CN113963526B - Fire-fighting equipment quality detection method and device based on cloud platform and storage medium - Google Patents
Fire-fighting equipment quality detection method and device based on cloud platform and storage medium Download PDFInfo
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- CN113963526B CN113963526B CN202111054516.0A CN202111054516A CN113963526B CN 113963526 B CN113963526 B CN 113963526B CN 202111054516 A CN202111054516 A CN 202111054516A CN 113963526 B CN113963526 B CN 113963526B
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
- G08B29/18—Prevention or correction of operating errors
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/06—Electric actuation of the alarm, e.g. using a thermally-operated switch
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/10—Actuation by presence of smoke or gases, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
- G08B29/18—Prevention or correction of operating errors
- G08B29/185—Signal analysis techniques for reducing or preventing false alarms or for enhancing the reliability of the system
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B7/00—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00
- G08B7/06—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources
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Abstract
The application provides a fire-fighting equipment quality detection method, a fire-fighting equipment quality detection device and a storage medium based on a cloud platform, wherein the cloud platform can acquire sensing data and alarm data of each fire-fighting equipment, and the method comprises the following steps: classifying fire-fighting equipment connected to the cloud platform, and grouping all the categories; acquiring sensing data and alarm data uploaded to a cloud platform by each class of fire fighting equipment, and obtaining a standard value corresponding to each class after carrying out statistical analysis on the sensing data and the alarm data of each class; comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the error value is used to adjust the parameters of all fire fighting equipment within the corresponding group. In consideration of the fact that systematic errors which are difficult to perceive may occur in fire-fighting equipment produced in the same batch, all fire-fighting equipment which is connected into the cloud platform are detected and analyzed to obtain fire-fighting equipment which may have problems, and accordingly the fire-fighting equipment which may have problems is adjusted.
Description
Technical Field
The application relates to the technical field of big data analysis, in particular to a fire fighting equipment quality detection method and device based on a cloud platform and a storage medium.
Background
The sensing type fire-fighting equipment can be subjected to sensing precision test when leaving the factory, for example, the fire-fighting equipment can be a smoke alarm, and each manufacturer can be subjected to sensing precision test on the smoke alarm when leaving the factory, and the test is often carried out under laboratory conditions. Because the preset experimental conditions of each manufacturer are different, when the experimental condition setting is greatly deviated from the actual setting, the sensing precision of the smoke sensor is insufficient, and the systematic error manufacturer cannot perceive and correct the error.
Disclosure of Invention
The application provides a fire-fighting equipment quality detection method and device based on a cloud platform and a storage medium, aiming at solving the technical problem that the sensing precision of the existing fire-fighting equipment is not high.
The application provides a fire-fighting equipment quality detection method based on a cloud platform, which can acquire sensing data and alarm data of each fire-fighting equipment and comprises the following steps:
classifying fire-fighting equipment connected to the cloud platform, and grouping all the categories;
acquiring sensing data and alarm data uploaded to a cloud platform by each class of fire fighting equipment, and obtaining a standard value corresponding to each class after carrying out statistical analysis on the sensing data and the alarm data of each class;
comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the error value is used to adjust the parameters of all fire fighting equipment within the corresponding group.
According to some embodiments, the step of classifying the fire protection equipment that is connected to the cloud platform comprises:
fire-fighting equipment with the same type of the manufacturer and the same equipment are classified into the same class; each category has a manufacturer identification and a type identification.
According to some embodiments, the step of grouping all categories comprises:
all the categories are grouped, and the categories with the same type identification are classified into the same group.
