CN112667710A - Inverter overheating early warning method and device, computer equipment and storage medium - Google Patents
Inverter overheating early warning method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses an inverter overheating early warning method and device, computer equipment and a storage medium, and relates to the field of industrial control. The method comprises the following steps: receiving a user request; obtaining historical data of the inverter from a database; preprocessing historical data to obtain the working temperature and overload running time of the inverter; determining parameters of a preset binary regression prediction model according to the working temperature and the overload running time of the inverter to obtain an overheating fault rate model, and acquiring and preprocessing the real-time working temperature and the overload running time of the inverter; inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model to calculate the overheating fault rate of the inverter; whether an overheating fault early warning is sent is judged according to the overheating fault rate, so that the function of early warning of the overheating fault of the inverter is achieved, and good user experience is provided for users.
Description
Technical Field
The invention relates to the field of industrial control, in particular to an inverter overheating early warning method and device, computer equipment and a storage medium.
Background
With the progress of science and technology and society in recent years, the development of the internet of things is rapid, the value of the internet of things lies in data, and the data of the internet of things has the characteristics of diversity, heterogeneity, non-structure and the like and has extremely high growth speed. Traditional thing networking data directly uploads cloud platform through equipment, and cloud platform butt joint user application system and database, after the overheated trouble of dc-to-ac converter takes place, upload the overheated trouble data of dc-to-ac converter and forward to user application system to the cloud platform again, give the user trouble and remind, this process just sends out the trouble and reminds for the user after equipment has broken down, does not have the early warning function, and user experience is poor.
Disclosure of Invention
The embodiment of the invention provides an inverter overheating early warning method and device, computer equipment and a storage medium, and aims to solve the problems that an existing inverter overheating fault reminding function is not achieved, and user experience is poor.
In a first aspect, an embodiment of the present invention provides an inverter overheating warning method, where the method includes:
receiving a user request, wherein the request is used for subscribing the overheating early warning function of the inverter;
acquiring historical data of the inverter;
preprocessing the historical data to obtain the working temperature and overload running time of the inverter;
determining parameters of a preset binary regression prediction model according to the working temperature and the overload running time of the inverter to obtain overheatingA failure rate model, wherein the binary regression prediction model is Y ═ beta + beta1X1+β2X2Where Y is the inverter over-temperature failure rate, X1Is the operating temperature of the inverter, X2For the overload operation time of the inverter, beta1，β2Parameters of a binary regression prediction model;
acquiring the real-time working temperature and overload operation time of the inverter;
preprocessing the real-time working temperature and overload running time of the inverter;
inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model to calculate the overheating fault rate of the inverter;
and judging whether to send out overheating fault early warning according to the overheating fault rate.
In a second aspect, an embodiment of the present invention further provides an inverter overheating warning device, where the inverter overheating warning device includes:
the system comprises a receiving unit, a processing unit and a processing unit, wherein the receiving unit is used for receiving a user request which is used for subscribing the overheating early warning function of an inverter;
a first acquisition unit configured to acquire history data of the inverter;
the first preprocessing unit is used for preprocessing the historical data to obtain the working temperature and overload running time of the inverter;
a first calculating unit, configured to determine parameters of a preset binary regression prediction model according to the operating temperature and the overload operation time of the inverter to calculate an overheating fault rate model, where the binary regression prediction model is Y ═ β + β -1X1+β2X2Where Y is the inverter over-temperature failure rate, X1Is the operating temperature of the inverter, X2For the overload operation time of the inverter, beta1，β2Parameters of a binary regression prediction model;
a second acquisition unit for acquiring real-time operating temperature and overload operation time of the inverter
The second preprocessing unit is used for preprocessing the real-time working temperature and the overload running time of the inverter;
the second calculation unit is used for inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model so as to calculate the overheating fault rate of the inverter;
and the judging unit is used for judging whether to send out overheating fault early warning according to the overheating fault rate.
In a third aspect, an embodiment of the present invention further provides a computer device, where the computer device includes a memory and a processor, where the memory stores a computer program, and the processor implements the above method when executing the computer program.
In a fourth aspect, the present invention also provides a computer-readable storage medium, which stores a computer program, and the computer program realizes the above method when being executed by a processor.
