CN116505630B - Method and system for prolonging service life of power supply battery of fire-fighting Internet of things equipment - Google Patents
Method and system for prolonging service life of power supply battery of fire-fighting Internet of things equipment Download PDFInfo
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- CN116505630B CN116505630B CN202310781429.8A CN202310781429A CN116505630B CN 116505630 B CN116505630 B CN 116505630B CN 202310781429 A CN202310781429 A CN 202310781429A CN 116505630 B CN116505630 B CN 116505630B
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- 238000000034 method Methods 0.000 title claims abstract description 23
- 230000007613 environmental effect Effects 0.000 claims abstract description 50
- 230000002159 abnormal effect Effects 0.000 claims description 52
- 238000007781 pre-processing Methods 0.000 claims description 14
- 230000005856 abnormality Effects 0.000 claims description 9
- 238000012544 monitoring process Methods 0.000 abstract description 3
- 230000002035 prolonged effect Effects 0.000 abstract description 3
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0029—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with safety or protection devices or circuits
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Abstract
According to the method and the system for prolonging the service life of the power supply battery of the fire-fighting Internet of things equipment, provided by the application, whether the environmental data of the power supply battery of the current equipment is normal or not is determined through comparing and analyzing the environmental data of the power supply battery of the current equipment with the preset standard environmental data, if so, the working environment of the power supply battery of the corresponding equipment is normal, and if not, the working environment of the power supply battery of the current equipment is correspondingly adjusted; meanwhile, the application monitors the output power of the equipment power supply battery and maintains the output power of the equipment power supply battery in a stable state. The service life of the power supply battery of the equipment is prolonged by monitoring the working environment and the output power of the power supply battery of the equipment and correspondingly adjusting the working environment and the output power.
Description
Technical Field
The application relates to the technical field of batteries, in particular to a method and a system for prolonging service life of a power supply battery of fire-fighting Internet of things equipment.
Background
The battery-powered type internet of things equipment is located in a network, and the control and management of the power consumption of the equipment are determined by the communication interaction frequency, the stability of the network, the state of a working environment and the like, and common network topologies comprise a star network, a tree network, a cluster tree network and a mesh network.
In the current internet of things system, battery-powered equipment performs information interaction in the whole network according to function requirements, and the power consumption is reduced by increasing the battery capacity or selecting a low power consumption period as far as possible in terms of hardware on the premise that the service life of a delay battery is preset through related indexes.
Accordingly, there is a need for improvement in the art.
Disclosure of Invention
In view of the above problems, the present application aims to provide a method and a system for improving the service life of a power supply battery of a fire-fighting internet of things device, which can more effectively improve the service life of the power supply battery of the device.
The first aspect of the application provides a method for prolonging the service life of a power supply battery of fire-fighting Internet of things equipment, which comprises the following steps:
acquiring environmental data of a power supply battery of the current equipment;
preprocessing the environmental data to obtain a first characteristic value;
performing difference calculation on the first characteristic value and a preset characteristic value to obtain a first data difference;
judging whether the absolute value of the first data difference is larger than a preset data difference threshold value, if so, extracting a corresponding duration value of the first data difference; if not, the current equipment power supply battery is normal;
judging whether the duration time value of the first data difference is larger than a preset first time threshold value, if so, triggering abnormal prompt information of the battery environment; if not, recording the first data difference for abnormal time;
extracting the abnormal times value of the first data difference;
judging whether the abnormal frequency value of the first data difference is larger than a preset first frequency threshold value, if so, triggering abnormal prompt information of the battery environment; if not, the current equipment power supply battery is normal;
and adjusting the current battery environment according to the battery environment abnormality prompt information.
In this scheme, the step of preprocessing the environmental data to obtain the first feature value specifically includes:
extracting a factor value in the current environment data;
normalizing the factor values in the current environment data to obtain first factor values;
inquiring in a preset characteristic weight coefficient table according to the first factor value to obtain a characteristic weight coefficient corresponding to the first factor value;
multiplying the first factor value by the corresponding characteristic weight coefficient to obtain a first factor characteristic value;
and accumulating the first factor characteristic values to obtain first characteristic values.
In this solution, the step of normalizing the factor value in the current environmental data to obtain a first factor value specifically includes:
acquiring a factor value in historical environment data;
arranging the factor values in the historical environment data in order from small to large to obtain a maximum historical factor value and a minimum historical factor value;
subtracting the minimum historical factor value from the factor value in the current environment data to obtain a first factor difference value, and subtracting the minimum historical factor value from the maximum historical factor value to obtain a second factor difference value;
the first factor value is the ratio of the first factor difference value to the second factor difference value.