According to some embodiments, the fire protection device comprises a smoke alarm, the smoke alarm presets an early warning threshold and an alarm threshold, the early warning threshold corresponds to a first smoke concentration, the alarm threshold corresponds to a second smoke concentration, the second smoke concentration is greater than the first smoke concentration, the smoke alarm transmits an early warning signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the first smoke concentration, and the smoke alarm transmits an alarm signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the second smoke concentration;
comparing and analyzing different standard values in the same group to obtain error values in the same group; wherein the step of adjusting the error value for parameters of all fire fighting devices within the corresponding group comprises:
acquiring an early warning threshold value and an alarm threshold value of each smoke alarm in each category;
acquiring real fire data, wherein the real fire data comprises a real early warning threshold value, a real warning threshold value, manufacturer information and a time interval between sending an early warning signal and sending an alarm signal of a smoke alarm in an area where a fire disaster occurs;
when the time interval is in a preset time period, taking the difference value between a preset early warning threshold value and a real early warning threshold value corresponding to each category as a first error value, and correspondingly adjusting the preset early warning threshold value in each category to approach the real early warning threshold value; and taking the difference value between the preset alarm threshold value corresponding to each category and the real alarm threshold value as a second error value, and correspondingly adjusting the preset alarm threshold value in each category to approach the real alarm threshold value.
According to some embodiments, the fire protection device comprises a smoke alarm, the smoke alarm presets an early warning threshold and an alarm threshold, the early warning threshold corresponds to a first smoke concentration, the alarm threshold corresponds to a second smoke concentration, the second smoke concentration is greater than the first smoke concentration, the smoke alarm transmits an early warning signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the first smoke concentration, and the smoke alarm transmits an alarm signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the second smoke concentration;
comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the step of adjusting the error value for parameters of all fire fighting devices within the corresponding group comprises:
acquiring early warning threshold values of the smoke alarms in each category, acquiring early warning times of the smoke alarms in each category in preset time, and acquiring average early warning times of the smoke alarms in the preset time in each category;
the error value in the same group is preset, and when the maximum average early warning times and the minimum average early warning times in the same group are larger than the error value, the early warning threshold value of the smoke alarm corresponding to the maximum average early warning times is increased, and the early warning threshold value of the smoke alarm corresponding to the minimum early warning times is reduced.
According to some embodiments, the fire protection device comprises a smoke alarm, the smoke alarm presets an early warning threshold and an alarm threshold, the early warning threshold corresponds to a first smoke concentration, the alarm threshold corresponds to a second smoke concentration, the second smoke concentration is greater than the first smoke concentration, the smoke alarm transmits an early warning signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the first smoke concentration, and the smoke alarm transmits an alarm signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the second smoke concentration;
comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the step of adjusting the error value for parameters of all fire fighting devices within the corresponding group comprises:
acquiring early warning threshold values of all smoke alarms in each category, acquiring early warning times of all the smoke alarms in each category in preset time, and selecting the smoke alarms as target alarms when the warning times of all the smoke alarms in the preset time are higher than the preset times;
obtaining average early warning times of the target smoke alarms in preset time in each category;
the error value in the same group is preset, and when the maximum average early warning times and the minimum average early warning times in the same group are larger than the error value, the early warning threshold value of the smoke alarm corresponding to the maximum average early warning times is increased, and the early warning threshold value of the smoke alarm corresponding to the minimum early warning times is reduced.
The second aspect of the application also provides a fire-fighting equipment quality detection device based on cloud platform big data analysis, which comprises:
the signal receiving module is used for receiving sensing signals and alarm signals of all the fire-fighting equipment;
the analysis processing module classifies fire-fighting equipment accessed to the cloud platform and groups all the categories; and is used for comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the error value is used to adjust the parameters of all fire fighting equipment within the corresponding group.
According to some embodiments, the signal receiving module is further configured to obtain real fire data, where the real fire data includes a real early warning threshold, a real warning threshold, manufacturer information, and a time interval between sending the early warning signal and sending the warning signal of the smoke alarm in an area where the fire occurs;
the analysis processing module is also used for taking the difference value between the early warning threshold value corresponding to each class and the real early warning threshold value as a first error value when the time interval is in a preset time period, and correspondingly adjusting the early warning threshold value in each class to approach the real early warning threshold value; taking the difference value between the alarm threshold value corresponding to each category and the real alarm threshold value as a second error value, and correspondingly adjusting the alarm threshold value in each category to approach the real alarm threshold value
According to some embodiments, the signal receiving module is further configured to obtain an early warning threshold of each smoke alarm in each category, obtain an early warning number of each smoke alarm in each category in a preset time, and obtain an average early warning number of a single smoke alarm in the preset time;
the analysis processing module is also used for presetting error values in the same group, and when the maximum average early warning times and the minimum average early warning times in the same group are larger than the error values, the early warning threshold of the smoke alarm corresponding to the maximum average early warning times is improved, and the early warning threshold of the smoke alarm corresponding to the minimum early warning times is reduced.
