realized to ensure the safe operation of the gas cylinder cabinet, while reducing maintenance costs and failure risks, and improving the overall performance and efficiency of the gas cylinder cabinet control system;

[0004] The purpose of the present invention can be achieved by the following technical solutions:

[0005] A fully automatic gas cylinder cabinet control method, comprising:

[0006] S1: Collecting gas cylinder cabinet data through sensors, wherein the gas cylinder cabinet data includes gas cylinder cabinet temperature data, gas cylinder cabinet humidity data, and gas cylinder cabinet pressure data;

[0007] S2: establishing a gas cylinder cabinet variable collaborative model based on the gas cylinder cabinet data by principal component analysis to obtain a gas cylinder cabinet abnormal information set;

[0008] S3: Obtain a gas cylinder cabinet abnormality mapping value set through reverse mapping according to the gas cylinder cabinet abnormality information set, and generate a gas cylinder cabinet independent control instruction value set according to the gas cylinder cabinet abnormality mapping value set;

[0009] S4: generating a gas cylinder cabinet control information set according to the gas cylinder cabinet independent control instruction value set, and dynamically adjusting the gas cylinder cabinet parameters through a closed-loop feedback system according to the gas cylinder cabinet control information set;

[0010] S5: Acquire historical data of the gas cylinder cabinet, construct a historical data set of the gas cylinder cabinet according to the historical data of the gas cylinder cabinet, and obtain a maintenance prediction model of the gas cylinder cabinet by training and testing the historical data set of the gas cylinder cabinet through a random forest algorithm;

[0011] S6: Obtain a gas cylinder cabinet fault status label according to the gas cylinder cabinet data through the gas cylinder cabinet maintenance prediction model, and generate a gas cylinder cabinet maintenance reminder instruction according to the gas cylinder cabinet fault status label.

[0012] Preferably, the step S2 specifically includes the following steps:

[0013] S201: Obtaining a gas cylinder cabinet covariance matrix set according to the gas cylinder cabinet data through the gas cylinder cabinet variable relationship, wherein the expression of the gas cylinder cabinet variable relationship is:

[0014]

[0015] Among them, x is the original matrix of gas cylinder cabinet data, is the mean vector of gas cylinder cabinet data, and n is the number of gas cylinder cabinet data samples;

[0016] S202: Obtain a gas cylinder cabinet feature vector set and a gas cylinder cabinet feature set by eigendecomposition according to the gas cylinder cabinet covariance matrix set, wherein the expression of the eigendecomposition is:

[0017]

[0018] Among them, λ i is the gas cylinder cabinet eigenvalue, eig(X) is the gas cylinder cabinet eigenvector;

[0019] S203: Obtain a gas cylinder cabinet principal component information set according to the gas cylinder cabinet feature vector set and the gas cylinder cabinet feature value set by accumulating variance contribution rate, construct a gas cylinder cabinet principal component matrix set according to the gas cylinder cabinet principal component information set, construct a gas cylinder cabinet original matrix according to the gas cylinder cabinet data, and obtain a gas cylinder cabinet principal component score set by element-by-element multiplication of the gas cylinder cabinet data original matrix according to the gas cylinder cabinet principal component matrix set;

[0020] S204: The abnormal information set of the gas cylinder cabinet is obtained by identifying the abnormal information set of the gas cylinder cabinet according to the main component information set of the gas cylinder cabinet and the main component score set of the gas cylinder cabinet through the Z-score statistical method. The abnormal information set of the gas cylinder cabinet is the main component set of the gas cylinder cabinets in the main component information set of the gas cylinder cabinet whose absolute value of the Z-score of the gas cylinder cabinet is greater than 3. The expression of the Z-score statistical method is:

[0021]

[0022] Among them, pscore is the main component score of the gas cylinder cabinet, pmean is the mean of the main component score of the gas cylinder cabinet, psd is the standard deviation of the main component score of the gas cylinder cabinet, and Z is the Z score of the gas cylinder cabinet.

