CN112489402A - Early warning method, device and system for pipe gallery and storage medium - Google Patents
Early warning method, device and system for pipe gallery and storage medium Download PDFInfo
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Abstract
The invention provides an early warning method, an early warning device, an early warning system and a storage medium for a pipe gallery, wherein the pipe gallery comprises monitoring equipment and associated equipment, the associated equipment is associated with the monitoring equipment, and the method comprises the following steps: acquiring historical monitoring data of monitoring equipment; calculating the prediction data of the monitoring equipment at a preset time in the future based on the historical monitoring data and the time series model; comparing the predicted data with a corresponding data threshold value, and sending out an early warning signal when the predicted data is greater than or equal to the data threshold value; and controlling the action of the associated equipment according to the early warning signal so as to enable the actual data of the monitoring equipment at the preset time to be smaller than the corresponding data threshold. According to the early warning method, the early warning device, the early warning system and the storage medium for the pipe rack of the vehicle, the pipe rack environment is predicted in real time based on the historical monitoring data and the time sequence algorithm of the pipe rack, early warning is carried out in advance to reduce or avoid accidents, the labor cost and the safety threat of personnel are reduced, and the efficiency and the safety of monitoring the pipe rack are improved.
Description
Technical Field
The invention relates to the technical field of monitoring, in particular to an early warning technology of a pipe gallery.
Background
The pipe gallery is a place for intensively laying various pipelines, and generally comprises columns, beams and trusses of steel structures or reinforced concrete structures, which can be divided into single-layer or multi-layer structures according to types, accessible or inaccessible and the like. For example, an urban pipe gallery refers to a place where municipal utility pipelines such as electric power, communication, gas, water supply and drainage, heat and the like are intensively laid in the same underground tunnel space, and are comprehensively developed and utilized to save urban construction land and facilitate unified management and planning. The functions of the pipe gallery such as power, illumination, drainage and the like are various, and no matter the pipeline fails or auxiliary equipment related to the pipeline fails, the breakdown of the functions of the city along the line and even disastrous accidents can be caused.
At present, most of city pipe galleries are basically connected with various monitoring devices, when monitoring data of the devices are abnormal and reach a certain threshold value, an alarm is triggered, and then the monitoring devices are manually processed. The traditional alarm mode can only alarm by real-time monitoring numerical values, belongs to post remedy, and cannot avoid the occurrence of abnormal conditions.
Therefore, the problem that only after-the-fact alarm can be given out and the data of the equipment in the pipe gallery can not be predicted timely, effectively and accurately exists in the pipe gallery monitoring in the prior art.
Disclosure of Invention
The present invention has been made in view of the above problems. The invention provides a monitoring method, a device and a system for a pipe gallery and a computer storage medium, which aim to solve the problem that the data of equipment in the pipe gallery can not be predicted timely, effectively and accurately because only a later alarm is given in the monitoring of the pipe gallery.
According to a first aspect of the present invention, there is provided a method of pre-warning a pipe gallery, the pipe gallery including a monitoring device and an association device associated with the monitoring device, the method comprising:
acquiring historical monitoring data of the monitoring equipment;
calculating the prediction data of the monitoring equipment at a preset time in the future based on the historical monitoring data and the time series model;
comparing the predicted data with a corresponding data threshold, and sending out an early warning signal when the predicted data is greater than or equal to the data threshold;
and controlling the associated equipment to act according to the early warning signal so as to enable the actual data of the monitoring equipment at the preset time to be smaller than the corresponding data threshold value.
According to a second aspect of the present invention there is provided an early warning apparatus for a pipe gallery, the pipe gallery including monitoring equipment and associated equipment associated with the monitoring equipment, the apparatus comprising:
the acquisition module is used for acquiring historical monitoring data of the monitoring equipment;
the prediction module is used for calculating prediction data of the monitoring equipment at a preset time in the future based on the historical monitoring data and the time series model;
the judging module is used for comparing the predicted data with a corresponding data threshold value and sending out an early warning signal when the predicted data is greater than or equal to the data threshold value;
and the execution module is used for controlling the associated equipment to act according to the early warning signal so as to enable the actual data of the monitoring equipment at the preset time to be smaller than the corresponding data threshold value.