The third aspect of the present application also provides a storage medium having stored thereon computer instructions which, when executed by a processor, implement the fire protection equipment quality detection method based on cloud platform big data analysis of any one of the preceding claims.
Compared with the prior art, the fire-fighting equipment quality detection method based on cloud platform big data analysis provided by the application considers that the fire-fighting equipment produced in the same batch can have imperceptible systematic errors, and the fire-fighting equipment possibly having problems is obtained by detecting and analyzing all the fire-fighting equipment connected to the cloud platform, so that the fire-fighting equipment possibly having problems is adjusted.
Drawings
Fig. 1 is a flowchart of a fire fighting equipment quality detection method based on a cloud platform according to a first embodiment of the present application;
fig. 2 is a block diagram of a fire fighting equipment quality detection device based on a cloud platform according to a first embodiment of the present application.
Detailed Description
For the purpose of making the technical solution and advantages of the present application more apparent, the present application will be further described in detail below with reference to the accompanying drawings and examples of implementation. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for illustrative purposes only.
The sensing type fire-fighting equipment can be subjected to sensing precision test when leaving the factory, for example, the fire-fighting equipment can be a smoke alarm, and each manufacturer can be subjected to sensing precision test on the smoke alarm when leaving the factory, and the test is often carried out under laboratory conditions. Because the preset experimental conditions of each manufacturer are different, when the experimental condition setting is greatly deviated from the actual setting, the sensing precision of the smoke sensors of some manufacturers is insufficient, and the systematic error manufacturer cannot perceive and correct the error, and the error occurs in batches by the manufacturer.
In view of the above, referring to fig. 1, the present application provides a fire fighting equipment quality detection method based on a cloud platform, which can obtain sensing data and alarm data of each fire fighting equipment.
The cloud platform is used for being connected with various fire-fighting equipment of various factories, and the fire-fighting equipment can be specifically a smoke alarm, a temperature sensing detector, an audible and visual alarm, a manual alarm, a combustible gas detection alarm, a carbon monoxide detection alarm, a fire extinguisher, a camera and the like. The cloud platform can receive the sensing signals and the alarm signals of the equipment and can also remotely control the fire-fighting equipment.
Specifically, the cloud platform-based fire fighting equipment quality detection method comprises the following steps:
s101: and classifying the fire-fighting equipment connected to the cloud platform, and grouping all the categories. In a specific embodiment, fire-fighting equipment of the same type as the manufacturer may be classified into the same category. Fire-fighting equipment with the same type of the manufacturer and the equipment are classified into the same class; each category has a manufacturer identification and a type identification. Each category has a manufacturer identification and a type identification.
For example, the company a produced smoke alarms, temperature sensing detectors, audible and visual alarms. Company b has produced smoke alarms, temperature sensing detectors, audible and visual alarms. At this time, all smoke alarms of the first company are classified into one category, all temperature sensing detectors are classified into one category, and all audible and visual alarms are classified into one category. All smoke alarms of company b are classified into one category, all temperature sensing detectors are classified into one category, and all audible and visual alarms are classified into one category. The category of the smoke alarm of the company A and the category of the smoke alarm of the company B are divided into the same group, the category of the temperature sensing detector of the company A and the category of the temperature sensing detector of the company B are divided into the same group, the category of the sound and light alarm of the company A and the category of the sound and light alarm of the company B are divided into the same group. In other words, all fire-fighting equipment within the same group are of the same type, and the manufacturer varies from one class to another within the same group.
S102: and acquiring sensing data and alarm data uploaded to the cloud platform by the fire fighting equipment of each category, and obtaining a standard value corresponding to each category after carrying out statistical analysis on the sensing data and alarm data of each category.
S103: comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the error value is used to adjust the parameters of all fire fighting equipment within the corresponding group.