[0023] Preferably, the step S3 specifically includes the following steps:

[0024] S301: Obtain a gas cylinder cabinet abnormal information score set by calculating a gas cylinder cabinet abnormal score according to the gas cylinder cabinet abnormal information set and the gas cylinder cabinet principal component score set. The calculation formula of the gas cylinder cabinet abnormal score is:

[0025] S=p score -p mean

[0026] Among them, pscore is the main component score of the gas cylinder cabinet, pmean is the mean of the main component score of the gas cylinder cabinet, and S is the abnormal information score of the gas cylinder cabinet;

[0027] S302: constructing a gas cylinder cabinet load matrix by multiplying the gas cylinder cabinet covariance matrix set and the gas cylinder cabinet feature vector set according to the gas cylinder cabinet abnormality information set;

[0028] S303: obtaining a gas cylinder cabinet abnormality mapping value set by multiplying the gas cylinder cabinet abnormality information score and the gas cylinder cabinet load matrix according to the gas cylinder cabinet abnormality information set, wherein the gas cylinder cabinet abnormality mapping value set is a set of abnormal value parameters in the gas cylinder cabinet data;

[0029] S304: taking the absolute value of the gas cylinder cabinet load matrix according to the gas cylinder cabinet abnormality information set to obtain a gas cylinder cabinet abnormal value parameter weight set;

[0030] S305: Generate the gas cylinder cabinet independent control instruction value set according to the gas cylinder cabinet abnormal mapping value set, through the gas cylinder cabinet abnormal control target value and the gas cylinder cabinet abnormal value parameter weight set, and the specific expression is:

[0031]

[0032] M=weight*C

[0033] in, For the abnormal mapping value of the gas cylinder cabinet, is the mean value of the abnormal mapping value of the gas cylinder cabinet, C is the abnormal control target value of the gas cylinder cabinet, weight is the abnormal value parameter weight of the gas cylinder cabinet, and M is the independent control instruction value of the gas cylinder cabinet.

[0034] Preferably, generating the gas cylinder cabinet control information set according to the gas cylinder cabinet independent control instruction value set in step S4 includes:

[0035] When the independent control instruction value of the gas cylinder cabinet is greater than zero, the gas cylinder cabinet control information is an increase parameter and the increase value is the absolute value of the independent control instruction value of the gas cylinder cabinet;

[0036] When the independent control instruction value of the gas cylinder cabinet is less than zero, the gas cylinder cabinet regulation information is a lowering parameter and the lowering value is the absolute value of the independent control instruction value of the gas cylinder cabinet.

[0037] Preferably, in step S4, dynamically adjusting the gas cylinder cabinet parameters through a closed-loop feedback system according to the gas cylinder cabinet control information set includes:

[0038] According to the gas cylinder cabinet data, a closed-loop feedback system is used to check whether the actual parameter value deviates from the set value. When the actual parameter value deviates from the set value, the actuator is controlled to dynamically adjust the gas cylinder cabinet parameters according to the gas cylinder cabinet control information set.

[0039] Preferably, the step S5 specifically includes the following steps:

[0040] S501: The gas cylinder cabinet historical data set includes a gas cylinder cabinet historical fault state label and a gas cylinder cabinet historical environmental condition data, the gas cylinder cabinet historical fault state label includes a gas cylinder cabinet historical normal state label and a gas cylinder cabinet historical abnormal state label, and the gas cylinder cabinet historical environmental condition data includes a gas cylinder cabinet historical temperature data, a gas cylinder cabinet historical humidity data, and a gas cylinder cabinet historical gas cylinder cabinet pressure data;

[0041] S502: obtaining a standard set of historical data of the gas cylinder cabinet by data preprocessing according to the historical data set of the gas cylinder cabinet, wherein the data preprocessing includes data cleaning and data standardization;

[0042] S503: Obtaining a gas cylinder cabinet historical feature vector set by feature extraction according to the gas cylinder cabinet historical data standard set;

[0043] S504: A gas cylinder cabinet maintenance prediction model is obtained by training and testing the gas cylinder cabinet historical feature vector set through a random forest algorithm.

