CN112530127A - Dynamic judgment method for smoke alarm of intelligent smoke sensing equipment - Google Patents
Dynamic judgment method for smoke alarm of intelligent smoke sensing equipment Download PDFInfo
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- CN112530127A CN112530127A CN202011230690.1A CN202011230690A CN112530127A CN 112530127 A CN112530127 A CN 112530127A CN 202011230690 A CN202011230690 A CN 202011230690A CN 112530127 A CN112530127 A CN 112530127A
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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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Abstract
The invention discloses a dynamic judgment method for smoke alarm of intelligent smoke sensing equipment, which comprises the following steps of firstly, smoke detection; step two, early warning judgment; step three, detecting the concentration; step four, recording data; step five, closing at fixed time; in the first step, a proper smoke alarm is manually selected, the working condition of the smoke alarm is detected, the smoke alarm is installed at a proper position, and the equipment reports a heartbeat packet at regular time; acquiring a smoke signal through a smoke alarm, detecting smoke concentration and a threshold value, and storing data; the dynamic judgment method for the smoke alarm of the intelligent smoke sensing equipment is low in cost, detects the smoke threshold value in the air at regular time, generates an alarm judgment model to dynamically judge the smoke alarm of the smoke sensing equipment by analyzing a historical data set, and improves the real-time performance and the accuracy of the alarm by combining the comprehensive judgment of the variables such as regions, environments, climates, weather, temperatures, historical concentration curves and the like with different weights.
Description
Technical Field
The invention relates to the technical field of smoke alarm, in particular to a dynamic judgment method for smoke alarm of intelligent smoke sensing equipment.
Background
The intelligent smoke sensing equipment is complex in installation environment, accurate judgment of smoke alarm is always very challenging work, false alarm is easily caused frequently when the alarm threshold is set too low, fire occurs but alarm is not given in time when the threshold is set too high, and meanwhile, due to the fact that installation regions, temperature and humidity, climate, installation places and other factors are different, the traditional method for triggering alarm based on the fixed threshold of the equipment is difficult to meet actual requirements of different scenes; in view of these drawbacks, it is necessary to design a dynamic determination method for smoke alarm of an intelligent smoke sensing device.
Disclosure of Invention
The invention aims to provide a dynamic judgment method for smoke alarm of intelligent smoke sensing equipment, which aims to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a dynamic judgment method for smoke alarm of intelligent smoke sensing equipment comprises the steps of firstly, smoke detection; step two, early warning judgment; step three, detecting the concentration; step four, recording data; step five, closing at fixed time;
in the first step, the smoke detection comprises the following steps:
1) manually selecting a proper smoke alarm, detecting the working condition of the smoke alarm, installing the smoke alarm at a proper position, and reporting a heartbeat packet by equipment at regular time;
2) acquiring a smoke signal through a smoke alarm, detecting smoke concentration and a threshold value, and storing data;
in the second step, the early warning judgment comprises the following steps:
1) the smoke alarm transmits the smoke concentration and the threshold value obtained in the step one 2) to a computer, reports a pre-alarm packet when the smoke concentration reaches the pre-alarm threshold value, and periodically calibrates the actual results of various alarms by a background;
2) according to the comparison between the smoke concentration and the threshold value and the standard smoke threshold value, the alarm judgment model is obtained by analyzing and modeling the historical data through the data analysis platform, and modeling analysis can be performed by using various big data classification methods, including but not limited to: linear regression, decision trees, neural networks, support vector machines, and the like;
3) the influence degree of each variable on the judgment result is different, a smoke alarm judgment model is established through training optimization, and whether real alarm exists is finally judged;
wherein in the third step, the concentration detection comprises the following steps:
1) the smoke alarm determines whether to alarm or not according to the comparison of the smoke concentration and the threshold value with the standard smoke threshold value, if the smoke concentration exceeds the standard smoke threshold value, concentration detection is carried out, and if the smoke concentration is lower than the standard smoke threshold value, the step is returned to carry out re-measurement again;
2) if the smoke concentration reaches the alarm threshold value, executing an alarm reporting process, and executing an alarm processing process by the platform;
3) if the model is judged to be real alarm, executing an alarm processing flow;
4) if the model judges that the false alarm is given, executing a false alarm processing flow;
5) when the smoke concentration does not reach the alarm threshold value, ending the alarm processing;
in the fourth step, the data recording comprises the following steps:
1) the smoke alarm acquires the smoke threshold value in the air again at intervals, draws the threshold value into a line graph and records the drawing time;
2) manually checking a smoke threshold value line graph periodically, and discharging potential safety hazards according to the line graph;
and in the fifth step, if no one is at home, the smoke alarm detection time is set manually, and the smoke alarm is dormant at regular time.