In this scheme, still include:
acquiring historical environment data of a power supply battery of the equipment based on a preset first time period;
comparing and analyzing the historical environment data with preset ideal environment data to obtain similarity;
sequentially arranging the similarity according to the sequence from small to large, and extracting the maximum similarity;
and setting the historical environment data corresponding to the maximum similarity as standard environment data.
In this scheme, still include:
extracting a factor value in standard environment data;
normalizing the factor values in the standard environment data to obtain second factor values;
inquiring in a preset characteristic weight coefficient table according to the second factor value to obtain a second characteristic weight coefficient corresponding to the second factor value;
multiplying the second factor value by a corresponding second characteristic weight coefficient to obtain a second factor characteristic value;
and accumulating the second factor characteristic values to obtain preset characteristic values.
In this scheme, the step of adjusting the current battery environment according to the abnormal prompt information of the battery environment specifically includes:
performing difference calculation on the first factor characteristic value and the second factor characteristic value to obtain a factor characteristic difference value;
sequentially arranging different factor characteristic differences in sequence from large to small to obtain a maximum factor characteristic difference;
and setting the factor corresponding to the maximum factor characteristic difference as a first target of current battery environment adjustment.
In this scheme, still include:
acquiring a power supply battery output power data set based on a preset second time period;
extracting the maximum output power and the minimum output power in the power supply battery output power data set;
calculating the difference value between the maximum output power and the minimum output power to obtain an output power fluctuation value;
judging whether the fluctuation value of the output power is larger than a preset first power threshold value, if so, recording the fluctuation of the power output once; if not, the power supply battery works normally;
acquiring a power output fluctuation secondary value based on a preset third time period;
judging whether the power output fluctuation frequency value is larger than a preset second frequency threshold value or not, and if yes, triggering prompt information;
and sending the prompt information to a preset management terminal for display.
The application provides a system for prolonging the service life of a power supply battery of a fire-fighting Internet of things device, which comprises a memory and a processor, wherein a method program for prolonging the service life of the power supply battery of the fire-fighting Internet of things device is stored in the memory, and the method program for prolonging the service life of the power supply battery of the fire-fighting Internet of things device is executed by the processor to realize the following steps:
acquiring environmental data of a power supply battery of the current equipment;
preprocessing the environmental data to obtain a first characteristic value;
performing difference calculation on the first characteristic value and a preset characteristic value to obtain a first data difference;
judging whether the absolute value of the first data difference is larger than a preset data difference threshold value, if so, extracting a corresponding duration value of the first data difference; if not, the current equipment power supply battery is normal;
judging whether the duration time value of the first data difference is larger than a preset first time threshold value, if so, triggering abnormal prompt information of the battery environment; if not, recording the first data difference for abnormal time;
extracting the abnormal times value of the first data difference;
judging whether the abnormal frequency value of the first data difference is larger than a preset first frequency threshold value, if so, triggering abnormal prompt information of the battery environment; if not, the current equipment power supply battery is normal;
and adjusting the current battery environment according to the battery environment abnormality prompt information.
In this scheme, the step of preprocessing the environmental data to obtain the first feature value specifically includes:
extracting a factor value in the current environment data;
normalizing the factor values in the current environment data to obtain first factor values;
inquiring in a preset characteristic weight coefficient table according to the first factor value to obtain a characteristic weight coefficient corresponding to the first factor value;
multiplying the first factor value by the corresponding characteristic weight coefficient to obtain a first factor characteristic value;
and accumulating the first factor characteristic values to obtain first characteristic values.
In this solution, the step of normalizing the factor value in the current environmental data to obtain a first factor value specifically includes:
acquiring a factor value in historical environment data;
arranging the factor values in the historical environment data in order from small to large to obtain a maximum historical factor value and a minimum historical factor value;
subtracting the minimum historical factor value from the factor value in the current environment data to obtain a first factor difference value, and subtracting the minimum historical factor value from the maximum historical factor value to obtain a second factor difference value;
the first factor value is the ratio of the first factor difference value to the second factor difference value.
In this scheme, still include:
acquiring historical environment data of a power supply battery of the equipment based on a preset first time period;
comparing and analyzing the historical environment data with preset ideal environment data to obtain similarity;
sequentially arranging the similarity according to the sequence from small to large, and extracting the maximum similarity;
and setting the historical environment data corresponding to the maximum similarity as standard environment data.
In this scheme, still include:
extracting a factor value in standard environment data;
normalizing the factor values in the standard environment data to obtain second factor values;
inquiring in a preset characteristic weight coefficient table according to the second factor value to obtain a second characteristic weight coefficient corresponding to the second factor value;
multiplying the second factor value by a corresponding second characteristic weight coefficient to obtain a second factor characteristic value;
and accumulating the second factor characteristic values to obtain preset characteristic values.