[0044] Preferably, the step S6 specifically includes the following steps:

[0045] S601: Evaluate the current state of the gas cylinder cabinet through the gas cylinder cabinet maintenance prediction model according to the gas cylinder cabinet data to obtain the gas cylinder cabinet fault state label;

[0046] S602: Generate a gas cylinder cabinet maintenance reminder instruction according to the gas cylinder cabinet fault state tag, and generate a gas cylinder cabinet maintenance reminder instruction when the gas cylinder cabinet fault state tag is a gas cylinder cabinet abnormal state tag.

[0047] A fully automatic gas cylinder cabinet control system, including a sensor module, a control module, a feedback adjustment module, and a maintenance reminder module;

[0048] The sensor module is used to monitor the operating data of the gas cylinder cabinet in real time; the control module is used to analyze the operating data of the gas cylinder cabinet to generate independent control instructions for the gas cylinder cabinet; the feedback adjustment module is used to continuously monitor the real-time operating status of the gas cylinder cabinet and dynamically adjust the gas cylinder cabinet parameters according to the independent control instructions of the gas cylinder cabinet; the maintenance reminder module is used to predict the fault status label of the gas cylinder cabinet and generate a maintenance reminder for the gas cylinder cabinet.

[0049] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned fully automatic gas cylinder cabinet control method when executing the program.

[0050] A storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute the above-mentioned fully automatic gas cylinder cabinet control method when executed by a computer processor.

[0051] The beneficial effects of the present invention are:

[0052] (1) The temperature, humidity, and pressure data of the gas cylinder cabinet are monitored in real time through the sensor module. The variable collaborative model of the gas cylinder cabinet is established by combining the principal component analysis method, thus realizing real-time monitoring and accurate analysis of the gas cylinder cabinet environment.

[0053] (2) The abnormal information of the gas cylinder cabinet is extracted through the principal component analysis method, and the abnormal mapping value of the gas cylinder cabinet is obtained through reverse mapping to generate independent control instructions for the gas cylinder cabinet, so as to quickly respond to abnormal situations and ensure the safe operation of the gas cylinder cabinet.

[0054] (3) The closed-loop feedback system monitors the gas cylinder cabinet parameters in real time and makes intelligent dynamic adjustments to ensure that the parameters are stable within the set range, reducing manual intervention, while improving the accuracy and reliability of gas cylinder cabinet control and achieving efficient automated gas cylinder cabinet management.

[0055] (4) A gas cylinder cabinet maintenance prediction model is obtained through random forest algorithm training and testing. The fault status label is predicted according to the gas cylinder cabinet data and the gas cylinder cabinet maintenance reminder instruction is generated, which realizes the predictive maintenance management of the gas cylinder cabinet and reduces the maintenance cost and failure risk. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0057] Figure 1 The present invention is a flowchart of a fully automatic gas cylinder cabinet control method. DETAILED DESCRIPTION

[0058] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0059] See also Figure 1 , a fully automatic gas cylinder cabinet control method, comprising:

[0060] S1: Collecting gas cylinder cabinet data through sensors, wherein the gas cylinder cabinet data includes gas cylinder cabinet temperature data, gas cylinder cabinet humidity data, and gas cylinder cabinet pressure data;

[0061] S2: establishing a gas cylinder cabinet variable collaborative model based on the gas cylinder cabinet data by principal component analysis to obtain a gas cylinder cabinet abnormal information set;

[0062] S3: Obtain a gas cylinder cabinet abnormality mapping value set through reverse mapping according to the gas cylinder cabinet abnormality information set, and generate a gas cylinder cabinet independent control instruction value set according to the gas cylinder cabinet abnormality mapping value set;

[0063] S4: generating a gas cylinder cabinet control information set according to the gas cylinder cabinet independent control instruction value set, and dynamically adjusting the gas cylinder cabinet parameters through a closed-loop feedback system according to the gas cylinder cabinet control information set;

[0064] S5: Acquire historical data of the gas cylinder cabinet, construct a historical data set of the gas cylinder cabinet according to the historical data of the gas cylinder cabinet, and obtain a maintenance prediction model of the gas cylinder cabinet by training and testing the historical data set of the gas cylinder cabinet through a random forest algorithm;

[0065] S6: Obtain a gas cylinder cabinet fault status label according to the gas cylinder cabinet data through the gas cylinder cabinet maintenance prediction model, and generate a gas cylinder cabinet maintenance reminder instruction according to the gas cylinder cabinet fault status label.