According to a third aspect of the present invention, there is provided a pre-warning system for a pipe rack, comprising a memory, a processor and a computer program stored on the memory and running on the processor, wherein the processor implements the steps of the method according to the first aspect when executing the computer program.
According to a fourth aspect of the present invention, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a computer, carries out the steps of the method according to the first aspect.
According to the early warning method, the early warning device, the early warning system and the computer storage medium for the pipe gallery, the pipe gallery environment is predicted in real time based on the historical monitoring data and the time sequence algorithm of the pipe gallery, potential safety hazards which possibly exist in the pipe gallery are early warned in advance, accidents are reduced or avoided, the labor cost and the safety threat of personnel are reduced, the time is saved, and the efficiency and the safety of monitoring the pipe gallery are improved.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail embodiments of the present invention with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings, like reference numbers generally represent like parts or steps.
Fig. 1 is a schematic flow diagram of a method of monitoring a pipe lane according to an embodiment of the invention;
FIG. 2 is an example of a monitoring system for a pipe lane according to an embodiment of the present invention;
fig. 3 is a schematic block diagram of a monitoring device of a pipe lane according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely a subset of embodiments of the invention and not all embodiments of the invention, with the understanding that the invention is not limited to the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the invention described herein without inventive step, shall fall within the scope of protection of the invention.
Most city piping lane has accessed into various monitoring and monitoring equipment basically at present, and wherein environmental monitoring mainly has gas sensor and temperature and humidity sensor etc.. The gas sensor mainly comprises oxygen, methane and hydrogen sulfide, and the temperature and humidity sensor comprises a temperature sensor and a humidity sensor. At present, aiming at the better early warning system for the data lack of the sensors, the alarm is triggered basically when the sensors reach a certain threshold value, then other equipment is controlled manually to process, for example, when the methane concentration exceeds the alarm threshold value, the alarm information is transmitted to upper platform software, and operation and maintenance personnel manually start a fan to ventilate according to the alarm information so as to reduce the methane concentration value. There are two disadvantages to environmental monitoring in this way: firstly, alarming is basically carried out by means of real-time numerical values of the sensors, historical numerical values of the sensors cannot be known, prediction cannot be carried out, and therefore early warning is achieved; secondly, when alarming, people are needed to cooperate with a starting control system, automatic linkage control cannot be realized, and various disaster results can be caused in case that operation and maintenance personnel are out of site.
Based on the consideration, the early warning method for the pipe gallery is provided. Next, an early warning method 1 of a pipe lane according to an embodiment of the present invention will be described with reference to fig. 1. As shown in fig. 1, a method 1 for early warning of a pipe gallery includes:
step S1-1, acquiring historical monitoring data of the monitoring equipment;
step S1-2, calculating the prediction data of the monitoring equipment at a preset time in the future based on the historical monitoring data and the time series model;
step S1-3, comparing the prediction data with a corresponding data threshold value, and sending out an early warning signal when the prediction data is greater than or equal to the data threshold value;
and step S1-4, controlling the associated equipment to act according to the early warning signal, so that the actual data of the monitoring equipment in the preset time is smaller than the corresponding data threshold.
According to the embodiment of the invention, the data of the monitoring equipment in the pipe gallery is predicted by using the time sequence model through the historical monitoring data of at least one monitoring equipment, and because the monitoring equipment monitors the environment of the pipe gallery and the equipment, the prediction can carry out early warning on the interior of the pipe gallery, and an alarm is given out before an accident occurs, so that the accident is prevented in the bud, the occurrence of the accident in the pipe gallery is reduced, the frequency of manual handling of the accident is reduced, a large amount of manpower and material resources are saved, and the reliability of a pipe gallery monitoring system is improved. Meanwhile, when early warning occurs, other monitoring equipment associated with the equipment which generates early warning can be linked, so that the equipment which generates early warning is processed in time, abnormal conditions are avoided, the normal running state of the equipment is ensured, and the reliability of the monitoring equipment and the monitoring system is further improved. According to the early warning method of the pipe gallery, disclosed by the embodiment of the invention, the working condition of the pipe gallery can be predicted by working personnel, the potential safety hazard can be timely treated before the accident of the pipe gallery occurs, the maintenance greening and the resource utilization intensive management are realized, and the labor power, operation and maintenance cost is greatly saved. The method is suitable for being widely applied to the monitoring and early warning of closed scenes.