Compared with the prior art, the fire-fighting equipment quality detection method based on cloud platform big data analysis provided by the application considers that the fire-fighting equipment produced in the same batch can have imperceptible systematic errors, and the fire-fighting equipment possibly having problems is obtained by detecting and analyzing all the fire-fighting equipment connected to the cloud platform, so that the fire-fighting equipment possibly having problems is adjusted.
Fire-fighting equipment is numerous, and for convenience of description, the fire-fighting equipment is exemplified as a smoke alarm in the present application.
According to some embodiments, the fire protection device comprises a smoke alarm, the smoke alarm presets an early warning threshold and an alarm threshold, the early warning threshold corresponds to a first smoke concentration, the alarm threshold corresponds to a second smoke concentration, the second smoke concentration is greater than the first smoke concentration, the smoke alarm transmits an early warning signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the first smoke concentration, and the smoke alarm transmits an alarm signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the second smoke concentration.
That is, a typical smoke alarm sets two thresholds, and when a first smoke threshold is sensed to be high in smoke concentration, the alarm is triggered as soon as a hazard is considered to be generated. When it is sensed that the smoke concentration is above the second smoke threshold, the alarm signal is triggered, assuming that a hazard has occurred. Because the ideas of each manufacturer are different, the early warning or alarm threshold value of each manufacturer is initially set to be different.
Comparing and analyzing different standard values in the same group to obtain error values in the same group; wherein the step of adjusting the error value for parameters of all fire fighting devices within the corresponding group comprises:
acquiring an early warning threshold value and an alarm threshold value of each smoke alarm in each category;
acquiring real fire data, wherein the real fire data comprises a real early warning threshold value, a real warning threshold value, manufacturer information and a time interval between sending an early warning signal and sending an alarm signal of a smoke alarm in an area where a fire disaster occurs;
when the time interval is in a preset time period, taking the difference value between a preset early warning threshold value and a real early warning threshold value corresponding to each category as a first error value, and correspondingly adjusting the preset early warning threshold value in each category to approach the real early warning threshold value; and taking the difference value between the preset alarm threshold value corresponding to each category and the real alarm threshold value as a second error value, and correspondingly adjusting the preset alarm threshold value in each category to approach the real alarm threshold value.
For example, the preset time period is one minute to five minutes (the time is only used for example, the actual time is preset according to the needs), when the time interval from the early warning signal to the alarm signal is more than one minute and less than five minutes, the smoke alarm is considered to be qualified under the actual condition, and the threshold value of the smoke alarm is reasonably set, so that the early warning threshold value and the alarm threshold value of the smoke alarm can be used as standard value reference. Taking the difference value between the preset early warning threshold value and the real early warning threshold value corresponding to each category as a first error value, and correspondingly adjusting the preset early warning threshold value in each category to approach the real early warning threshold value; and taking the difference value between the preset alarm threshold value corresponding to each category and the real alarm threshold value as a second error value, and correspondingly adjusting the preset alarm threshold value in each category to approach the real alarm threshold value. As to how close it is, it can be according to the actual requirement.
According to some embodiments, the fire protection device comprises a smoke alarm, the smoke alarm presets an early warning threshold and an alarm threshold, the early warning threshold corresponds to a first smoke concentration, the alarm threshold corresponds to a second smoke concentration, the second smoke concentration is greater than the first smoke concentration, the smoke alarm transmits an early warning signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the first smoke concentration, and the smoke alarm transmits an alarm signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the second smoke concentration;
comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the step of adjusting the error value for parameters of all fire fighting devices within the corresponding group comprises:
acquiring early warning threshold values of the smoke alarms in each category, acquiring early warning times of the smoke alarms in each category in preset time, and acquiring average early warning times of the smoke alarms in the preset time in each category;
the error value in the same group is preset, and when the maximum average early warning times and the minimum average early warning times in the same group are larger than the error value, the early warning threshold value of the smoke alarm corresponding to the maximum average early warning times is increased, and the early warning threshold value of the smoke alarm corresponding to the minimum early warning times is reduced.