[0066] In step S2, a gas cylinder cabinet variable collaborative model is established based on the gas cylinder cabinet data by principal component analysis to obtain a gas cylinder cabinet abnormal information set, which specifically includes the following steps:

[0067] S201: Obtaining a gas cylinder cabinet covariance matrix set according to the gas cylinder cabinet data through the gas cylinder cabinet variable relationship, wherein the expression of the gas cylinder cabinet variable relationship is:

[0068]

[0069] Among them, x is the original matrix of gas cylinder cabinet data, is the mean vector of gas cylinder cabinet data, and n is the number of gas cylinder cabinet data samples;

[0070] S202: Obtain a gas cylinder cabinet feature vector set and a gas cylinder cabinet feature set by eigendecomposition according to the gas cylinder cabinet covariance matrix set, wherein the expression of the eigendecomposition is:

[0071]

[0072] Among them, λ i is the gas cylinder cabinet eigenvalue, eig(X) is the gas cylinder cabinet eigenvector;

[0073] S203: Obtain a gas cylinder cabinet principal component information set according to the gas cylinder cabinet feature vector set and the gas cylinder cabinet feature value set by accumulating variance contribution rate, construct a gas cylinder cabinet principal component matrix set according to the gas cylinder cabinet principal component information set, construct a gas cylinder cabinet original matrix according to the gas cylinder cabinet data, and obtain a gas cylinder cabinet principal component score set by element-by-element multiplication of the gas cylinder cabinet data original matrix according to the gas cylinder cabinet principal component matrix set;

[0074] S204: The abnormal information set of the gas cylinder cabinet is obtained by identifying the abnormal information set of the gas cylinder cabinet according to the main component information set of the gas cylinder cabinet and the main component score set of the gas cylinder cabinet through the Z-score statistical method. The abnormal information set of the gas cylinder cabinet is the main component set of the gas cylinder cabinets in the main component information set of the gas cylinder cabinet whose absolute value of the Z-score of the gas cylinder cabinet is greater than 3. The expression of the Z-score statistical method is:

[0075]

[0076] Among them, pscore is the main component score of the gas cylinder cabinet, pmean is the mean of the main component score of the gas cylinder cabinet, psd is the standard deviation of the main component score of the gas cylinder cabinet, and Z is the Z score of the gas cylinder cabinet;

[0077] In step S3, a gas cylinder cabinet abnormality mapping value set is obtained by reverse mapping according to the gas cylinder cabinet abnormality information set, and a gas cylinder cabinet independent control instruction set is generated according to the gas cylinder cabinet abnormality mapping value set, which specifically includes the following steps:

[0078] S301: Obtain a gas cylinder cabinet abnormal information score set by calculating a gas cylinder cabinet abnormal score according to the gas cylinder cabinet abnormal information set and the gas cylinder cabinet principal component score set. The calculation formula of the gas cylinder cabinet abnormal score is:

[0079] S=p score -p mean

[0080] Among them, pscore is the main component score of the gas cylinder cabinet, pmean is the mean of the main component score of the gas cylinder cabinet, and S is the abnormal information score of the gas cylinder cabinet;

[0081] S302: constructing a gas cylinder cabinet load matrix by multiplying the gas cylinder cabinet covariance matrix set and the gas cylinder cabinet feature vector set according to the gas cylinder cabinet abnormality information set;

[0082] S303: obtaining a gas cylinder cabinet abnormality mapping value set by multiplying the gas cylinder cabinet abnormality information score and the gas cylinder cabinet load matrix according to the gas cylinder cabinet abnormality information set, wherein the gas cylinder cabinet abnormality mapping value set is a set of abnormal value parameters in the gas cylinder cabinet data;

[0083] S304: Obtaining a gas cylinder cabinet abnormal value parameter weight set by taking an absolute value through the gas cylinder cabinet load matrix according to the gas cylinder cabinet abnormality information set;

