CN111724562A - Smoke alarm and correction method thereof - Google Patents
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- CN111724562A CN111724562A CN202010506680.XA CN202010506680A CN111724562A CN 111724562 A CN111724562 A CN 111724562A CN 202010506680 A CN202010506680 A CN 202010506680A CN 111724562 A CN111724562 A CN 111724562A
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- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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- 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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Abstract
The invention discloses a smoke alarm and a correction method thereof. Wherein, the method comprises the following steps: after a self-learning mode is started, acquiring air flow rate and smoke concentration within a set time length of the self-learning mode; determining a smoke alarm threshold according to the air flow rate and the smoke concentration; and replacing the initial alarm threshold value of the smoke alarm with the smoke alarm threshold value so as to be used for smoke alarm in a normal working mode. According to the invention, the air is actively collected and analyzed, so that the influence of the airflow on the detection of the smoke concentration is reduced. The smoke alarm threshold value under different environments is automatically adjusted through the self-learning function, the detection sensitivity and reliability are improved, and the defect that the use environment of the smoke alarm is limited is overcome.
Description
Technical Field
The invention relates to the technical field of smoke alarms, in particular to a smoke alarm and a correction method thereof.
Background
The smoke alarm is an alarm device for realizing fire prevention by monitoring smoke concentration. The traditional smoke alarm can only detect smoke when the smoke drifts to the detection range of the detector, and for special places with large space span, high height and the like, airflow is easy to layer and transversely diffuse, the smoke is usually diluted by the airflow, and the smoke alarm can not play a role.
In addition, the threshold value has been set in advance for traditional smoke alarm, and to different service environments, the normal standard of smoke concentration and alarm threshold value should be different, and the condition of misinformation or delayed alarm can appear when adopting this type of smoke alarm, so its service environment receives great restriction.
Aiming at the problem that the smoke alarm in the prior art cannot be adjusted in a self-adaptive manner under different external conditions, an effective solution is not provided at present.
Disclosure of Invention
The embodiment of the invention provides a smoke alarm and a correction method thereof, which aim to solve the problem that the smoke alarm cannot be adjusted in a self-adaptive manner under different external conditions in the prior art.
In order to solve the technical problem, the invention provides a correction method of a smoke alarm, wherein the method comprises the following steps: after a self-learning mode is started, acquiring air flow rate and smoke concentration within a set time length of the self-learning mode; determining a smoke alarm threshold according to the air flow rate and the smoke concentration; and replacing the initial alarm threshold value of the smoke alarm with the smoke alarm threshold value so as to be used for smoke alarm in a normal working mode.
Further, before turning on the self-learning mode, the method further comprises: acquiring air flow rate and smoke concentration; determining an initial alarm threshold according to the air flow rate and the smoke concentration; or determining an initial alarm threshold according to the information of the workplace where the smoke alarm is located, which is input by the user.
Further, acquiring the air flow rate and the smoke concentration includes: collecting air through an air suction pump and a sampling pipeline, and monitoring the air flow rate through an air flow sensor; particulate matters in the air are filtered through the filter, the filtered air is input into the smoke detection cavity, and the smoke concentration in the air is analyzed through the smoke detection cavity.
Further, the sampling pipeline is arranged in a segmented mode and used for positioning an abnormal area when the smoke alarm gives an alarm.
Further, determining a smoke alarm threshold based on the air flow rate and the smoke concentration, comprising: determining a flow speed interval in which the air flow speed is positioned and a concentration interval in which the smoke concentration is positioned; determining a corresponding smoke alarm threshold according to the flow speed interval and the concentration interval by combining a preset relation; the preset relation is a mapping relation between a flow speed interval, a concentration interval and a smoke alarm threshold value.
Further, after determining a smoke alarm threshold based on the air flow rate and the smoke concentration, the method further comprises: calculating the difference between the smoke alarm threshold and the initial alarm threshold; if the difference value exceeds a preset value, a new round of self-learning mode is started again; if the difference value does not exceed the preset value, the process data of the self-learning mode are archived so as to form the corresponding relation between different workplaces and the initial alarm threshold value.
The invention also provides a smoke alarm, wherein the smoke alarm comprises: the air sampling module is used for collecting air of a workplace where the smoke alarm is located; the air flow sensor is connected with the main control chip and used for detecting the air flow rate; the smoke sensor is connected with the main control chip and used for detecting the smoke concentration in the air; the main control chip is used for determining a smoke alarm threshold according to the air flow rate and the smoke concentration; when the smoke concentration in the current air exceeds the smoke alarm threshold, sending a control signal to an alarm module; and the alarm module is used for alarming after receiving the control signal.