In the above embodiment, only the reasonability of the alarm threshold and the early warning threshold set by each manufacturer is considered (the alarm threshold and the early warning threshold of each manufacturer may be different, and the above scheme is only used for adjusting the alarm threshold and the early warning threshold). However, the inventor considers that the experimental environments of the two factories are different, so that when the early warning threshold value and the alarm threshold value of the smoke alarm of the two factories are the same, the problem that the actual sensing effect is different occurs. For example, when the early warning threshold of the first manufacturer is the same as the early warning threshold of the second manufacturer, in the actual sensing process, the situation that the early warning effect of the smoke alarm produced by the first manufacturer is closer to the actual situation than that of the smoke alarm produced by the second manufacturer can also occur. Due to the above situation, it is difficult to make the sensing effects of different manufacturers tend to be consistent (closer to reality) by adjusting the early warning and the alarm threshold.
In order to solve the above problems, according to some embodiments, a fire protection device includes a smoke alarm, the smoke alarm presets an early warning threshold and an alarm threshold, the early warning threshold corresponds to a first smoke concentration, the alarm threshold corresponds to a second smoke concentration, the second smoke concentration is greater than the first smoke concentration, the smoke alarm transmits an early warning signal to a cloud platform when the smoke concentration sensed by the smoke alarm is greater than the first smoke concentration, and the smoke alarm transmits an alarm signal to the cloud platform when the smoke concentration sensed by the smoke alarm is greater than the second smoke concentration;
comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the step of adjusting the error value for parameters of all fire fighting devices within the corresponding group comprises:
acquiring early warning threshold values of the smoke alarms in each category, acquiring early warning times of the smoke alarms in each category in preset time, and selecting the smoke alarms as target alarms when the warning times of the smoke alarms in the preset time are higher than the preset times.
Obtaining average early warning times of the target smoke alarms in preset time in each category; for example, when a first manufacturer has hundreds of smoke alarms, the number of early warning times of one hundred smoke alarms in a randomly selected period of time is higher than ten times, and the sum of the early warning times of the hundred smoke alarms is divided by one hundred to be the average early warning times. When the manufacturer B has fifty thousand smoke alarms, the early warning times of two hundred (data are only used as reference) smoke alarms in a randomly selected period of time are higher than ten times, and the sum of the early warning times of the two hundred smoke alarms is divided by two hundred to be used as the average early warning times.
The error value in the same group is preset, and when the maximum average early warning times and the minimum average early warning times in the same group are larger than the error value, the early warning threshold value of the smoke alarm corresponding to the maximum average early warning times is increased, and the early warning threshold value of the smoke alarm corresponding to the minimum early warning times is reduced. That is, when there are ten categories of manufacturers in a group, there are ten average warning times. When the obtained value is greater than five, the smoke alarms which are necessarily produced by the manufacturer are considered to have larger systematic errors (under the background of big data, the early warning times of the smoke alarms can reflect the sensitivity of the smoke alarms, and the premise is that all the obtained smoke alarms do not transmit alarm signals after the preset time, namely, when the smoke alarms transmit alarm signals again after transmitting the early warning signals, the smoke alarms are discharged from the statistical range). At this time, it is still unknown which manufacturer produces smoke alarms with larger system errors, so that the safety risk is reduced by adopting a mode that the early warning thresholds of all the smoke alarms tend to be uniform. Namely, the early warning threshold value of the smoke alarm corresponding to the maximum average early warning times is raised, and the early warning threshold value of the smoke alarm corresponding to the minimum early warning times is lowered. The specific rising and falling amounts depend on the actual requirements.
In the embodiment, the system error of each manufacturer can be corrected, the signal blockage can be avoided, the overall ineffective early warning frequency is reduced, and the bandwidth is dredged.
Referring to fig. 2, the second aspect of the present application further provides a fire-fighting equipment quality detection apparatus 100 based on cloud platform big data analysis, including:
a signal receiving module 110 for receiving sensing signals and alarm signals of various fire fighting equipments;
the analysis processing module 120 classifies fire-fighting equipment accessed to the cloud platform and groups all the categories; and is used for comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the error value is used to adjust the parameters of all fire fighting equipment within the corresponding group.