In this scheme, the step of adjusting the current battery environment according to the abnormal prompt information of the battery environment specifically includes:
performing difference calculation on the first factor characteristic value and the second factor characteristic value to obtain a factor characteristic difference value;
sequentially arranging different factor characteristic differences in sequence from large to small to obtain a maximum factor characteristic difference;
and setting the factor corresponding to the maximum factor characteristic difference as a first target of current battery environment adjustment.
In this scheme, still include:
acquiring a power supply battery output power data set based on a preset second time period;
extracting the maximum output power and the minimum output power in the power supply battery output power data set;
calculating the difference value between the maximum output power and the minimum output power to obtain an output power fluctuation value;
judging whether the fluctuation value of the output power is larger than a preset first power threshold value, if so, recording the fluctuation of the power output once; if not, the power supply battery works normally;
acquiring a power output fluctuation secondary value based on a preset third time period;
judging whether the power output fluctuation frequency value is larger than a preset second frequency threshold value or not, and if yes, triggering prompt information;
and sending the prompt information to a preset management terminal for display.
According to the method and the system for prolonging the service life of the power supply battery of the fire-fighting Internet of things equipment, provided by the application, whether the environmental data of the power supply battery of the current equipment is normal or not is determined through comparing and analyzing the environmental data of the power supply battery of the current equipment with the preset standard environmental data, if so, the working environment of the power supply battery of the corresponding equipment is normal, and if not, the working environment of the power supply battery of the current equipment is correspondingly adjusted; meanwhile, the application monitors the output power of the equipment power supply battery and maintains the output power of the equipment power supply battery in a stable state. The service life of the power supply battery of the equipment is prolonged by monitoring the working environment and the output power of the power supply battery of the equipment and correspondingly adjusting the working environment and the output power.
Drawings
FIG. 1 illustrates a flow chart of a method of the present application for improving the life of a fire-fighting Internet of things device power supply battery;
FIG. 2 shows a flow chart of a system for improving the life of a power supply battery of a fire-fighting Internet of things device of the present application;
fig. 3 shows a block diagram of a system for improving the life of a power supply battery of a fire-fighting internet of things device according to the present application.
Description of the embodiments
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced in other ways than those described herein, and therefore the scope of the present application is not limited to the specific embodiments disclosed below.
Fig. 1 shows a flowchart of a method for improving service life of a power supply battery of a fire-fighting internet of things device according to the application.
As shown in fig. 1, the application discloses a method for prolonging service life of a power supply battery of fire-fighting internet of things equipment, which comprises the following steps:
s101, acquiring environmental data of a current equipment power supply battery;
s102, preprocessing environment data to obtain a first characteristic value;
s103, carrying out difference value calculation on the first characteristic value and a preset characteristic value to obtain a first data difference;
s104, judging whether the absolute value of the first data difference is larger than a preset data difference threshold value, if so, extracting a time value corresponding to the duration of the first data difference; if not, the current equipment power supply battery is normal;
s105, judging whether the duration time value of the first data difference is larger than a preset first time threshold value, and if so, triggering abnormal prompt information of the battery environment; if not, recording the first data difference for abnormal time;
s106, extracting an abnormal frequency value of the first data difference;
s107, judging whether the abnormal frequency value of the first data difference is larger than a preset first frequency threshold value, if so, triggering abnormal prompt information of the battery environment; if not, the current equipment power supply battery is normal;
s108, adjusting the current battery environment according to the battery environment abnormality prompt information.
According to an embodiment of the present application, the environmental data of the current device power supply battery includes: the method comprises the steps of recording the abnormal times of a first data difference, such as the temperature, the humidity, the acidity and alkalinity of a working environment of a power supply battery, and the like, wherein the abnormal times of the first data difference have certain timeliness, and clearing the abnormal times of the first data difference after the timeliness is exceeded, for example, the effective time value is 30 minutes, when the abnormal times of the first data difference can only be reserved for 30 minutes, clearing the abnormal times of the corresponding first data difference after the effective time is exceeded, and reserving the abnormal times of the first data difference with timeliness. The preset data difference threshold, the first time threshold and the first time count threshold are all set by a person skilled in the art.
According to an embodiment of the present application, the step of preprocessing the environmental data to obtain the first feature value specifically includes:
extracting a factor value in the current environment data;
normalizing the factor values in the current environment data to obtain first factor values;
inquiring in a preset characteristic weight coefficient table according to the first factor value to obtain a characteristic weight coefficient corresponding to the first factor value;
multiplying the first factor value by the corresponding characteristic weight coefficient to obtain a first factor characteristic value;
and accumulating the first factor characteristic values to obtain first characteristic values.