[0084] S305: Generate the gas cylinder cabinet independent control instruction value set according to the gas cylinder cabinet abnormal mapping value set, through the gas cylinder cabinet abnormal control target value and the gas cylinder cabinet abnormal value parameter weight set, and the specific expression is:

[0085]

[0086] M=weight*C

[0087] in, For the abnormal mapping value of the gas cylinder cabinet, is the mean value of the abnormal mapping value of the gas cylinder cabinet, C is the abnormal control target value of the gas cylinder cabinet, weight is the abnormal value parameter weight of the gas cylinder cabinet, and M is the independent control instruction value of the gas cylinder cabinet;

[0088] In step S4, generating the gas cylinder cabinet control information set according to the gas cylinder cabinet independent control instruction value set includes:

[0089] When the independent control instruction value of the gas cylinder cabinet is greater than zero, the gas cylinder cabinet control information is an increase parameter and the increase value is the absolute value of the independent control instruction value of the gas cylinder cabinet;

[0090] When the independent control instruction value of the gas cylinder cabinet is less than zero, the gas cylinder cabinet regulation information is a lowering parameter and the lowering value is the absolute value of the independent control instruction value of the gas cylinder cabinet.

[0091] In step S4, dynamically adjusting the gas cylinder cabinet parameters through a closed-loop feedback system according to the gas cylinder cabinet control information set includes:

[0092] According to the gas cylinder cabinet data, a closed-loop feedback system is used to check whether the actual parameter value deviates from the set value. When the actual parameter value deviates from the set value, the actuator is controlled to dynamically adjust the gas cylinder cabinet parameters according to the gas cylinder cabinet control information set.

[0093] In step S5, a gas cylinder cabinet maintenance prediction model is obtained by training and testing the gas cylinder cabinet historical data set through a random forest algorithm, which specifically includes the following steps:

[0094] S501: The gas cylinder cabinet historical data set includes a gas cylinder cabinet historical fault state label and a gas cylinder cabinet historical environmental condition data, the gas cylinder cabinet historical fault state label includes a gas cylinder cabinet historical normal state label and a gas cylinder cabinet historical abnormal state label, and the gas cylinder cabinet historical environmental condition data includes a gas cylinder cabinet historical temperature data, a gas cylinder cabinet historical humidity data, and a gas cylinder cabinet historical gas cylinder cabinet pressure data;

[0095] S502: obtaining a standard set of historical data of the gas cylinder cabinet by data preprocessing according to the historical data set of the gas cylinder cabinet, wherein the data preprocessing includes data cleaning and data standardization;

[0096] S503: Obtaining a gas cylinder cabinet historical feature vector set by feature extraction according to the gas cylinder cabinet historical data standard set;

[0097] S504: A gas cylinder cabinet maintenance prediction model is obtained by training and testing the gas cylinder cabinet historical feature vector set through a random forest algorithm, specifically comprising the following steps:

[0098] S504-1: obtaining a gas cylinder cabinet training set and a gas cylinder cabinet test set by dividing the data set according to the gas cylinder cabinet historical data standard set;

[0099] S504-2: sampling N times with replacement sampling strategy according to the gas cylinder cabinet training set to obtain a gas cylinder cabinet training set, where N is the number of samples in the gas cylinder cabinet training set;

[0100] S504-3: Select the gas cylinder cabinet feature vector set through a random selection strategy features to obtain the gas cylinder cabinet feature set, where m is the number of samples of the gas cylinder cabinet feature vector set;

[0101] S504-4: Obtaining a decision tree through training according to the gas cylinder cabinet training set and the gas cylinder cabinet feature set;

[0102] S504-5: obtaining an initial gas cylinder cabinet maintenance prediction model through a random forest generation method according to the gas cylinder cabinet training set, wherein the random forest generation method is to repeat the process from step S504-2 to step S504-4 k times to obtain a random forest, wherein k is the size of the random forest, and the size of the random forest is the number of decision trees contained in the random forest;