Further, the air sampling module includes: the suction pump and the sampling pipeline are connected and used for collecting air of a workplace where the smoke alarm is located; the sampling pipeline is arranged in a segmented mode and used for positioning an abnormal area when the smoke alarm gives an alarm; the filter is used for filtering particulate matters in the air, the filtered air is input into the smoke detection cavity, and the smoke detection cavity is used for analyzing the smoke concentration in the air.
Further, the smoke alarm further comprises: the communication module is connected with the main control chip and used for uploading the data of the smoke alarm to a cloud end for storage; wherein the data includes at least one of: air flow rate, smoke concentration, smoke alarm threshold.
The invention also provides a computer-readable storage medium, on which a computer program is stored, characterized in that the program realizes the above-mentioned method when executed by a processor.
By applying the technical scheme of the invention, the influence of the airflow on the detection of the smoke concentration is reduced by actively collecting and analyzing the air. The smoke alarm threshold value under different environments is automatically adjusted through the self-learning function, the detection sensitivity and reliability are improved, and the defect that the use environment of the smoke alarm is limited is overcome.
Drawings
Figure 1 is a flow chart of a method of modifying a smoke alarm according to an embodiment of the invention;
figure 2 is a schematic diagram of the construction of a smoke alarm according to an embodiment of the invention;
figure 3 is a flow chart of threshold setting for a smoke alarm according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, 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.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and "a plurality" typically includes at least two.
It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.
It is also noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that an 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 article or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in the article or device in which the element is included.
Alternative embodiments of the present invention are described in detail below with reference to the accompanying drawings.
Example 1
Fig. 1 is a flow chart of a method of modifying a smoke alarm according to an embodiment of the invention, as shown in fig. 1, the method comprising the steps of:
step S101, after a self-learning mode is started, acquiring air flow rate and smoke concentration within a set time length of the self-learning mode;
step S102, determining a smoke alarm threshold according to the air flow rate and the smoke concentration;
and step S103, replacing the initial alarm threshold value of the smoke alarm with the smoke alarm threshold value to alarm the smoke in the normal working mode.
The embodiment reduces the influence of the airflow on the detection of the smoke concentration by actively collecting and analyzing the air. The smoke alarm threshold value under different environments is automatically adjusted through the self-learning function, the detection sensitivity and reliability are improved, and the defect that the use environment of the smoke alarm is limited is overcome.
It should be noted that, for setting the initial alarm threshold, the following preferred embodiments can be implemented: before the self-learning mode is started, acquiring air flow rate and smoke concentration; determining an initial alarm threshold value according to the air flow rate and the smoke concentration; or determining an initial alarm threshold according to the information of the workplace where the smoke alarm is located, which is input by the user. That is, initial alarm thresholds in different workplaces (working environments) can be preset, so that the detection accuracy of the smoke alarm in different application environments is improved. In addition, for setting the duration of the self-learning mode, the working place where the smoke alarm is located can be referred to. Different workplaces may correspond to different durations.
In this embodiment, obtaining the air flow rate and the smoke concentration can be achieved by the following preferred embodiments: collecting air through an air suction pump and a sampling pipeline, and monitoring the air flow rate through an air flow sensor; particulate matters in the air are filtered through the filter, the filtered air is input into the smoke detection cavity, and the smoke concentration in the air is analyzed through the smoke detection cavity. The sampling pipeline can be arranged in a segmented mode and used for positioning an abnormal area when the smoke alarm gives an alarm. Based on this, actively gather the air in the current environment, detect air velocity and smog concentration. After the smoke alarm threshold is determined from the air flow rate and the smoke concentration, the effect of the air flow on the detection of the smoke concentration can be reduced.
It should be noted that, the determination of the smoke alarm threshold value according to the air flow rate and the smoke concentration may be implemented by a calculation method, or may also be implemented by the following preferred embodiments: determining a flow speed interval in which the air flow speed is positioned and a concentration interval in which the smoke concentration is positioned; determining a corresponding smoke alarm threshold value according to the flow speed interval and the concentration interval by combining a preset relation; the preset relation is a mapping relation between a flow speed interval, a concentration interval and a smoke alarm threshold value. Based on this, the smoke alarm threshold of the smoke alarm can be accurately determined in the self-learning mode.
After the smoke alarm threshold value is determined, calculating the difference value between the smoke alarm threshold value and the initial alarm threshold value; if the difference value exceeds the preset value, a new round of self-learning mode is started again; if the difference value does not exceed the preset value, the process data of the self-learning mode is archived so as to form the corresponding relation between different workplaces and the initial alarm threshold value. In this way, the initial alarm threshold value can be set according to the work site as a reference. And the process data of the self-learning mode is archived and can be used as a reference basis for setting the initial alarm threshold value of a similar workplace, and the calculation method of the initial alarm threshold value can be corrected and supplemented.