The method includes setting data, such as temperature, humidity, acidity and alkalinity, in environmental data, which have influences on the service life of a battery as factor values in current environmental data, normalizing the factor values to obtain first factor values, and storing characteristic weight coefficients corresponding to the first factor values in a preset characteristic weight coefficient table.
According to an embodiment of the present application, the step of normalizing the factor value in the current environmental data to obtain a first factor value specifically includes:
acquiring a factor value in historical environment data;
arranging the factor values in the historical environment data in order from small to large to obtain a maximum historical factor value and a minimum historical factor value;
subtracting the minimum historical factor value from the factor value in the current environment data to obtain a first factor difference value, and subtracting the minimum historical factor value from the maximum historical factor value to obtain a second factor difference value;
the first factor value is the ratio of the first factor difference value to the second factor difference value.
It should be noted that, normalization processing is performed on different factor values to obtain a first factor value with a unified unit.
According to an embodiment of the present application, further comprising:
acquiring historical environment data of a power supply battery of the equipment based on a preset first time period;
comparing and analyzing the historical environment data with preset ideal environment data to obtain similarity;
sequentially arranging the similarity according to the sequence from small to large, and extracting the maximum similarity;
and setting the historical environment data corresponding to the maximum similarity as standard environment data.
It should be noted that, for example, if the first time period is preset to be 30 days, historical environmental data of all the power supply batteries of the equipment within 30 days is extracted, the historical environmental data of all the power supply batteries of the equipment within 30 days is sequentially compared with preset ideal environmental data to obtain a plurality of similarities, the maximum similarity in the plurality of similarities is extracted, and the historical environmental data corresponding to the maximum similarity is set as standard environmental data.
According to an embodiment of the present application, further comprising:
extracting a factor value in standard environment data;
normalizing the factor values in the standard environment data to obtain second factor values;
inquiring in a preset characteristic weight coefficient table according to the second factor value to obtain a second characteristic weight coefficient corresponding to the second factor value;
multiplying the second factor value by a corresponding second characteristic weight coefficient to obtain a second factor characteristic value;
and accumulating the second factor characteristic values to obtain preset characteristic values.
The preset characteristic value is a characteristic value obtained after preprocessing the standard environmental data.
According to the embodiment of the application, the step of adjusting the current battery environment according to the battery environment abnormality prompting information specifically comprises the following steps:
performing difference calculation on the first factor characteristic value and the second factor characteristic value to obtain a factor characteristic difference value;
sequentially arranging different factor characteristic differences in sequence from large to small to obtain a maximum factor characteristic difference;
and setting the factor corresponding to the maximum factor characteristic difference as a first target of current battery environment adjustment.
It should be noted that, when the factor characteristic difference value is larger, the factor value of the factor in the current environment data and the factor value of the factor in the standard environment data are larger, the factor with the largest difference is set as a first target of current battery environment adjustment, the factor with the second largest difference is set as a second target of current battery environment adjustment, and so on.
According to an embodiment of the present application, further comprising:
acquiring a power supply battery output power data set based on a preset second time period;
extracting the maximum output power and the minimum output power in the power supply battery output power data set;
calculating the difference value between the maximum output power and the minimum output power to obtain an output power fluctuation value;
judging whether the fluctuation value of the output power is larger than a preset first power threshold value, if so, recording the fluctuation of the power output once; if not, the power supply battery works normally;
acquiring a power output fluctuation secondary value based on a preset third time period;
judging whether the power output fluctuation frequency value is larger than a preset second frequency threshold value or not, and if yes, triggering prompt information;
and sending the prompt information to a preset management terminal for display.
It should be noted that, the output power of the power supply battery is calculated by multiplying the output current of the power supply battery by the power supply voltage, the output current of the power supply battery is obtained in real time by a preset battery power supply type current sensor, the power supply voltage is determined by the power supply battery setting, the preset third time period is greater than the preset second time period, and the preset second time period is the time of the power supply battery of the device in the same fire-fighting state, for example, the preset second time period is the time under normal working or the preset second time period is the time during the fire-fighting alarm. The preset second time period, the preset third time period, the preset first power threshold and the preset second time threshold are all set by a person skilled in the art.
According to an embodiment of the present application, further comprising:
judging whether the maximum output power or the minimum output power is in a preset power range, if so, enabling the equipment power supply battery to work normally; if not, triggering abnormal prompting information of the power supply battery of the equipment;
and sending the prompt message of abnormal operation of the power supply battery of the triggering device to a preset management terminal for display.