The embodiment of the invention provides an inverter overheating early warning method, an inverter overheating early warning device, computer equipment and a storage medium, wherein the inverter overheating early warning method comprises the following steps: receiving a user request, wherein the request is used for subscribing the overheating early warning function of the inverter; obtaining historical data of the inverter from a database; preprocessing the historical data to obtain the working temperature and overload running time of the inverter; determining parameters of a preset binary regression prediction model according to the working temperature and the overload running time of the inverter to obtain an overheating fault rate model, and acquiring the real-time working temperature and the overload running time of the inverter; preprocessing the real-time working temperature and overload running time of the inverter; inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model to calculate the overheating fault rate of the inverter; and judging whether to send out overheating fault early warning according to the overheating fault rate. The embodiment of the invention realizes the function of early warning of the overheating fault of the inverter, improves the safety of the inverter in the using process, reduces the fault occurrence rate of the inverter and provides good experience for users.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic block diagram of an internet of things platform according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of an inverter overheating warning method according to an embodiment of the present invention;
fig. 3 is a schematic sub-flow chart of an inverter overheating warning method according to an embodiment of the present invention;
fig. 4 is a schematic sub-flow chart of an inverter overheating warning method according to an embodiment of the present invention;
fig. 5 is a schematic sub-flow chart of an inverter overheating warning method according to an embodiment of the present invention;
fig. 6 is a schematic block diagram of an inverter overheating warning device according to an embodiment of the present invention;
fig. 7 is a schematic block diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It is to be understood that the terms "includes" and "including" when used in this specification and the appended claims are also to be construed to indicate that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Referring to fig. 1, fig. 1 is a schematic block diagram of an internet of things platform 200 according to an embodiment of the present invention. As shown in the figure, the internet of things platform 200 includes a database 201, a second cloud platform 202, a plurality of first cloud platforms 203 and a plurality of inverter control terminals 204, each inverter control terminal 204 is connected with an inverter 205, each first cloud platform 203 is connected with a plurality of inverter control terminals 204, a plurality of first cloud platforms 203 are connected with the second cloud platform 202, and the second cloud platform 202 is connected with the database 201. The inverter overheating early warning method provided by the embodiment of the invention is applied to an inverter control terminal 204 in an internet of things platform 200, and before the receiving a user request, the inverter 205 overheating early warning method further includes:
instructing a plurality of the first cloud platforms 203 to send the collected data of the plurality of the inverters 205 to the second cloud platform 202;
instructing the second cloud platform 202 to store the received data of the plurality of inverters 205 in the database 201.
In a specific implementation, the inverter control terminal 204 instructs the plurality of first cloud platforms 203 to send the collected data of the plurality of inverters 205 to the second cloud platform 202; the inverter control terminal 204 instructs the second cloud platform 202 to store the received data of the plurality of inverters 205 in the database 201. So as to provide historical data of the operation of the inverter 205 when a user request is received to subscribe to the overheat warning function of the inverter 205, wherein the historical data of the operation of the inverter 205 includes data of the operating temperature of the inverter 205, the overload running time, the parameters of the inverter 205, the operating voltage and current of the inverter 205, and the like. It should be noted that the inverter control terminal 204 may be an upper computer connected to the inverter 205, or may be an internet of things module loaded on the inverter 205.
Referring to fig. 2, fig. 2 is a schematic flowchart of an inverter overheating warning method according to an embodiment of the present invention. As shown in FIG. 2, the method includes the following steps S1-S8.
And S1, receiving the user request.
In specific implementation, a user request is received, wherein the request is used for subscribing the overheating early warning function of the inverter, and when the user clicks the overheating early warning function of the inverter on a user side interface, the request for subscribing the overheating early warning function of the inverter is sent out.
And S2, obtaining historical data of the inverter from the database.
In specific implementation, historical data of the inverter is obtained from a database, and the historical data of the inverter working in the Internet of things platform is stored in the database. Specifically, an inverter control terminal in the platform of the internet of things accesses the database, inverter data stored in the database are used as historical data of the inverter, the historical data of the inverter comprises data such as the working temperature of the inverter, overload running time, parameters of the inverter, the working voltage and current of the inverter and the like, and data are provided for building an inverter overheating fault rate model and calculating model parameters.