According to the technical scheme, the time for acquiring the smoke signal at this time is recorded in the step one 2).
According to the technical scheme, the data in the step two 2) can also be transmitted to the mobile phone of the user.
According to the technical scheme, the smoke alarm alarms in the step three 2), and then transmits the fire to the user computer through the cloud server.
According to the technical scheme, the smoke alarm in the step four 1) detects every 10-25 min.
According to the technical scheme, the timing sleep time in the fifth step is not more than 1 h.
Compared with the prior art, the invention has the following beneficial effects: the dynamic judgment method for the smoke alarm of the intelligent smoke sensing equipment is low in cost, detects the smoke threshold value in the air at regular time, generates an alarm judgment model to dynamically judge the smoke alarm of the smoke sensing equipment by analyzing a historical data set, and improves the real-time performance and the accuracy of the alarm by combining the comprehensive judgment of the variables such as regions, environments, climates, weather, temperatures, historical concentration curves and the like with different weights.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a method of the present invention;
fig. 2 is a smoke determination flow chart of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution: a dynamic judgment method for smoke alarm of intelligent smoke sensing equipment comprises the steps of firstly, smoke detection; step two, early warning judgment; step three, detecting the concentration; step four, recording data; step five, closing at fixed time;
in the first step, the smoke detection comprises the following steps:
1) manually selecting a proper smoke alarm, detecting the working condition of the smoke alarm, installing the smoke alarm at a proper position, and reporting a heartbeat packet by equipment at regular time;
2) acquiring a smoke signal through a smoke alarm, detecting smoke concentration and a threshold value, storing data, and recording the time for acquiring the smoke signal;
in the second step, the early warning judgment comprises the following steps:
1) the smoke alarm transmits the smoke concentration and the threshold value obtained in the step one 2) to a computer, reports a pre-alarm packet when the smoke concentration reaches the pre-alarm threshold value, and periodically calibrates the actual results of various alarms by a background;
2) according to the comparison between the smoke concentration and the threshold value and the standard smoke threshold value, the alarm judgment model is obtained by analyzing and modeling the historical data through the data analysis platform, and modeling analysis can be performed by using various big data classification methods, including but not limited to: linear regression, decision trees, neural networks, support vector machines, etc., and data can also be transmitted to the user's handset;
3) the influence degree of each variable on the judgment result is different, a smoke alarm judgment model is established through training optimization, and whether real alarm exists is finally judged;
wherein in the third step, the concentration detection comprises the following steps:
1) the smoke alarm determines whether to alarm or not according to the comparison of the smoke concentration and the threshold value with the standard smoke threshold value, if the smoke concentration exceeds the standard smoke threshold value, concentration detection is carried out, and if the smoke concentration is lower than the standard smoke threshold value, the step is returned to carry out re-measurement again;
2) if the smoke concentration reaches the alarm threshold value, executing an alarm reporting process, executing an alarm processing process by the platform, and transmitting the fire to the user computer through the cloud server after the smoke alarm gives an alarm;
3) if the model is judged to be real alarm, executing an alarm processing flow;
4) if the model judges that the false alarm is given, executing a false alarm processing flow;
5) when the smoke concentration does not reach the alarm threshold value, ending the alarm processing;
in the fourth step, the data recording comprises the following steps:
1) the smoke alarm acquires the smoke threshold value in the air again at intervals, draws the threshold value into a line graph, records the drawing time, and detects the smoke alarm once every 10-25 min;
2) manually checking a smoke threshold value line graph periodically, and discharging potential safety hazards according to the line graph;
and in the fifth step, if no one is at home, manually setting the detection time of the smoke alarm and sleeping at regular time, wherein the regular sleeping time is not more than 1 h.