The maximum output power or the minimum output power includes the output power of the power supply battery of the device under the normal working condition and the output power during the consumption alarm; the preset power range is divided into a preset first power range and a preset second power range, wherein the preset first power range is the power range of the power supply battery of the equipment under the normal working condition; the preset second power range is the power range of the equipment power supply battery during the fire alarm; the preset power range corresponding to the output power of the battery under the normal working condition is a preset first power range, and the preset second power range corresponding to the output power of the battery during the fire alarm period is preset. The preset power range is set by a person skilled in the art.
According to an embodiment of the present application, further comprising:
acquiring real-time electric quantity of a power supply battery of the equipment;
judging whether the real-time electric quantity of the equipment power supply battery is lower than a preset first electric quantity threshold value, if so, charging the equipment power supply battery, and recording the real-time electric quantity;
judging whether the real-time electric quantity is equal to a preset second electric quantity threshold value, if so, stopping charging the power supply battery of the equipment, and recording the charging time;
judging whether the charging time is greater than a preset time threshold, if so, triggering abnormal charging information;
and sending the abnormal charging information to a preset management terminal for display.
It should be noted that, when the electric quantity of the power supply battery of the device is lower than a preset first electric quantity threshold, the power supply battery of the device is started to have an automatic charging function, and the real-time electric quantity and the current first time are recorded; when the real-time electric quantity of the equipment power supply battery is equal to a preset second electric quantity threshold value, the equipment power supply battery stops charging, the current second time is recorded, the charging time is the difference value of the current second time minus the current first time, and the preset first electric quantity threshold value, the preset second electric quantity threshold value and the preset time threshold value are all set by a person skilled in the art.
Fig. 2 shows a flowchart of a system for improving the service life of a power supply battery of a fire-fighting internet of things device according to the application.
As shown in fig. 2, the application is applied to various sensors of the fire-fighting internet of things, the fire-fighting site is detected in real time through the various sensors, for example, the temperature value of the working environment of a power supply battery and the temperature value of a fire-fighting end are obtained through a battery-powered temperature sensor, the power supply current of the power supply battery is obtained in real time through a battery-powered current sensor, and the like, and then the obtained data are transmitted to a data processing system through the fire-fighting internet of things, wherein the fire-fighting internet of things transmission network framework comprises a star network, a tree network, a cluster tree network and a mesh network.
Fig. 3 shows a block diagram of a system for improving the life of a power supply battery of a fire-fighting internet of things device according to the present application.
As shown in fig. 3, a second aspect of the present application provides a system 3 for improving service life of a power supply battery of a fire-fighting internet of things device, including a memory 31 and a processor 32, where a method program for improving service life of a power supply battery of a fire-fighting internet of things device is stored in the memory, and when the method program for improving service life of a power supply battery of a fire-fighting internet of things device is executed by the processor, the following steps are implemented:
acquiring environmental data of a power supply battery of the current equipment;
preprocessing the environmental data to obtain a first characteristic value;
performing difference calculation on the first characteristic value and a preset characteristic value to obtain a first data difference;
judging whether the absolute value of the first data difference is larger than a preset data difference threshold value, if so, extracting a corresponding duration value of the first data difference; if not, the current equipment power supply battery is normal;
judging whether the duration time value of the first data difference is larger than a preset first time threshold value, if so, triggering abnormal prompt information of the battery environment; if not, recording the first data difference for abnormal time;
extracting the abnormal times value of the first data difference;
judging whether the abnormal frequency value of the first data difference is larger than a preset first frequency threshold value, if so, triggering abnormal prompt information of the battery environment; if not, the current equipment power supply battery is normal;
and adjusting the current battery environment according to the battery environment abnormality prompt information.
According to an embodiment of the present application, the environmental data of the current device power supply battery includes: the method comprises the steps of recording the abnormal times of a first data difference, such as the temperature, the humidity, the acidity and alkalinity of a working environment of a power supply battery, and the like, wherein the abnormal times of the first data difference have certain timeliness, and clearing the abnormal times of the first data difference after the timeliness is exceeded, for example, the effective time value is 30 minutes, when the abnormal times of the first data difference can only be reserved for 30 minutes, clearing the abnormal times of the corresponding first data difference after the effective time is exceeded, and reserving the abnormal times of the first data difference with timeliness. The preset data difference threshold, the first time threshold and the first time count threshold are all set by a person skilled in the art.
According to an embodiment of the present application, the step of preprocessing the environmental data to obtain the first feature value specifically includes:
extracting a factor value in the current environment data;
normalizing the factor values in the current environment data to obtain first factor values;
inquiring in a preset characteristic weight coefficient table according to the first factor value to obtain a characteristic weight coefficient corresponding to the first factor value;
multiplying the first factor value by the corresponding characteristic weight coefficient to obtain a first factor characteristic value;
and accumulating the first factor characteristic values to obtain first characteristic values.