And S3, preprocessing the historical data to obtain the working temperature and the overload running time of the inverter.
In specific implementation, the historical data is preprocessed to obtain the working temperature and overload running time of the inverter. According to the experience of engineers and the preliminary analysis of historical data of the inverter operation, two key factors which are used for promoting the inverter to generate overheating faults can be obtained as the operating temperature and the overload running time of the inverter. The operating temperature and overload operation time of the inverter need to be screened from historical operating data of the inverter before the inverter overheating fault rate model is established, so that the inverter can be used for later modeling.
In the real world, data is mostly incomplete, inconsistent dirty data and cannot be directly used. Preprocessing of the data is required in order to improve the quality of the data.
Referring to fig. 3, in an embodiment, the step S3 specifically includes: S31-S32.
And S31, screening the operating temperature and the overload running time of the inverter from the historical data.
In a specific implementation, the operating temperature and the overload operation time of the inverter are screened from the historical data. The screening of the data plays an important role in mathematical modeling, is the first step of the mathematical modeling, and can ensure the authenticity and the accuracy of the obtained result only if good data are obtained. The amount of data encountered in practical problems is often enormous. In order to ensure that the method can be realized under the support of the original data, the data must be screened, so that the solution is simplified. Meanwhile, the screened data are representative, so that the obtained result is more accurate and real.
And S32, performing data cleaning processing on the working temperature and the overload running time of the inverter.
In specific implementation, data cleaning processing is carried out on the working temperature and overload running time of the inverter. Some incomplete and wrong data in the screened data of the working temperature and the overload running time of the inverter need to be subjected to data cleaning processing to obtain data suitable for modeling.
Data cleansing is the process of re-examining and verifying data with the aim of deleting duplicate information, correcting existing errors, and providing data consistency. Data cleansing refers to the "washing out" of "dirty" by name, which refers to the last procedure to find and correct recognizable errors in a data file, including checking data consistency, dealing with invalid and missing values, etc. Because the data in the database is a collection of data oriented to a certain subject, the data are extracted from historical data, and therefore, the condition that some data are wrong data and some data conflict with each other is avoided, and the wrong or conflicting data obviously cannot be used for establishing an inverter overheating fault rate model and are called as 'dirty data'. We need to "wash" dirty data according to certain rules, which is data washing. The task of data cleansing is to filter out those data that are not satisfactory. Specifically, the working temperature and the overload running time of the inverter subjected to the data cleaning processing are used for calculating parameters of an inverter overheating fault rate model.
And S4, determining the parameters of a preset binary regression prediction model according to the working temperature and the overload running time of the inverter to obtain an overheating fault rate model.
In specific implementation, parameters of a preset binary regression prediction model are determined according to the working temperature and the overload running time of the inverter so as to obtain an overheating fault rate model. The binary regression prediction method is a prediction method for performing regression analysis by establishing a binary regression prediction model by using two independent variables influencing one dependent variable. In the embodiment, the dependent variable of the binary regression prediction model is the overheating fault rate of the inverter, and the two independent variables of the binary regression prediction model are two key factors for promoting the overheating fault rate of the inverter, namely the working temperature and the overload running time of the inverter. Establishing a binary regression prediction model as Y ═ beta + beta according to a binary regression prediction method1X1+β2X2Y is the inverter over-temperature failure rate, X1Is the operating temperature of the inverter, X2For the overload operation time of the inverter, beta1，β2Are parameters of a binary regression prediction model.
Referring to fig. 4, in an embodiment, the step S4 specifically includes: S41-S43.
And S41, establishing an estimation model of the inverter overheating fault rate according to the preset binary regression prediction model.
In specific implementation, a pre-estimation model of the inverter overheating fault rate is established according to a preset binary regression prediction model, and an estimation value of a parameter of the binary regression prediction model is used as a parameter of the pre-estimation model of the inverter overheating fault rate to obtain the pre-estimation model as
Wherein Y is the inverter overheating fault rate, X1Is the operating temperature of the inverter, X2The overload operation time of the inverter is,
for the predicted values of the model parameters, e is the residual.
And S42, calculating the estimated value of the model parameter according to a formula so as to obtain an estimated model of the overheating fault rate.