Based on the above, the dynamic judgment method for the smoke alarm of the intelligent smoke sensing equipment has the advantages that the cost is low, the smoke threshold value in the air is detected at regular time, the alarm judgment model is generated by analyzing the historical data set to dynamically judge the smoke alarm of the smoke sensing equipment, and the real-time performance and the accuracy of the alarm are improved by combining the comprehensive judgment of the variables such as regions, environments, climates, weather, temperatures, historical concentration curves and the like with different weights.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A dynamic judgment method for smoke alarm of intelligent smoke sensing equipment comprises the steps of firstly, smoke detection; step two, early warning judgment; step three, detecting the concentration; step four, recording data; step five, closing at fixed time; the method is characterized in that:
in the first step, the smoke detection comprises the following steps:
1) manually selecting a proper smoke alarm, detecting the working condition of the smoke alarm, installing the smoke alarm at a proper position, and reporting a heartbeat packet by equipment at regular time;
2) acquiring a smoke signal through a smoke alarm, detecting smoke concentration and a threshold value, and storing data;
in the second step, the early warning judgment comprises the following steps:
1) the smoke alarm transmits the smoke concentration and the threshold value obtained in the step one 2) to a computer, reports a pre-alarm packet when the smoke concentration reaches the pre-alarm threshold value, and periodically calibrates the actual results of various alarms by a background;
2) according to the comparison between the smoke concentration and the threshold value and the standard smoke threshold value, the alarm judgment model is obtained by analyzing and modeling the historical data through the data analysis platform, and modeling analysis can be performed by using various big data classification methods, including but not limited to: linear regression, decision trees, neural networks, support vector machines, and the like;
3) the influence degree of each variable on the judgment result is different, a smoke alarm judgment model is established through training optimization, and whether real alarm exists is finally judged;
wherein in the third step, the concentration detection comprises the following steps:
1) the smoke alarm determines whether to alarm or not according to the comparison of the smoke concentration and the threshold value with the standard smoke threshold value, if the smoke concentration exceeds the standard smoke threshold value, concentration detection is carried out, and if the smoke concentration is lower than the standard smoke threshold value, the step is returned to carry out re-measurement again;
2) if the smoke concentration reaches the alarm threshold value, executing an alarm reporting process, and executing an alarm processing process by the platform;
3) if the model is judged to be real alarm, executing an alarm processing flow;
4) if the model judges that the false alarm is given, executing a false alarm processing flow;
5) when the smoke concentration does not reach the alarm threshold value, ending the alarm processing;
in the fourth step, the data recording comprises the following steps:
1) the smoke alarm acquires the smoke threshold value in the air again at intervals, draws the threshold value into a line graph and records the drawing time;
2) manually checking a smoke threshold value line graph periodically, and discharging potential safety hazards according to the line graph;
and in the fifth step, if no one is at home, the smoke alarm detection time is set manually, and the smoke alarm is dormant at regular time.
2. The dynamic decision method for smoke alarm of intelligent smoke sensing equipment according to claim 1, characterized by: and in the step one 2), recording the time for acquiring the smoke signal.
3. The dynamic decision method for smoke alarm of intelligent smoke sensing equipment according to claim 1, characterized by: and the data in the step 2) can also be transmitted to the mobile phone of the user.
4. The dynamic decision method for smoke alarm of intelligent smoke sensing equipment according to claim 1, characterized by: and transmitting the fire to a user computer through the cloud server after the smoke alarm gives an alarm in the step three 2).
5. The dynamic decision method for smoke alarm of intelligent smoke sensing equipment according to claim 1, characterized by: and in the step four 1), the smoke alarm is detected once every 10-25 min.
6. The dynamic decision method for smoke alarm of intelligent smoke sensing equipment according to claim 1, characterized by: and in the fifth step, the timed sleep time is not more than 1 h.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202011230690.1A CN112530127A (en) | 2020-11-06 | 2020-11-06 | Dynamic judgment method for smoke alarm of intelligent smoke sensing equipment |
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| CN202011230690.1A CN112530127A (en) | 2020-11-06 | 2020-11-06 | Dynamic judgment method for smoke alarm of intelligent smoke sensing equipment |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114733117A (en) * | 2022-04-11 | 2022-07-12 | 浙江友安建设工程管理有限责任公司 | Fire-fighting spraying system and using method |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114733117A (en) * | 2022-04-11 | 2022-07-12 | 浙江友安建设工程管理有限责任公司 | Fire-fighting spraying system and using method |
| CN114733117B (en) * | 2022-04-11 | 2023-01-31 | 浙江友安建设工程管理有限责任公司 | Fire-fighting spraying system and using method |
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