The method includes setting data, such as temperature, humidity, acidity and alkalinity, in environmental data, which have influences on the service life of a battery as factor values in current environmental data, normalizing the factor values to obtain first factor values, and storing characteristic weight coefficients corresponding to the first factor values in a preset characteristic weight coefficient table.
According to an embodiment of the present application, the step of normalizing the factor value in the current environmental data to obtain a first factor value specifically includes:
acquiring a factor value in historical environment data;
arranging the factor values in the historical environment data in order from small to large to obtain a maximum historical factor value and a minimum historical factor value;
subtracting the minimum historical factor value from the factor value in the current environment data to obtain a first factor difference value, and subtracting the minimum historical factor value from the maximum historical factor value to obtain a second factor difference value;
the first factor value is the ratio of the first factor difference value to the second factor difference value.
It should be noted that, normalization processing is performed on different factor values to obtain a first factor value with a unified unit.
According to an embodiment of the present application, further comprising:
acquiring historical environment data of a power supply battery of the equipment based on a preset first time period;
comparing and analyzing the historical environment data with preset ideal environment data to obtain similarity;
sequentially arranging the similarity according to the sequence from small to large, and extracting the maximum similarity;
and setting the historical environment data corresponding to the maximum similarity as standard environment data.
It should be noted that, for example, if the first time period is preset to be 30 days, historical environmental data of all the power supply batteries of the equipment within 30 days is extracted, the historical environmental data of all the power supply batteries of the equipment within 30 days is sequentially compared with preset ideal environmental data to obtain a plurality of similarities, the maximum similarity in the plurality of similarities is extracted, and the historical environmental data corresponding to the maximum similarity is set as standard environmental data.
According to an embodiment of the present application, further comprising:
extracting a factor value in standard environment data;
normalizing the factor values in the standard environment data to obtain second factor values;
inquiring in a preset characteristic weight coefficient table according to the second factor value to obtain a second characteristic weight coefficient corresponding to the second factor value;
multiplying the second factor value by a corresponding second characteristic weight coefficient to obtain a second factor characteristic value;
and accumulating the second factor characteristic values to obtain preset characteristic values.
The preset characteristic value is a characteristic value obtained after preprocessing the standard environmental data.
According to the embodiment of the application, the step of adjusting the current battery environment according to the battery environment abnormality prompting information specifically comprises the following steps:
performing difference calculation on the first factor characteristic value and the second factor characteristic value to obtain a factor characteristic difference value;
sequentially arranging different factor characteristic differences in sequence from large to small to obtain a maximum factor characteristic difference;
and setting the factor corresponding to the maximum factor characteristic difference as a first target of current battery environment adjustment.
It should be noted that, when the factor characteristic difference value is larger, the factor value of the factor in the current environment data and the factor value of the factor in the standard environment data are larger, the factor with the largest difference is set as a first target of current battery environment adjustment, the factor with the second largest difference is set as a second target of current battery environment adjustment, and so on.
According to an embodiment of the present application, further comprising:
acquiring a power supply battery output power data set based on a preset second time period;
extracting the maximum output power and the minimum output power in the power supply battery output power data set;
calculating the difference value between the maximum output power and the minimum output power to obtain an output power fluctuation value;
judging whether the fluctuation value of the output power is larger than a preset first power threshold value, if so, recording the fluctuation of the power output once; if not, the power supply battery works normally;
acquiring a power output fluctuation secondary value based on a preset third time period;
judging whether the power output fluctuation frequency value is larger than a preset second frequency threshold value or not, and if yes, triggering prompt information;
and sending the prompt information to a preset management terminal for display.
It should be noted that, the output power of the power supply battery is calculated by multiplying the output current of the power supply battery by the power supply voltage, the output current of the power supply battery is obtained in real time by a preset battery power supply type current sensor, the power supply voltage is determined by the power supply battery setting, the preset third time period is greater than the preset second time period, and the preset second time period is the time of the power supply battery of the device in the same fire-fighting state, for example, the preset second time period is the time under normal working or the preset second time period is the time during the fire-fighting alarm. The preset second time period, the preset third time period, the preset first power threshold and the preset second time threshold are all set by a person skilled in the art.
According to an embodiment of the present application, further comprising:
judging whether the maximum output power or the minimum output power is in a preset power range, if so, enabling the equipment power supply battery to work normally; if not, triggering abnormal prompting information of the power supply battery of the equipment;
and sending the prompt message of abnormal operation of the power supply battery of the triggering device to a preset management terminal for display.