In specific implementation, according to the formula
Calculating the pre-estimated value of the model parameters of the pre-estimated model of the inverter overheating fault rate to obtain the pre-estimated model of the overheating fault rate, and obtaining the pre-estimated value of the model parameters by the least square method
The sum of the squares of the residuals e should be minimized, and the estimated values of the model parameters can be obtained according to the extreme value principle of the multivariate function. Wherein Y is the inverter overheating fault rate, X1Is the operating temperature of the inverter, X2The overload operation time of the inverter is,
for the predicted values of the model parameters, e is the residual.
And S43, checking the prediction model of the overheating fault rate to obtain the overheating fault rate model.
In specific implementation, the prediction model of the overheating fault rate is checked to obtain the overheating fault rate model. The model obtained in step S42 is an estimated model of the inverter overheating fault rate, and therefore needs to be checked to obtain an overheating fault rate model. If the predictive model of the overheating fault rate passes the inspection, the predictive value of the model parameter
As a parameter of the thermal failure rate model1，β2Thereby obtaining an overheating fault rate model; if the check is not passed, the process returns to step S2 until the check is passed. In the embodiment of the invention, the binary regression prediction model is tested to obtain a tested model as an overheating fault rate model. The common test methods include regression standard deviation test, correlation coefficient test, F test, t test, etc., and the user may select the test method according to the actual situation, which is not specifically limited in the present invention.
And S5, acquiring the real-time working temperature and the overload running time of the inverter.
In the specific implementation, the real-time working temperature and the overload running time of the inverter are obtained, and the real-time working temperature and the overload running time of the inverter are obtained by accessing a database for storing inverter working data.
And S6, preprocessing the real-time working temperature and the overload running time of the inverter.
In a specific implementation, the real-time operating temperature and the overload operation time of the inverter are preprocessed, and the processing manner of this step is the same as that of step S32, and will not be described again here.
And S7, inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model to calculate the overheating fault rate of the inverter.
In specific implementation, the preprocessed real-time working temperature and overload running time of the inverter are input into the overheating fault rate model to calculate the overheating fault rate of the inverter. And substituting the real-time working temperature and the overload running time of the preprocessed inverter into an inverter overheating fault rate model to calculate the overheating fault rate of the inverter, wherein the overheating fault rate of the inverter is a numerical value of 0-1.
And S8, judging whether to send out overheating fault early warning according to the overheating fault rate.
In specific implementation, judging whether the overheating fault rate is smaller than a preset threshold value; the preset threshold is a probability value of the inverter approaching the overheating fault rate, and a user can set the preset threshold according to the actual situation, which is not specifically limited by the invention.
Referring to fig. 5, in an embodiment, the step S8 specifically includes: S81-S82.
And S81, judging whether the overheating fault rate is smaller than a preset threshold value.
In a specific implementation, it is determined whether the overheating fault rate is smaller than a preset threshold, and if the overheating fault rate is smaller than the preset threshold, the step S81 of determining whether the overheating fault rate is equal to the preset threshold is returned.
And S82, sending an overheating fault early warning to a user.
In specific implementation, if the overheating fault rate is judged to be not less than the preset threshold, an overheating fault early warning is sent to a user to remind the user to process the inverter which is likely to have the overheating fault, so that the fault rate of the inverter is reduced, and good experience is provided for the user.
The embodiment of the invention provides an inverter overheating early warning method, an inverter overheating early warning device, computer equipment and a storage medium, wherein the inverter overheating early warning method comprises the following steps: receiving a user request, wherein the request is used for subscribing the overheating early warning function of the inverter; obtaining historical data of the inverter from a database; preprocessing the historical data to obtain the working temperature and overload running time of the inverter; determining parameters of a preset binary regression prediction model according to the working temperature and the overload running time of the inverter to obtain an overheating fault rate model, and acquiring the real-time working temperature and the overload running time of the inverter; preprocessing the real-time working temperature and overload running time of the inverter; inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model to calculate the overheating fault rate of the inverter; and judging whether to send out overheating fault early warning according to the overheating fault rate. The embodiment of the invention realizes the function of early warning of the overheating fault of the inverter, improves the safety of the inverter in the using process, reduces the fault occurrence rate of the inverter and provides good experience for users.