[0103] S504-6: According to the gas cylinder cabinet test set, the initial gas cylinder cabinet maintenance prediction model is tested to obtain an initial gas cylinder cabinet maintenance prediction model test result, and according to the initial gas cylinder cabinet maintenance prediction model test result, the gas cylinder cabinet maintenance prediction model evaluation index is calculated to obtain a gas cylinder cabinet maintenance prediction model evaluation result, and the gas cylinder cabinet maintenance prediction model evaluation index is the gas cylinder cabinet maintenance prediction model accuracy, and the calculation formula is:

[0104]

[0105] Among them, ACC is the accuracy of the initial gas cylinder cabinet maintenance prediction model, TP is the number of samples that are actually abnormal and correctly predicted as abnormal by the initial gas cylinder cabinet maintenance prediction model, FP is the number of samples that are actually normal but are incorrectly predicted as abnormal by the model according to the initial gas cylinder cabinet maintenance prediction model, TN is the number of samples that are actually normal and correctly predicted as normal by the model according to the initial gas cylinder cabinet maintenance prediction model, and FN is the number of samples that are actually abnormal but are incorrectly predicted as normal by the model according to the initial gas cylinder cabinet maintenance prediction model;

[0106] S504-7: Obtain the gas cylinder cabinet maintenance prediction model according to the evaluation result of the gas cylinder cabinet maintenance prediction model. When the accuracy rate of the initial gas cylinder cabinet maintenance prediction model reaches 90%, the initial gas cylinder cabinet maintenance prediction model is the gas cylinder cabinet maintenance prediction model.

[0107] In step S6, a gas cylinder cabinet fault status label is obtained according to the gas cylinder cabinet data through the gas cylinder cabinet maintenance prediction model, and a gas cylinder cabinet maintenance reminder instruction is generated according to the gas cylinder cabinet fault status label, which specifically includes the following steps:

[0108] S601: Evaluate the current state of the gas cylinder cabinet through the gas cylinder cabinet maintenance prediction model according to the gas cylinder cabinet data to obtain the gas cylinder cabinet fault state label;

[0109] S602: Generate a gas cylinder cabinet maintenance reminder instruction according to the gas cylinder cabinet fault state tag, and generate a gas cylinder cabinet maintenance reminder instruction when the gas cylinder cabinet fault state tag is a gas cylinder cabinet abnormal state tag.

[0110] A fully automatic gas cylinder cabinet control system includes a sensor module, a control module, a feedback adjustment module, and a maintenance reminder module;

[0111] The sensor module is used to monitor the operating data of the gas cylinder cabinet in real time; the control module is used to analyze the operating data of the gas cylinder cabinet to generate independent control instructions for the gas cylinder cabinet; the feedback adjustment module is used to continuously monitor the real-time operating status of the gas cylinder cabinet and dynamically adjust the gas cylinder cabinet parameters according to the independent control instructions of the gas cylinder cabinet; the maintenance reminder module is used to predict the fault status label of the gas cylinder cabinet and generate a maintenance reminder for the gas cylinder cabinet.

[0112] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0113] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0114] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0115] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A fully automatic gas cylinder cabinet control method, characterized in that: include: S1: Collecting gas cylinder cabinet data through sensors, wherein the gas cylinder cabinet data includes gas cylinder cabinet temperature data, gas cylinder cabinet humidity data, and gas cylinder cabinet pressure data; S2: establishing a gas cylinder cabinet variable collaborative model based on the gas cylinder cabinet data by principal component analysis to obtain a gas cylinder cabinet abnormal information set; S3: Obtain a gas cylinder cabinet abnormality mapping value set through reverse mapping according to the gas cylinder cabinet abnormality information set, and generate a gas cylinder cabinet independent control instruction value set according to the gas cylinder cabinet abnormality mapping value set; S4: generating a gas cylinder cabinet control information set according to the gas cylinder cabinet independent control instruction value set, and dynamically adjusting the gas cylinder cabinet parameters through a closed-loop feedback system according to the gas cylinder cabinet control information set; S5: Acquire historical data of the gas cylinder cabinet, construct a historical data set of the gas cylinder cabinet according to the historical data of the gas cylinder cabinet, and obtain a maintenance prediction model of the gas cylinder cabinet by training and testing the historical data set of the gas cylinder cabinet through a random forest algorithm; S6: Obtain a gas cylinder cabinet fault status label according to the gas cylinder cabinet data through the gas cylinder cabinet maintenance prediction model, and generate a gas cylinder cabinet maintenance reminder instruction according to the gas cylinder cabinet fault status label.