After the initial alarm threshold value is replaced by the smoke alarm threshold value, the smoke alarm can enter a normal working mode, namely, the smoke concentration in the air is monitored, and an alarm is given when the smoke concentration exceeds the smoke alarm threshold value.
Example 2
Figure 2 is a schematic diagram of the structure of a smoke alarm according to an embodiment of the invention, as shown in figure 2, comprising:
the air sampling module is used for collecting air of a workplace where the smoke alarm is located; specifically, the air sampling module includes: the suction pump and the sampling pipeline are connected and used for collecting air of a workplace where the smoke alarm is located; the sampling pipeline is arranged in a segmented mode and used for positioning an abnormal area when the smoke alarm gives an alarm; the filter is used for filtering particulate matters in the air, the filtered air is input into the smoke detection cavity, and the smoke detection cavity is used for analyzing the smoke concentration in the air.
And the airflow sensor is connected with the main control chip and used for detecting the air flow rate.
And the smoke sensor is connected with the main control chip and used for detecting the smoke concentration in the air.
The main control chip is used for determining a smoke alarm threshold according to the air flow rate and the smoke concentration; and when the smoke concentration in the current air exceeds a smoke alarm threshold value, sending a control signal to an alarm module.
And the alarm module is used for giving an alarm after receiving the control signal, for example, generating an acoustic alarm signal and an optical alarm signal when the smoke concentration exceeds a smoke alarm threshold value.
The communication module is connected with the main control chip and used for uploading the data of the smoke alarm to the cloud for storage; wherein the data includes at least one of: air flow rate, smoke concentration, smoke alarm threshold.
According to the embodiment, active sampling of air is achieved through the sampling pipeline and the air suction pump, the air flow rate and the smoke concentration are analyzed through the air flow sensor and the smoke sensor, and the smoke alarm automatically adjusts smoke alarm threshold values of different using environments according to the air flow rate and the smoke concentration through a self-learning function.
Example 3
Fig. 3 is a flow chart of threshold setting for a smoke alarm according to an embodiment of the invention, as shown in fig. 3, the flow chart comprising:
1) the air flow rate and the smoke concentration in the air are collected.
2) An initial alarm threshold is determined based on the air flow rate and the smoke concentration.
Specifically, an initial alarm threshold value is calculated according to the smoke concentration and the air flow rate and an empirical threshold value calculation method, and the threshold value is temporarily used as an alarm basis of the system before self-learning is completed.
3) Setting a self-learning mode and time length, and starting a self-learning function.
Specifically, the self-learning duration of the alarm can be set according to the installation place of the alarm, the self-learning duration is prolonged as much as possible according to conditions, and the alarm threshold value closer to the real working environment can be obtained. And selecting a corresponding self-learning mode so that the alarm can perform proper learning behaviors according to the working environment.
4) And detecting the smoke condition of the installation environment as a sample of the self-learning model.
Specifically, the self-learning function of the smoke alarm is started, at the moment, the smoke alarm automatically detects the smoke concentration and the airflow speed of the installation environment, and the smoke alarm is used as a sample to train the self-learning model. When self-learning is complete, the system will automatically generate a smoke alarm threshold that is consistent with the characteristics of the installation site.
5) A smoke alarm threshold is generated and compared to an initial alarm threshold.
6) Comparing whether the difference between the smoke alarm threshold and the initial alarm threshold is large, for example, whether the difference exceeds a preset value.
7) If the difference is larger, the communication module feeds back to the platform, and the self-learning mode is carried out again.
Specifically, the alarm threshold generated by the self-learning function is compared with the calculated initial threshold, and the alarm threshold of the system is corrected. If the difference between the two groups of values is large, the communication module feeds back the values to the platform so as to analyze the reason and re-perform the smoke self-learning process if necessary.
8) And if the difference value is smaller, correcting the initial alarm threshold value, and replacing the smoke alarm threshold value with the initial alarm threshold value.
9) Recording environmental parameters, debugging process and correcting initial alarm threshold.
Specifically, after the alarm threshold is corrected through the self-learning function, the working condition, debugging process and other contents of the installation site of the alarm are recorded and stored, and the recorded contents are used as a reference basis for setting similar workplace thresholds to correct and supplement the calculation method of the initial alarm threshold.
10) The flow ends.
It should be noted that, when the smoke concentration is collected, the sampling pipeline can be partitioned, when the smoke concentration is monitored to be abnormal, an abnormal area can be conveniently located, but due to the fact that time is needed for partition switching scanning, the alarm pipeline can be judged only after scanning is finished, and alarm time lag can be caused. In the embodiment, the calculation of the initial threshold value and the self-learning process can be carried out at the cloud end by reporting the monitored smoke concentration and air flow velocity in real time, but the communication between the alarm and the cloud platform has the possibility of delay and even disconnection, so that the stability is not high enough.