Fig. 6 is a schematic block diagram of an inverter overheating warning device according to an embodiment of the present invention. As shown in fig. 6, the present invention also provides an inverter overheating warning device 100 corresponding to the above inverter overheating warning method. The inverter overheating warning device 100 includes a unit for performing the inverter overheating warning method, and may be configured in a desktop computer, a tablet computer, a laptop computer, or the like. Specifically, referring to fig. 6, the inverter overheating warning device 100 includes a receiving unit 101, a first obtaining unit 102, a first preprocessing unit 103, a first calculating unit 104, a second obtaining unit 105, a second preprocessing unit 106, a second calculating unit 107, and a determining unit 108.
A receiving unit 101, configured to receive a user request, where the request is used to subscribe to an overheat early warning function of an inverter;
a first obtaining unit 102, configured to obtain historical data of the inverter from a database;
the first preprocessing unit 103 is configured to preprocess the historical data to obtain a working temperature and an overload operation time of the inverter;
a first calculating unit 104, configured to determine parameters of a preset binary regression prediction model according to the operating temperature and the overload operation time of the inverter to calculate an overheating fault rate model, where the binary regression prediction model is Y ═ β + β -1X1+β2X2Where Y is the inverter over-temperature failure rate, X1Is the operating temperature of the inverter, X2For the overload operation time of the inverter, beta1，β2Is twoParameters of a meta-regression prediction model;
a second obtaining unit 105 for obtaining the real-time operating temperature and the overload operation time of the inverter
A second preprocessing unit 106, configured to preprocess a real-time operating temperature and an overload operation time of the inverter;
a second calculating unit 107, configured to input the preprocessed real-time operating temperature and overload running time of the inverter into the overheating fault rate model to calculate an overheating fault rate of the inverter;
and the judging unit 108 is used for judging whether to send out an overheating fault early warning according to the overheating fault rate.
In an embodiment, the preprocessing the historical data to obtain the operating temperature and the overload operation time of the inverter includes:
screening out the operating temperature and overload running time of the inverter from the historical data;
and carrying out data cleaning processing on the working temperature and the overload running time of the inverter.
In an embodiment, the determining parameters of a preset binary regression prediction model according to the operating temperature and the overload operation time of the inverter to obtain an overheating fault rate model includes:
establishing a pre-estimation model of the overheating fault rate of the inverter according to the preset binary regression prediction model, wherein the pre-estimation model is
According to the formula
Calculating the estimated value of the model parameter of the estimation model of the inverter overheating fault rate, wherein Y is the inverter overheating fault rate, and X is the inverter overheating fault rate1Is the operating temperature of the inverter, X2The overload operation time of the inverter is,
the estimated value of the model parameter is obtained, and e is a residual error;
and checking the prediction model of the overheating fault rate to obtain the overheating fault rate model.
In one embodiment, the preprocessing the real-time operating temperature and the overload operation time of the inverter includes:
and carrying out data cleaning processing on the real-time working temperature and the overload running time of the inverter.
In one embodiment, whether the overheating fault rate is smaller than a preset threshold value is judged;
if the overheating fault rate is not smaller than the preset threshold value, an overheating fault early warning is sent to a user;
and if the overheating fault rate is smaller than the preset threshold, returning to the step of judging whether the overheating fault rate is equal to the preset threshold.
In an embodiment, the method is applied to an inverter control terminal in an internet of things platform, where the internet of things platform includes a database, a second cloud platform, a plurality of first cloud platforms, and a plurality of inverter control terminals, each inverter control terminal is connected to an inverter, each first cloud platform is connected to a plurality of inverter control terminals, the plurality of first cloud platforms are connected to the second cloud platform, the second cloud platform is connected to the database, and before receiving a user request, the inverter overheating early warning method further includes:
instructing the plurality of first cloud platforms to send the collected data of the plurality of inverters to the second cloud platform;
instruct the second cloud platform to store the received data for the plurality of inverters in the database.
In one embodiment, the obtaining historical data of the inverter includes:
and accessing the database, and taking the inverter data stored in the database as historical data of the inverter.
It should be noted that, as can be clearly understood by those skilled in the art, the specific implementation processes of the inverter overheating early warning device and each unit may refer to the corresponding descriptions in the foregoing method embodiments, and for convenience and brevity of description, no further description is provided herein.