According to some embodiments, the signal receiving module 110 is further configured to obtain real fire data, where the real fire data includes a real early warning threshold, a real warning threshold, manufacturer information, and a time interval between sending the early warning signal and sending the warning signal of the smoke alarm in an area where the fire occurs before the fire occurs;
the analysis processing module 120 is further configured to take, when the time interval is within a preset time period, a difference value between the early warning threshold value corresponding to each category and the real early warning threshold value as a first error value, and correspondingly adjust the early warning threshold value in each category to approach the real early warning threshold value; taking the difference value between the alarm threshold value corresponding to each category and the real alarm threshold value as a second error value, and correspondingly adjusting the alarm threshold value in each category to approach the real alarm threshold value
According to some embodiments, the signal receiving module 110 is further configured to obtain an early warning threshold of each smoke alarm in each category, obtain the early warning times of each smoke alarm in each category in a preset time, and obtain an average early warning times of a single smoke alarm in the preset time;
the analysis processing module 120 is further configured to preset an error value in the same group, and when the maximum average early warning frequency and the minimum average early warning frequency in the same group are greater than the error value, raise the early warning threshold of the smoke alarm corresponding to the maximum average early warning frequency, and lower the early warning threshold of the smoke alarm corresponding to the minimum early warning frequency.
The third aspect of the present application also provides a storage medium having stored thereon computer instructions which, when executed by a processor, implement the fire fighting equipment quality detection method based on cloud platform big data analysis in any of the foregoing embodiments.
The above description is only of the preferred embodiments of the present application and is not intended to limit the application, but any modifications, equivalents, improvements, etc. within the principles of the present application should be included in the scope of the present application.
Claims (3)
1. The cloud platform based fire-fighting equipment quality detection method is characterized by comprising the following steps that the cloud platform can acquire sensing data and alarm data of each fire-fighting equipment:
classifying fire-fighting equipment connected to the cloud platform, and grouping all the categories;
acquiring sensing data and alarm data uploaded to a cloud platform by the fire fighting equipment of each category, and obtaining a standard value corresponding to each category after carrying out statistical analysis on the sensing data and the alarm data of each category;
comparing and analyzing different standard values in the same group, and determining error values in the same group; the error value is used for adjusting parameters of all the fire-fighting equipment in the corresponding group;
the step of classifying the fire fighting equipment accessing the cloud platform comprises the following steps:
classifying the fire-fighting equipment with the same type as the fire-fighting equipment of the manufacturer into the same category; each category has a manufacturer identifier and a type identifier;
the step of grouping all of the categories includes:
grouping all the categories, and classifying the categories with the same type identifier into the same group;
the fire-fighting equipment comprises a smoke alarm, wherein the smoke alarm is provided with an early warning threshold and an alarm threshold, the early warning threshold corresponds to a first smoke concentration, the alarm threshold corresponds to a second smoke concentration, the second smoke concentration is larger than the first smoke concentration, the smoke alarm transmits an early warning signal to the cloud platform when the smoke concentration sensed by the smoke alarm is higher than the first smoke concentration, and the smoke alarm transmits an alarm signal to the cloud platform when the smoke concentration sensed by the smoke alarm is higher than the second smoke concentration;
comparing and analyzing different standard values in the same group to obtain error values in the same group; wherein the step of adjusting the error value for all parameters of the fire fighting equipment within the corresponding group comprises:
acquiring the early warning threshold value and the warning threshold value of each smoke alarm in each category;
acquiring real fire data, wherein the real fire data comprises a real early warning threshold value, a real warning threshold value, manufacturer information and a time interval from sending an early warning signal to sending an alarm signal of a smoke alarm in an area where a fire disaster occurs;
when the time interval is in a preset time period, taking the difference value between the preset early warning threshold value corresponding to each category and the real early warning threshold value as a first error value, and correspondingly adjusting the preset early warning threshold value in each category to approach the real early warning threshold value; taking the difference value between the preset alarm threshold value corresponding to each category and the real alarm threshold value as a second error value, and correspondingly adjusting the preset alarm threshold value in each category to approach the real alarm threshold value;