Optionally, the monitoring device in the pipe rack may be one or more. Further, when the pipe rack comprises a plurality of monitoring devices, it may comprise monitoring devices of the same type, or monitoring devices of different types. Specifically, the plurality of monitoring devices may be the same type of monitoring devices disposed at different locations, may be different types of monitoring devices disposed at the same location, or may be the same type of monitoring devices disposed at different locations.
Optionally, the associated equipment in the tube lane may also be one or more.
In some embodiments, historical monitoring data of one monitoring device in the pipe gallery can be obtained, prediction data of the one monitoring device in a future preset time is calculated, and when the prediction data is larger than or equal to a preset threshold value, an early warning signal is sent out; and meanwhile, controlling one or more associated devices associated with the monitoring device to perform corresponding actions so that the actual data of the monitoring device at the preset time is smaller than the corresponding data threshold.
In some embodiments, historical monitoring data of a plurality of monitoring devices in the pipe gallery can be obtained, prediction data of the monitoring device in a future preset time is calculated, and when the prediction data is larger than or equal to a preset threshold value, an early warning signal is sent out; and meanwhile, controlling one or more associated devices associated with the monitoring device to perform corresponding actions so that the actual data of the monitoring device at the preset time is smaller than the corresponding data threshold.
In some embodiments, historical monitoring data may be obtained for a plurality of different types of monitoring devices in a pipe rack, and environmental forecast data for the pipe rack may be calculated based at least in part on the historical monitoring data; when the environmental prediction data is greater than or equal to a preset threshold value, sending an early warning signal; and simultaneously, controlling one or more associated devices associated with a plurality of different types of monitoring devices to perform corresponding actions, so that the actual data of the environmental data of the pipe gallery at the preset time is smaller than the corresponding data threshold value, thereby ensuring that the pipe gallery is in a safe environment.
The monitoring equipment or the related equipment can comprise an exhaust fan, a drainage pump, a water pump, an infrared correlation alarm device, temperature and humidity inspection equipment, gas detection equipment, a power distribution cabinet and other equipment for detecting the working data of the pipeline. Other working equipment for use in a pipe gallery scene may also be included. For example. The monitoring device may also be: the system comprises a multi-parameter (O2, CH4, H2S, CO, temperature and humidity sensing elements which are freely combined as required), an intelligent combined detector, an equipment start and stop sensor, a water level sensor, an air speed sensor, a smoke sensor, an intrinsically safe integrated network substation (a built-in optical fiber network switch, a liquid crystal display screen and an acousto-optic alarm function are arranged in the integrated network substation, sixteen paths of analog quantity/switching quantity/digital type sensors can be accessed, sixteen paths of card readers can be connected, eight paths of control output are provided), an intrinsically safe controller, an explosion-proof and intrinsically safe uninterrupted power supply, a ground monitoring host, environment and equipment monitoring system software and the like.
According to the embodiment of the invention, in step S1-1, historical monitoring data of the monitoring device is acquired.
In some embodiments, in step S1-1, acquiring historical monitoring data of the monitoring device may further include:
collecting monitoring data of the monitoring equipment, and storing information of the monitoring equipment and the monitoring data corresponding to the monitoring equipment into a database in a correlation manner;
and acquiring monitoring data corresponding to the monitoring equipment from the database based on the information of the monitoring equipment as historical monitoring data of the monitoring equipment.
In some embodiments, the information of the monitoring device may include at least one of: a number (or ID number) of the monitoring device, a type of the monitoring device, and location information of the monitoring device.
In some embodiments, historical monitoring data for the monitoring device may be obtained from a database based on the number (or ID number) of the monitoring device. In some embodiments, historical monitoring data of all monitoring devices of the type may also be obtained from a database according to the type of the monitoring device. In some embodiments, historical monitoring data of all monitoring devices in a certain area may also be obtained according to the location information of the monitoring devices. It should be appreciated that the above-described embodiments of obtaining historical monitoring data based on information from a monitoring device may be performed individually or in any combination.
According to an embodiment of the present invention, in step S1-2, calculating the predicted data of the monitoring device at a preset time in the future based on the historical monitoring data and the time series model may include:
training the time sequence model according to the first part of the historical monitoring data to obtain a trained time sequence model;
and inputting a second part of the historical monitoring data into the trained time series model to obtain predicted data of the monitoring equipment at a preset time in the future, wherein the first part of the data is different from the second part of the data.