The inverter overheating warning device may be implemented in the form of a computer program that can be run on a computer device as shown in fig. 7.
Referring to fig. 7, fig. 7 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device 300 is an upper computer. The upper computer can be a tablet computer, a notebook computer, a desktop computer and other electronic equipment.
Referring to fig. 7, the computer device 300 includes a processor 302, memory, and a network interface 305 connected by a system bus 301, where the memory may include a non-volatile storage medium 303 and an internal memory 304.
The nonvolatile storage medium 303 may store an operating system 3031 and a computer program 3032. The computer program 3032, when executed, may cause the processor 302 to perform a method of inverter overheating warning.
The processor 302 is used to provide computing and control capabilities to support the operation of the overall computer device 300.
The internal memory 304 provides an environment for the operation of the computer program 3032 in the non-volatile storage medium 303, and the computer program 3032, when executed by the processor 302, causes the processor 302 to perform an inverter overheating warning method.
The network interface 305 is used for network communication with other devices. Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing device 300 to which the disclosed aspects apply, as a particular computing device 300 may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
Wherein the processor 302 is configured to run a computer program 3032 stored in the memory to implement the following steps:
receiving a user request, wherein the request is used for subscribing the overheating early warning function of the inverter;
obtaining historical data of the inverter from a database;
preprocessing the historical data to obtain the working temperature and overload running time of the inverter;
determining parameters of a preset binary regression prediction model according to the working temperature and the overload running time of the inverter to obtain an overheating fault rate model, wherein the binary regression prediction model is Y ═ beta + beta1X1+β2X2Where Y is the inverter over-temperature failure rate, X1Is the operating temperature of the inverter, X2For the overload operation time of the inverter, beta1，β2Parameters of a binary regression prediction model;
acquiring the real-time working temperature and overload operation time of the inverter;
preprocessing the real-time working temperature and overload running time of the inverter;
inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model to calculate the overheating fault rate of the inverter;
and judging whether to send out overheating fault early warning according to the overheating fault rate.
In an embodiment, the preprocessing the historical data to obtain the operating temperature and the overload operation time of the inverter includes:
screening out the operating temperature and overload running time of the inverter from the historical data;
and carrying out data cleaning processing on the working temperature and the overload running time of the inverter.
In an embodiment, the determining parameters of a preset binary regression prediction model according to the operating temperature and the overload operation time of the inverter to obtain an overheating fault rate model includes:
establishing an inverter overheating event according to the preset binary regression prediction modelThe pre-estimation model of the barrier rate is
According to the formula
Calculating the estimated value of the model parameter of the estimation model of the inverter overheating fault rate, wherein Y is the inverter overheating fault rate, and X is the inverter overheating fault rate1Is the operating temperature of the inverter, X2The overload operation time of the inverter is,
the estimated value of the model parameter is obtained, and e is a residual error;
and checking the prediction model of the overheating fault rate to obtain the overheating fault rate model.
In one embodiment, the preprocessing the real-time operating temperature and the overload operation time of the inverter includes:
and carrying out data cleaning processing on the real-time working temperature and the overload running time of the inverter.
In one embodiment, whether the overheating fault rate is smaller than a preset threshold value is judged;
if the overheating fault rate is not smaller than the preset threshold value, an overheating fault early warning is sent to a user;
and if the overheating fault rate is smaller than the preset threshold, returning to the step of judging whether the overheating fault rate is equal to the preset threshold.
In an embodiment, the method is applied to an inverter control terminal in an internet of things platform, where the internet of things platform includes a database, a second cloud platform, a plurality of first cloud platforms, and a plurality of inverter control terminals, each inverter control terminal is connected to an inverter, each first cloud platform is connected to a plurality of inverter control terminals, the plurality of first cloud platforms are connected to the second cloud platform, the second cloud platform is connected to the database, and before receiving a user request, the inverter overheating early warning method further includes:
instructing the plurality of first cloud platforms to send the collected data of the plurality of inverters to the second cloud platform;
instruct the second cloud platform to store the received data for the plurality of inverters in the database.
In one embodiment, the obtaining historical data of the inverter includes:
and accessing the database, and taking the inverter data stored in the database as historical data of the inverter.