The maximum output power or the minimum output power includes the output power of the power supply battery of the device under the normal working condition and the output power during the consumption alarm; the preset power range is divided into a preset first power range and a preset second power range, wherein the preset first power range is the power range of the power supply battery of the equipment under the normal working condition; the preset second power range is the power range of the equipment power supply battery during the fire alarm; the preset power range corresponding to the output power of the battery under the normal working condition is a preset first power range, and the preset second power range corresponding to the output power of the battery during the fire alarm period is preset. The preset power range is set by a person skilled in the art.
According to an embodiment of the present application, further comprising:
acquiring real-time electric quantity of a power supply battery of the equipment;
judging whether the real-time electric quantity of the equipment power supply battery is lower than a preset first electric quantity threshold value, if so, charging the equipment power supply battery, and recording the real-time electric quantity;
judging whether the real-time electric quantity is equal to a preset second electric quantity threshold value, if so, stopping charging the power supply battery of the equipment, and recording the charging time;
judging whether the charging time is greater than a preset time threshold, if so, triggering abnormal charging information;
and sending the abnormal charging information to a preset management terminal for display.
It should be noted that, when the electric quantity of the power supply battery of the device is lower than a preset first electric quantity threshold, the power supply battery of the device is started to have an automatic charging function, and the real-time electric quantity and the current first time are recorded; when the real-time electric quantity of the equipment power supply battery is equal to a preset second electric quantity threshold value, the equipment power supply battery stops charging, the current second time is recorded, the charging time is the difference value of the current second time minus the current first time, and the preset first electric quantity threshold value, the preset second electric quantity threshold value and the preset time threshold value are all set by a person skilled in the art.
According to the method and the system for prolonging the service life of the power supply battery of the fire-fighting Internet of things equipment, provided by the application, whether the environmental data of the power supply battery of the current equipment is normal or not is determined through comparing and analyzing the environmental data of the power supply battery of the current equipment with the preset standard environmental data, if so, the working environment of the power supply battery of the corresponding equipment is normal, and if not, the working environment of the power supply battery of the current equipment is correspondingly adjusted; meanwhile, the application monitors the output power of the equipment power supply battery and maintains the output power of the equipment power supply battery in a stable state. The service life of the power supply battery of the equipment is prolonged by monitoring the working environment and the output power of the power supply battery of the equipment and correspondingly adjusting the working environment and the output power.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present application may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present application may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
Claims (6)
1. The method for prolonging the service life of the power supply battery of the fire-fighting Internet of things equipment is characterized by comprising the following steps:
acquiring environmental data of a power supply battery of the current equipment;
preprocessing the environmental data to obtain a first characteristic value;
performing difference calculation on the first characteristic value and a preset characteristic value to obtain a first data difference;
judging whether the absolute value of the first data difference is larger than a preset data difference threshold value, if so, extracting a corresponding duration value of the first data difference; if not, the current equipment power supply battery is normal;
judging whether the duration time value of the first data difference is larger than a preset first time threshold value, if so, triggering abnormal prompt information of the battery environment; if not, recording the first data difference for abnormal time;
extracting the abnormal times value of the first data difference;
judging whether the abnormal frequency value of the first data difference is larger than a preset first frequency threshold value, if so, triggering abnormal prompt information of the battery environment; if not, the current equipment power supply battery is normal;
adjusting the current battery environment according to the battery environment abnormality prompt information;
the step of preprocessing the environmental data to obtain a first characteristic value specifically includes:
extracting a factor value in the current environment data;
normalizing the factor values in the current environment data to obtain first factor values;
inquiring in a preset characteristic weight coefficient table according to the first factor value to obtain a characteristic weight coefficient corresponding to the first factor value;
multiplying the first factor value by the corresponding characteristic weight coefficient to obtain a first factor characteristic value;
accumulating the first factor characteristic values to obtain first characteristic values;
further comprises:
acquiring historical environment data of a power supply battery of the equipment based on a preset first time period;
comparing and analyzing the historical environment data with preset ideal environment data to obtain similarity;
sequentially arranging the similarity according to the sequence from small to large, and extracting the maximum similarity;
setting historical environment data corresponding to the maximum similarity as standard environment data;
further comprises:
extracting a factor value in standard environment data;
normalizing the factor values in the standard environment data to obtain second factor values;
inquiring in a preset characteristic weight coefficient table according to the second factor value to obtain a second characteristic weight coefficient corresponding to the second factor value;
multiplying the second factor value by a corresponding second characteristic weight coefficient to obtain a second factor characteristic value;
and accumulating the second factor characteristic values to obtain preset characteristic values.