2. The fully automatic gas cylinder cabinet control method according to claim 1, characterized in that: The step S2 specifically includes the following steps: S201: Obtaining a gas cylinder cabinet covariance matrix set according to the gas cylinder cabinet data through the gas cylinder cabinet variable relationship, wherein the expression of the gas cylinder cabinet variable relationship is: Among them, x is the original matrix of gas cylinder cabinet data, is the mean vector of gas cylinder cabinet data, and n is the number of gas cylinder cabinet data samples; S202: Obtaining a gas cylinder cabinet feature vector set and a gas cylinder cabinet feature set by eigendecomposition according to the gas cylinder cabinet covariance matrix set, wherein the expression of the eigendecomposition is: Among them, λ i is the gas cylinder cabinet eigenvalue, eig(X) is the gas cylinder cabinet eigenvector; S203: Obtain a gas cylinder cabinet principal component information set according to the gas cylinder cabinet feature vector set and the gas cylinder cabinet feature value set by accumulating variance contribution rate, construct a gas cylinder cabinet principal component matrix set according to the gas cylinder cabinet principal component information set, construct a gas cylinder cabinet original matrix according to the gas cylinder cabinet data, and obtain a gas cylinder cabinet principal component score set by element-by-element multiplication of the gas cylinder cabinet data original matrix according to the gas cylinder cabinet principal component matrix set; S204: The abnormal information set of the gas cylinder cabinet is obtained by identifying the abnormal information set of the gas cylinder cabinet according to the main component information set of the gas cylinder cabinet and the main component score set of the gas cylinder cabinet through the Z-score statistical method. The abnormal information set of the gas cylinder cabinet is the main component set of the gas cylinder cabinets in the main component information set of the gas cylinder cabinet whose absolute value of the Z-score of the gas cylinder cabinet is greater than 3. The expression of the Z-score statistical method is: Among them, pscore is the main component score of the gas cylinder cabinet, pmean is the mean of the main component score of the gas cylinder cabinet, psd is the standard deviation of the main component score of the gas cylinder cabinet, and Z is the Z score of the gas cylinder cabinet.

3. The fully automatic gas cylinder cabinet control method according to claim 1, characterized in that: The step S3 specifically comprises the following steps: S301: Obtain a gas cylinder cabinet abnormal information score set by calculating a gas cylinder cabinet abnormal score according to the gas cylinder cabinet abnormal information set and the gas cylinder cabinet principal component score set. The calculation formula of the gas cylinder cabinet abnormal score is: S=p score -p mean Among them, pscore is the main component score of the gas cylinder cabinet, pmean is the mean of the main component score of the gas cylinder cabinet, and S is the abnormal information score of the gas cylinder cabinet; S302: constructing a gas cylinder cabinet load matrix by multiplying the gas cylinder cabinet covariance matrix set and the gas cylinder cabinet feature vector set according to the gas cylinder cabinet abnormality information set; S303: obtaining a gas cylinder cabinet abnormality mapping value set by multiplying the gas cylinder cabinet abnormality information score and the gas cylinder cabinet load matrix according to the gas cylinder cabinet abnormality information set, wherein the gas cylinder cabinet abnormality mapping value set is a set of abnormal value parameters in the gas cylinder cabinet data; S304: taking the absolute value of the gas cylinder cabinet load matrix according to the gas cylinder cabinet abnormality information set to obtain a gas cylinder cabinet abnormal value parameter weight set; S305: Generate the gas cylinder cabinet independent control instruction value set according to the gas cylinder cabinet abnormal mapping value set, through the gas cylinder cabinet abnormal control target value and the gas cylinder cabinet abnormal value parameter weight set, and the specific expression is: M=weight*C in, For the abnormal mapping value of the gas cylinder cabinet, is the mean value of the abnormal mapping value of the gas cylinder cabinet, C is the abnormal control target value of the gas cylinder cabinet, weight is the abnormal value parameter weight of the gas cylinder cabinet, and M is the independent control instruction value of the gas cylinder cabinet.