It should be understood that, in the embodiment of the present Application, the Processor 302 may be a Central Processing Unit (CPU), and the Processor 302 may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It will be understood by those skilled in the art that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program instructing associated hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program. The computer program, when executed by a processor, causes the processor to perform the steps of:
receiving a user request, wherein the request is used for subscribing the overheating early warning function of the inverter;
obtaining historical data of the inverter from a database;
preprocessing the historical data to obtain the working temperature and overload running time of the inverter;
determining parameters of a preset binary regression prediction model according to the working temperature and the overload running time of the inverter to obtain an overheating fault rate model, wherein the binary regression prediction model is Y ═ beta + beta1X1+β2X2Where Y is the inverter over-temperature failure rate, X1Is the operating temperature of the inverter, X2For the overload operation time of the inverter, beta1，β2Parameters of a binary regression prediction model;
acquiring the real-time working temperature and overload operation time of the inverter;
preprocessing the real-time working temperature and overload running time of the inverter;
inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model to calculate the overheating fault rate of the inverter;
and judging whether to send out overheating fault early warning according to the overheating fault rate.
In an embodiment, the preprocessing the historical data to obtain the operating temperature and the overload operation time of the inverter includes:
screening out the operating temperature and overload running time of the inverter from the historical data;
and carrying out data cleaning processing on the working temperature and the overload running time of the inverter.
In an embodiment, the determining parameters of a preset binary regression prediction model according to the operating temperature and the overload operation time of the inverter to obtain an overheating fault rate model includes:
establishing a pre-estimation model of the overheating fault rate of the inverter according to the preset binary regression prediction model, wherein the pre-estimation model is
According to the formula
Calculating the estimated value of the model parameter of the estimation model of the inverter overheating fault rate, wherein Y is the inverter overheating fault rate, and X is the inverter overheating fault rate1Is the operating temperature of the inverter, X2The overload operation time of the inverter is,
the estimated value of the model parameter is obtained, and e is a residual error;
and checking the prediction model of the overheating fault rate to obtain the overheating fault rate model.
In one embodiment, the preprocessing the real-time operating temperature and the overload operation time of the inverter includes:
and carrying out data cleaning processing on the real-time working temperature and the overload running time of the inverter.
In one embodiment, whether the overheating fault rate is smaller than a preset threshold value is judged;
if the overheating fault rate is not smaller than the preset threshold value, an overheating fault early warning is sent to a user;
and if the overheating fault rate is smaller than the preset threshold, returning to the step of judging whether the overheating fault rate is equal to the preset threshold.
In an embodiment, the method is applied to an inverter control terminal in an internet of things platform, where the internet of things platform includes a database, a second cloud platform, a plurality of first cloud platforms, and a plurality of inverter control terminals, each inverter control terminal is connected to an inverter, each first cloud platform is connected to a plurality of inverter control terminals, the plurality of first cloud platforms are connected to the second cloud platform, the second cloud platform is connected to the database, and before receiving a user request, the inverter overheating early warning method further includes:
instructing the plurality of first cloud platforms to send the collected data of the plurality of inverters to the second cloud platform;
instruct the second cloud platform to store the received data for the plurality of inverters in the database.
In one embodiment, the obtaining historical data of the inverter includes:
and accessing the database, and taking the inverter data stored in the database as historical data of the inverter.
The storage medium is an entity and non-transitory storage medium, and may be various entity storage media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, various elements or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented.
The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be merged, divided and deleted according to actual needs. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, while the invention has been described with respect to the above-described embodiments, it will be understood that the invention is not limited thereto but may be embodied with various modifications and changes.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An inverter overheating early warning method is characterized by comprising the following steps:
receiving a user request, wherein the request is used for subscribing the overheating early warning function of the inverter;
acquiring historical data of the inverter;
preprocessing the historical data to obtain the working temperature and overload running time of the inverter;
determining parameters of a preset binary regression prediction model according to the working temperature and the overload running time of the inverter to obtain an overheating fault rate model, wherein the binary regression prediction model is Y ═ beta + beta1X1+β2X2Where Y is the inverter over-temperature failure rate, X1Is the operating temperature of the inverter, X2For the overload operation time of the inverter, beta1，β2Parameters of a binary regression prediction model;
acquiring the real-time working temperature and overload operation time of the inverter;
preprocessing the real-time working temperature and overload running time of the inverter;
inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model to calculate the overheating fault rate of the inverter;
and judging whether to send out overheating fault early warning according to the overheating fault rate.