the fire-fighting equipment comprises a smoke alarm, wherein the smoke alarm is provided with an early warning threshold and an alarm threshold, the early warning threshold corresponds to a first smoke concentration, the alarm threshold corresponds to a second smoke concentration, the second smoke concentration is larger than the first smoke concentration, the smoke alarm transmits an early warning signal to the cloud platform when the smoke concentration sensed by the smoke alarm is higher than the first smoke concentration, and the smoke alarm transmits an alarm signal to the cloud platform when the smoke concentration sensed by the smoke alarm is higher than the second smoke concentration;
comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the step of adjusting the error value for all parameters of the fire fighting equipment within the corresponding group comprises:
acquiring the early warning threshold value of each smoke alarm in each category, acquiring the early warning times of each smoke alarm in each category in preset time, and acquiring the average early warning times of the smoke alarms in the preset time in each category;
presetting an error value in the same group, and when the maximum average early warning times and the minimum average early warning times in the same group are larger than the error value, increasing the early warning threshold value of the smoke alarm corresponding to the maximum average early warning times and reducing the early warning threshold value of the smoke alarm corresponding to the minimum early warning times;
the fire-fighting equipment comprises a smoke alarm, wherein the smoke alarm is provided with an early warning threshold and an alarm threshold, the early warning threshold corresponds to a first smoke concentration, the alarm threshold corresponds to a second smoke concentration, the second smoke concentration is larger than the first smoke concentration, the smoke alarm transmits an early warning signal to the cloud platform when the smoke concentration sensed by the smoke alarm is higher than the first smoke concentration, and the smoke alarm transmits an alarm signal to the cloud platform when the smoke concentration sensed by the smoke alarm is higher than the second smoke concentration;
comparing and analyzing different standard values in the same group, and determining error values in the same group; wherein the step of adjusting the error value for all parameters of the fire fighting equipment within the corresponding group comprises:
acquiring the early warning threshold value of each smoke alarm in each category, acquiring the early warning times of each smoke alarm in each category in preset time, and selecting the smoke alarm as a target alarm when the warning times of each smoke alarm in the preset time are higher than the preset times;
obtaining average early warning times of the target smoke alarm in the preset time in each category;
presetting an error value in the same group, and when the maximum average early warning times and the minimum average early warning times in the same group are larger than the error value, increasing the early warning threshold value of the smoke alarm corresponding to the maximum average early warning times and reducing the early warning threshold value of the smoke alarm corresponding to the minimum early warning times.
2. Fire-fighting equipment quality detection device based on cloud platform big data analysis, characterized by comprising:
the signal receiving module is used for receiving the sensing signals and the alarm signals of the fire-fighting equipment;
the analysis processing module classifies fire-fighting equipment accessed to the cloud platform and groups all the categories; and is used for comparing and analyzing different standard values in the same group, and determining error values in the same group; the error value is used for adjusting parameters of all the fire-fighting equipment in the corresponding group;
the signal receiving module is also used for acquiring real fire data, wherein the real fire data comprises a real early warning threshold value, a real warning threshold value and manufacturer information of a smoke alarm in an area where a fire disaster occurs and a time interval between sending of early warning signals and sending of warning signals;
the analysis processing module is further used for taking the difference value between the early warning threshold value corresponding to each category and the real early warning threshold value as a first error value when the time interval is in a preset time period, and correspondingly adjusting the early warning threshold value in each category to approach the real early warning threshold value; taking the difference value between the alarm threshold value corresponding to each category and the real alarm threshold value as a second error value, and correspondingly adjusting the alarm threshold value in each category to approach the real alarm threshold value;
the signal receiving module is further used for obtaining the early warning threshold value of each smoke alarm in each category, obtaining the early warning times of each smoke alarm in each category in preset time, and obtaining the average early warning times of a single smoke alarm in the preset time;
the analysis processing module is also used for presetting an error value in the same group, and when the maximum average early warning times and the minimum average early warning times in the same group are larger than the error value, the early warning threshold value of the smoke alarm corresponding to the maximum average early warning times is increased, and the early warning threshold value of the smoke alarm corresponding to the minimum early warning times is reduced.
3. A storage medium having stored thereon computer instructions which, when executed by a processor, implement the cloud platform based fire fighting equipment quality detection method of claim 1.
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