2. The method for improving the service life of a power supply battery of a fire-fighting internet of things device according to claim 1, wherein the step of normalizing factor values in the current environmental data to obtain first factor values specifically comprises:
acquiring a factor value in historical environment data;
arranging the factor values in the historical environment data in order from small to large to obtain a maximum historical factor value and a minimum historical factor value;
subtracting the minimum historical factor value from the factor value in the current environment data to obtain a first factor difference value, and subtracting the minimum historical factor value from the maximum historical factor value to obtain a second factor difference value;
the first factor value is the ratio of the first factor difference value to the second factor difference value.
3. The method for prolonging the service life of a power supply battery of a fire-fighting internet of things device according to claim 1, wherein the step of adjusting the current battery environment according to the battery environment abnormality prompt message specifically comprises the following steps:
performing difference calculation on the first factor characteristic value and the second factor characteristic value to obtain a factor characteristic difference value;
sequentially arranging different factor characteristic differences in sequence from large to small to obtain a maximum factor characteristic difference;
and setting the factor corresponding to the maximum factor characteristic difference as a first target of current battery environment adjustment.
4. The method for improving the service life of a power supply battery of a fire-fighting internet of things device according to claim 1, further comprising:
acquiring a power supply battery output power data set based on a preset second time period;
extracting the maximum output power and the minimum output power in the power supply battery output power data set;
calculating the difference value between the maximum output power and the minimum output power to obtain an output power fluctuation value;
judging whether the fluctuation value of the output power is larger than a preset first power threshold value, if so, recording the fluctuation of the power output once; if not, the power supply battery works normally;
acquiring a power output fluctuation secondary value based on a preset third time period;
judging whether the power output fluctuation frequency value is larger than a preset second frequency threshold value or not, and if yes, triggering prompt information;
and sending the prompt information to a preset management terminal for display.
5. The system for improving the service life of the power supply battery of the fire-fighting Internet of things device is characterized by comprising a memory and a processor, wherein a method program for improving the service life of the power supply battery of the fire-fighting Internet of things device is stored in the memory, and the method program for improving the service life of the power supply battery of the fire-fighting Internet of things device is implemented when executed by the processor and comprises the following steps:
acquiring environmental data of a power supply battery of the current equipment;
preprocessing the environmental data to obtain a first characteristic value;
performing difference calculation on the first characteristic value and a preset characteristic value to obtain a first data difference;
judging whether the absolute value of the first data difference is larger than a preset data difference threshold value, if so, extracting a corresponding duration value of the first data difference; if not, the current equipment power supply battery is normal;
judging whether the duration time value of the first data difference is larger than a preset first time threshold value, if so, triggering abnormal prompt information of the battery environment; if not, recording the first data difference for abnormal time;
extracting the abnormal times value of the first data difference;
judging whether the abnormal frequency value of the first data difference is larger than a preset first frequency threshold value, if so, triggering abnormal prompt information of the battery environment; if not, the current equipment power supply battery is normal;
adjusting the current battery environment according to the battery environment abnormality prompt information;
the step of preprocessing the environmental data to obtain a first characteristic value specifically includes:
extracting a factor value in the current environment data;
normalizing the factor values in the current environment data to obtain first factor values;
inquiring in a preset characteristic weight coefficient table according to the first factor value to obtain a characteristic weight coefficient corresponding to the first factor value;
multiplying the first factor value by the corresponding characteristic weight coefficient to obtain a first factor characteristic value;
accumulating the first factor characteristic values to obtain first characteristic values;
further comprises:
acquiring historical environment data of a power supply battery of the equipment based on a preset first time period;
comparing and analyzing the historical environment data with preset ideal environment data to obtain similarity;
sequentially arranging the similarity according to the sequence from small to large, and extracting the maximum similarity;
setting historical environment data corresponding to the maximum similarity as standard environment data;
further comprises:
extracting a factor value in standard environment data;
normalizing the factor values in the standard environment data to obtain second factor values;
inquiring in a preset characteristic weight coefficient table according to the second factor value to obtain a second characteristic weight coefficient corresponding to the second factor value;
multiplying the second factor value by a corresponding second characteristic weight coefficient to obtain a second factor characteristic value;
and accumulating the second factor characteristic values to obtain preset characteristic values.
6. The system for improving service life of a power supply battery of a fire-fighting internet of things device according to claim 5, wherein the step of normalizing factor values in the current environmental data to obtain first factor values specifically comprises:
acquiring a factor value in historical environment data;
arranging the factor values in the historical environment data in order from small to large to obtain a maximum historical factor value and a minimum historical factor value;
subtracting the minimum historical factor value from the factor value in the current environment data to obtain a first factor difference value, and subtracting the minimum historical factor value from the maximum historical factor value to obtain a second factor difference value;
the first factor value is the ratio of the first factor difference value to the second factor difference value.
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