According to the flow, after the smoke alarm threshold is corrected, the smoke alarm can avoid the influence of air flow on the alarm accuracy, and can be adaptively adjusted according to a workplace, so that the alarm sensitivity is improved, and the use environment is not limited any more.
Example 4
The embodiment of the present invention provides software for implementing the technical solutions described in the above embodiments and preferred embodiments.
An embodiment of the present invention provides a non-volatile computer storage medium, where a computer-executable instruction is stored in the computer storage medium, and the computer-executable instruction may execute the method for correcting a smoke alarm in any of the above method embodiments.
The storage medium stores the software, and the storage medium includes but is not limited to: optical disks, floppy disks, hard disks, erasable memory, etc.
The product can execute the method provided by the embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method of modifying a smoke alarm, the method comprising:
after a self-learning mode is started, acquiring air flow rate and smoke concentration within a set time length of the self-learning mode;
determining a smoke alarm threshold according to the air flow rate and the smoke concentration;
and replacing the initial alarm threshold value of the smoke alarm with the smoke alarm threshold value so as to be used for smoke alarm in a normal working mode.
2. The method of claim 1, wherein prior to turning on a self-learning mode, the method further comprises:
acquiring air flow rate and smoke concentration; determining an initial alarm threshold according to the air flow rate and the smoke concentration; alternatively, the first and second electrodes may be,
and determining an initial alarm threshold value according to the information of the workplace where the smoke alarm is positioned, which is input by a user.
3. The method of claim 1, wherein obtaining an air flow rate and a smoke concentration comprises:
collecting air through an air suction pump and a sampling pipeline, and monitoring the air flow rate through an air flow sensor;
particulate matters in the air are filtered through the filter, the filtered air is input into the smoke detection cavity, and the smoke concentration in the air is analyzed through the smoke detection cavity.
4. The method of claim 3, wherein the sampling line is segmented to locate an abnormal area when the smoke alarm is alarming.
5. The method of claim 1, wherein determining a smoke alarm threshold based on the air flow rate and the smoke concentration comprises:
determining a flow speed interval in which the air flow speed is positioned and a concentration interval in which the smoke concentration is positioned;
determining a corresponding smoke alarm threshold according to the flow speed interval and the concentration interval by combining a preset relation; the preset relation is a mapping relation between a flow speed interval, a concentration interval and a smoke alarm threshold value.
6. The method of claim 1, wherein after determining a smoke alarm threshold based on the air flow rate and the smoke concentration, the method further comprises:
calculating the difference between the smoke alarm threshold and the initial alarm threshold;
if the difference value exceeds a preset value, a new round of self-learning mode is started again;
if the difference value does not exceed the preset value, the process data of the self-learning mode are archived so as to form the corresponding relation between different workplaces and the initial alarm threshold value.
7. A smoke alarm characterised in that it comprises:
the air sampling module is used for collecting air of a workplace where the smoke alarm is located;
the air flow sensor is connected with the main control chip and used for detecting the air flow rate;
the smoke sensor is connected with the main control chip and used for detecting the smoke concentration in the air;
the main control chip is used for determining a smoke alarm threshold according to the air flow rate and the smoke concentration; when the smoke concentration in the current air exceeds the smoke alarm threshold, sending a control signal to an alarm module;
and the alarm module is used for alarming after receiving the control signal.
8. The smoke alarm of claim 7, wherein the air sampling module comprises:
the suction pump and the sampling pipeline are connected and used for collecting air of a workplace where the smoke alarm is located; the sampling pipeline is arranged in a segmented mode and used for positioning an abnormal area when the smoke alarm gives an alarm;
the filter is used for filtering particulate matters in the air, the filtered air is input into the smoke detection cavity, and the smoke detection cavity is used for analyzing the smoke concentration in the air.
9. The smoke alarm of claim 7, further comprising:
the communication module is connected with the main control chip and used for uploading the data of the smoke alarm to a cloud end for storage; wherein the data includes at least one of: air flow rate, smoke concentration, smoke alarm threshold.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method according to any one of claims 1 to 6.
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| CN113112738A (en) * | 2021-03-12 | 2021-07-13 | 珠海格力电器股份有限公司 | Smoke sensor, smoke detector, smoke detection method and device |
| CN113252114A (en) * | 2021-06-11 | 2021-08-13 | 中国煤炭科工集团太原研究院有限公司 | Method and device for monitoring internal environment state of explosion-proof electrical equipment |
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| CN116106505A (en) * | 2023-04-13 | 2023-05-12 | 西南石油大学 | Concentration analysis system and analysis method for natural gas exploitation |
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