4. The fully automatic gas cylinder cabinet control method according to claim 1, characterized in that: The step S4 of generating the gas cylinder cabinet control information set according to the gas cylinder cabinet independent control instruction value set includes: When the independent control instruction value of the gas cylinder cabinet is greater than zero, the gas cylinder cabinet control information is an increase parameter and the increase value is the absolute value of the independent control instruction value of the gas cylinder cabinet; When the independent control instruction value of the gas cylinder cabinet is less than zero, the gas cylinder cabinet regulation information is a lowering parameter and the lowering value is the absolute value of the independent control instruction value of the gas cylinder cabinet.

5. The fully automatic gas cylinder cabinet control method according to claim 1, characterized in that: The step S4 of dynamically adjusting the gas cylinder cabinet parameters through a closed-loop feedback system according to the gas cylinder cabinet control information set includes: According to the gas cylinder cabinet data, a closed-loop feedback system is used to check whether the actual parameter value deviates from the set value. When the actual parameter value deviates from the set value, the actuator is controlled to dynamically adjust the gas cylinder cabinet parameters according to the gas cylinder cabinet control information set.

6. The fully automatic gas cylinder cabinet control method according to claim 1, characterized in that: The step S5 specifically comprises the following steps: S501: The gas cylinder cabinet historical data set includes a gas cylinder cabinet historical fault state label and a gas cylinder cabinet historical environmental condition data, the gas cylinder cabinet historical fault state label includes a gas cylinder cabinet historical normal state label and a gas cylinder cabinet historical abnormal state label, and the gas cylinder cabinet historical environmental condition data includes a gas cylinder cabinet historical temperature data, a gas cylinder cabinet historical humidity data, and a gas cylinder cabinet historical gas cylinder cabinet pressure data; S502: obtaining a standard set of historical data of the gas cylinder cabinet by data preprocessing according to the historical data set of the gas cylinder cabinet, wherein the data preprocessing includes data cleaning and data standardization; S503: Obtaining a gas cylinder cabinet historical feature vector set by feature extraction according to the gas cylinder cabinet historical data standard set; S504: A gas cylinder cabinet maintenance prediction model is obtained by training and testing the gas cylinder cabinet historical feature vector set through a random forest algorithm.

7. The fully automatic gas cylinder cabinet control method according to claim 1, characterized in that: The step S6 specifically comprises the following steps: S601: Evaluate the current state of the gas cylinder cabinet through the gas cylinder cabinet maintenance prediction model according to the gas cylinder cabinet data to obtain the gas cylinder cabinet fault state label; S602: Generate a gas cylinder cabinet maintenance reminder instruction according to the gas cylinder cabinet fault state tag, and generate a gas cylinder cabinet maintenance reminder instruction when the gas cylinder cabinet fault state tag is a gas cylinder cabinet abnormal state tag.

8. A fully automatic gas cylinder cabinet control system, including a sensor module, a control module, a feedback adjustment module, and a maintenance reminder module, characterized in that: The sensor module is used to monitor the operating data of the gas cylinder cabinet in real time; the control module is used to analyze the operating data of the gas cylinder cabinet to generate independent control instructions for the gas cylinder cabinet; the feedback adjustment module is used to continuously monitor the real-time operating status of the gas cylinder cabinet and dynamically adjust the gas cylinder cabinet parameters according to the independent control instructions of the gas cylinder cabinet; the maintenance reminder module is used to predict the fault status label of the gas cylinder cabinet and generate a maintenance reminder for the gas cylinder cabinet.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the fully automatic gas cylinder cabinet control method as described in any one of claims 1-8 is implemented.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the fully automatic gas cylinder cabinet control method as described in any one of claims 1-8 when executed by a computer processor.

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