In some embodiments, the time series model may employ a moving average method or an exponential smoothing method. The time series model decomposes the time series with linear trend, seasonal variation and random variation, combines with an exponential smoothing method, respectively estimates the long-term trend, the trend increment and the seasonal variation, and establishes a prediction model, namely a time series model, so as to predict future data. For example, the environment inside a pipe gallery is periodically affected, and the temperature during the day is generally higher than the temperature at night, so the data can be predicted by a cubic exponential smoothing method.
Optionally, training the time series model according to the first part of the historical monitoring data to obtain a trained time series model, including:
respectively inputting at least one part of the first part of data serving as training data into initial time series models with different hyper-parameters for fitting to obtain time series models with different hyper-parameters;
predicting the time corresponding to the rest part in the first part of data based on the time series models of different hyper-parameters to obtain training prediction data of the time series models of different hyper-parameters;
taking the rest of the first part of data as test data, and calculating the fitting degree between the test data and the corresponding training prediction data;
and taking the hyperparameter corresponding to the training prediction data with the highest fitting degree with the residual part as the hyperparameter of the trained time series model.
In some embodiments, the different hyper-parameters comprise: and the adjacent hyper-parameters have the same preset difference value.
In some embodiments, calculating a fitness between the test data and the corresponding training prediction data comprises:
and calculating the variance between the test data and the corresponding training prediction data as the fitting degree.
Optionally, the time series model comprises:
wherein alpha, beta and gamma are respectively a horizontal smoothing coefficient, a trend smoothing coefficient and a seasonal smoothing coefficient, alpha is more than or equal to 0 and less than or equal to 1, beta is more than or equal to 0 and less than or equal to 1, and gamma is more than or equal to 0 and less than or equal to 1; k is the preset time; p is the period length.
In some embodiments, taking a gas sensor as an example of the monitoring device, the prediction data most suitable for the actual environment of the pipe rack can be fitted according to the indication part of the historical monitoring data by continuously collecting and storing the numerical value of the gas sensor inside the pipe rack as the historical monitoring data. For example, the current historical monitoring data includes data values of a cycles, the previous a1 cycle may be used as training data, the later a2 cycle may be used as test data, three parameters α, β, and γ are respectively incremented from 0 to 1, for example, each time b is increased, there are multiple combinations of the three parameters α, β, and γ, for each parameter combination, fitting is performed by using data of the previous a1 cycles, predicted data of the later a2 cycles are predicted, and then compared with actual data of the a2 cycles, the fitting degree of the variance determination algorithm may be used, and finally, the hyper-parameter with the highest fitting degree is selected as the hyper-parameter of the model. After the model is trained, the model can be deployed in an upper platform system. At this point, the possible data of the monitoring device for several cycles in the future can be predicted according to the latest historical data. Wherein a, a1, a2 and b are positive integers.
According to the embodiment of the present invention, in step S1-3, the data threshold may be set as needed, which is not limited herein.
According to the embodiment of the present invention, in step S1-4, controlling the associated device to act according to the early warning signal, so that the actual data of the monitoring device at the preset time is smaller than the corresponding data threshold, includes:
calculating a difference between the prediction data and the preset threshold;
calculating an output parameter of the associated equipment according to the difference value and the working parameter of the associated equipment;
controlling the associated device action based on the output parameter of the associated device.
Referring to fig. 2, fig. 2 shows an example of a pre-warning system for a pipe lane according to an embodiment of the invention. As shown in fig. 2, the early warning system of the illustrated pipe gallery includes:
a perception layer configured to include a monitoring device and an association device, the association device associated with the monitoring device;
a data collection layer in communication with the monitoring device in the awareness layer configured to store historical monitoring data for the monitoring device;
a business logic processing layer comprising a time series model configured to:
acquiring historical monitoring data of the monitoring equipment;
calculating the prediction data of the monitoring equipment at a preset time in the future based on the historical monitoring data and the time series model;
comparing the predicted data with a corresponding data threshold, and sending out an early warning signal when the predicted data is greater than or equal to the data threshold;
and controlling the action of the associated equipment so that the actual data of the monitoring equipment at the preset time is smaller than the corresponding data threshold.