2. The inverter overheating pre-warning method according to claim 1, wherein the preprocessing the historical data to obtain the operating temperature and the overload operation time of the inverter comprises:
screening out the operating temperature and overload running time of the inverter from the historical data;
and carrying out data cleaning processing on the working temperature and the overload running time of the inverter.
3. The inverter overheating early warning method according to claim 1, wherein the determining parameters of the preset binary regression prediction model according to the operating temperature and the overload operation time of the inverter to obtain the overheating fault rate model comprises:
establishing a pre-estimation model of the overheating fault rate of the inverter according to the preset binary regression prediction model, wherein the pre-estimation is carried outThe model is
According to the formula
Calculating the estimated value of the model parameter of the estimation model of the inverter overheating fault rate, wherein Y is the inverter overheating fault rate, and X is the inverter overheating fault rate1Is the operating temperature of the inverter, X2The overload operation time of the inverter is,
the estimated value of the model parameter is obtained, and e is a residual error;
and checking the prediction model of the overheating fault rate to obtain the overheating fault rate model.
4. The inverter overheating warning method according to claim 1, wherein the preprocessing of the real-time operating temperature and the overload running time of the inverter comprises:
and carrying out data cleaning processing on the real-time working temperature and the overload running time of the inverter.
5. The inverter overheating warning method according to claim 1, wherein the determining whether to issue an overheating warning according to the overheating fault rate includes:
judging whether the overheating fault rate is smaller than a preset threshold value or not;
if the overheating fault rate is not smaller than the preset threshold value, an overheating fault early warning is sent to a user;
and if the overheating fault rate is smaller than the preset threshold, returning to the step of judging whether the overheating fault rate is equal to the preset threshold.
6. The inverter overheating early warning method according to claim 1, wherein the inverter control terminal is applied to an internet of things platform, the internet of things platform comprises a database, a second cloud platform, a plurality of first cloud platforms and a plurality of inverter control terminals, each inverter control terminal is connected with one inverter, each first cloud platform is connected with the plurality of inverter control terminals, the plurality of first cloud platforms are connected with the second cloud platform, the second cloud platform is connected with the database, and before the receiving of the user request, the inverter overheating early warning method further comprises:
instructing the plurality of first cloud platforms to send the collected data of the plurality of inverters to the second cloud platform;
instruct the second cloud platform to store the received data for the plurality of inverters in the database.
7. The inverter overheating warning method according to claim 6, wherein the obtaining of the historical data of the inverter includes:
and accessing the database, and taking the inverter data stored in the database as historical data of the inverter.
8. An inverter overheat warning device, comprising:
the system comprises a receiving unit, a processing unit and a processing unit, wherein the receiving unit is used for receiving a user request which is used for subscribing the overheating early warning function of an inverter;
a first acquisition unit configured to acquire history data of the inverter;
the first preprocessing unit is used for preprocessing the historical data to obtain the working temperature and overload running time of the inverter;
a first calculating unit, configured to determine parameters of a preset binary regression prediction model according to the operating temperature and the overload operation time of the inverter to calculate an overheating fault rate model, where the binary regression prediction model is Y ═ β + β -1X1+β2X2Where Y is the inverter over-temperature failure rate, X1Is the operating temperature of the inverter, X2For overloading of invertersRun time, beta1，β2Parameters of a binary regression prediction model;
a second acquisition unit for acquiring real-time operating temperature and overload operation time of the inverter
The second preprocessing unit is used for preprocessing the real-time working temperature and the overload running time of the inverter;
the second calculation unit is used for inputting the preprocessed real-time working temperature and overload running time of the inverter into the overheating fault rate model so as to calculate the overheating fault rate of the inverter;
and the judging unit is used for judging whether to send out overheating fault early warning according to the overheating fault rate.
9. A computer arrangement, characterized in that the computer arrangement comprises a memory having stored thereon a computer program and a processor implementing the method according to any of claims 1-7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method according to any one of claims 1-7.
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