In one embodiment, the system shown in fig. 2 is taken as an example to describe the method for warning a pipe rack according to an embodiment of the present invention. The early warning system of piping lane contains the three-layer: the system comprises a perception layer, a data acquisition layer and a service logic processing layer.
The perception layer includes the gas sensor and the moderate degree sensor of temperature inside the various piping lane, and these sensors insert various PLC equipment. The PLC performs data interaction with the upper platform through various industrial communication protocols, such as an OPC protocol and the like. For example, the gas sensor mainly comprises oxygen, methane and hydrogen sulfide, and the temperature and humidity sensor comprises a temperature sensor and a humidity sensor.
The data acquisition layer can store the real-time data of the gas sensor and the temperature and humidity sensor in the pipe gallery to the database for the upper platform to perform service logic processing.
The business logic processing layer can predict and give an early warning by using the historical values of the internal gas sensors through a time sequence algorithm, and when the predicted values exceed the warning threshold value, the equipment of the lower platform can be controlled by using an OPC (optical proximity correction) protocol, for example, a fan is started to ventilate, so that the concentration of harmful gases in the environment is reduced.
Fig. 3 shows a schematic block diagram of a pre-warning device 3 of a pipe rack according to an embodiment of the invention. As shown in fig. 3, the pipe gallery includes a monitoring device and an associated device, the associated device is associated with the monitoring device, and the early warning device 3 of the pipe gallery according to the embodiment of the present invention includes:
the acquisition module 3-1 is used for acquiring historical monitoring data of the monitoring equipment;
the prediction module 3-2 is used for calculating prediction data of the monitoring equipment at a preset time in the future based on the historical monitoring data and the time series model;
the judging module 3-3 is used for comparing the predicted data with a corresponding data threshold value and sending out an early warning signal when the predicted data is larger than or equal to the data threshold value;
and the execution module 3-4 is used for controlling the associated equipment to act according to the early warning signal so as to enable the actual data of the monitoring equipment at the preset time to be smaller than the corresponding data threshold value.
Only the main functional modules of the early warning device 3 are explained here, and the early warning device 3 of the pipe rack according to the embodiment of the present invention is used for implementing the above early warning method of the pipe rack according to the embodiment of the present invention, and repeated parts are not described herein again.
Those of ordinary skill in the art will appreciate that the various illustrative elements and model steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. 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.
According to the embodiment of the invention, the invention further provides a pipe gallery early warning system which comprises a storage device and a processor.
The storage means stores program code for implementing the respective steps in the method for pre-warning of a pipe rack according to an embodiment of the invention.
The processor is configured to run the program code stored in the storage device to perform the respective steps of the method for pre-warning of a pipe rack according to an embodiment of the present invention, and to implement the respective modules in the device for pre-warning of a pipe rack according to an embodiment of the present invention.
Furthermore, according to an embodiment of the present invention, there is also provided a storage medium having stored thereon program instructions for executing the respective steps of the pre-warning method of a pipe rack according to an embodiment of the present invention when the program instructions are executed by a computer or a processor, and for implementing the respective modules in the pre-warning device of a pipe rack according to an embodiment of the present invention. The storage medium may include, for example, a memory card of a smart phone, a storage component of a tablet computer, a hard disk of a personal computer, a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a portable compact disc read only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer readable storage medium can be any combination of one or more computer readable storage media, e.g., one containing computer readable program code for randomly generating sequences of action instructions and another containing computer readable program code for performing data processing.
In an embodiment, the computer program instructions may, when executed by a computer, implement the respective functional modules of the pre-warning device of the pipe rack according to an embodiment of the invention and/or may perform the pre-warning method of the pipe rack according to an embodiment of the invention.
The modules in the pre-warning system of a pipe rack according to an embodiment of the invention may be implemented by a processor of an electronic device for pipe rack pre-warning according to an embodiment of the invention running computer program instructions stored in a memory, or may be implemented when computer instructions stored in a computer readable storage medium of a computer program product according to an embodiment of the invention are run by a computer.
According to the early warning method, the early warning device, the early warning system and the computer storage medium for the pipe gallery, the pipe gallery environment is predicted in real time based on the historical monitoring data and the time sequence algorithm of the pipe gallery, potential safety hazards which possibly exist in the pipe gallery are early warned in advance, accidents are reduced or avoided, the labor cost and the safety threat of personnel are reduced, the time is saved, and the efficiency and the safety of monitoring the pipe gallery are improved.
Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the foregoing illustrative embodiments are merely exemplary and are not intended to limit the scope of the invention thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the scope or spirit of the present invention. All such changes and modifications are intended to be included within the scope of the present invention as set forth in the appended claims.
It will be understood by those skilled in the art that all of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where such features are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Various component embodiments of the invention may be implemented in hardware, or in data modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some of the modules in an item analysis apparatus according to embodiments of the present invention. The present invention may also be embodied as apparatus programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
The above description is only for the specific embodiment of the present invention or the description thereof, and the protection scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the protection scope of the present invention. The protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method of pre-warning a pipe rack, the pipe rack comprising a monitoring device and an associated device, the associated device being associated with the monitoring device, the method comprising:
acquiring historical monitoring data of the monitoring equipment;
calculating the prediction data of the monitoring equipment at a preset time in the future based on the historical monitoring data and the time series model;
comparing the predicted data with a corresponding data threshold, and sending out an early warning signal when the predicted data is greater than or equal to the data threshold;
and controlling the associated equipment to act according to the early warning signal so as to enable the actual data of the monitoring equipment at the preset time to be smaller than the corresponding data threshold value.
2. The method of claim 1, wherein calculating the predicted data of the monitoring device at a preset time in the future based on the historical monitoring data and a time series model comprises:
training the time sequence model according to the first part of the historical monitoring data to obtain a trained time sequence model;
and inputting a second part of the historical monitoring data into the trained time series model to obtain predicted data of the monitoring equipment at a preset time in the future, wherein the first part of the data is different from the second part of the data.
3. The method of claim 2, wherein training the time series model according to the first portion of the historical monitoring data to obtain a trained time series model comprises:
respectively inputting at least one part of the first part of data serving as training data into initial time series models with different hyper-parameters for fitting to obtain time series models with different hyper-parameters;
predicting the time corresponding to the rest part in the first part of data based on the time series models of different hyper-parameters to obtain training prediction data of the time series models of different hyper-parameters;
taking the rest of the first part of data as test data, and calculating the fitting degree between the test data and the corresponding training prediction data;
and taking the hyperparameter corresponding to the training prediction data with the highest fitting degree with the residual part as the hyperparameter of the trained time series model.
4. The method of claim 3, wherein the different hyper-parameters comprise: and the adjacent hyper-parameters have the same preset difference value.
5. The method of claim 4, wherein calculating a fitness between the test data and the corresponding training prediction data comprises:
and calculating the variance between the test data and the corresponding training prediction data as the fitting degree.
6. The method of claim 5, wherein the time series model comprises:
wherein alpha, beta and gamma are respectively a horizontal smoothing coefficient, a trend smoothing coefficient and a seasonal smoothing coefficient, alpha is more than or equal to 0 and less than or equal to 1, beta is more than or equal to 0 and less than or equal to 1, and gamma is more than or equal to 0 and less than or equal to 1; k is the preset time; p is the period length.
7. The method of claim 1, wherein controlling the associated device to act according to the warning signal so that the actual data of the monitoring device at the preset time is smaller than the corresponding data threshold comprises:
calculating a difference between the prediction data and the preset threshold;
calculating an output parameter of the associated equipment according to the difference value and the working parameter of the associated equipment;
controlling the associated device action based on the output parameter of the associated device.
8. An early warning device for a pipe rack, comprising a monitoring device and an associated device in the pipe rack, the associated device being associated with the monitoring device, the device comprising:
the acquisition module is used for acquiring historical monitoring data of the monitoring equipment;
the prediction module is used for calculating prediction data of the monitoring equipment at a preset time in the future based on the historical monitoring data and the time series model;
the judging module is used for comparing the predicted data with a corresponding data threshold value and sending out an early warning signal when the predicted data is greater than or equal to the data threshold value;
and the execution module is used for controlling the associated equipment to act according to the early warning signal so as to enable the actual data of the monitoring equipment at the preset time to be smaller than the corresponding data threshold value.
9. A pre-warning system for a pipe gallery, the system comprising a memory, a processor and a computer program stored on the memory and running on the processor, wherein the processor, when executing the computer program, implements the method of any one of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored which, when executed by a computer, implements the method of any one of claims 1-7.
Priority Applications (1)
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