Smoke detection method, device and equipment based on double-labyrinth detection and storage medium

Abstract

The application provides a smoke detection method and device based on double-labyrinth detection, equipment and storage medium, and relates to the technical field of smoke detection. The method comprises the following steps: acquiring a first sampling value sequence of a first detection unit and a second sampling value sequence of a second detection unit in a double-labyrinth smoke detector; determining a first threshold drift of the first detection unit and a second threshold drift of the second detection unit based on the use time length of the first detection unit and the second detection unit; calculating a first change rate of the first detection unit and a second change rate of the second detection unit according to the first sampling value sequence and the second sampling value sequence; and obtaining a smoke detection result based on the first sampling value sequence, the second sampling value sequence, the first threshold drift, the second threshold drift, the first change rate and the second change rate. The application can resist interference and cope with the influence caused by device aging, thereby effectively improving the accuracy of the smoke detection result.

Description

Technical Field

[0001] This invention relates to the field of smoke detection technology, and in particular to a smoke detection method, apparatus, device, and storage medium based on dual-maze detection. Background Technology

[0002] Smoke detectors are key equipment in fire early warning systems, widely used in various buildings such as residences, office buildings, shopping malls, hospitals, factories, and warehouses. Their main function is to detect smoke particles produced by combustion in the early stages of a fire, promptly issuing audible and visual alarms to buy time for evacuation and fire rescue. Because fires are sudden and spread rapidly, the response speed and reliability of smoke detectors directly affect personal safety and property protection; therefore, their performance indicators and long-term stability are subject to strict regulations.

[0003] Currently, most mainstream photoelectric smoke detectors on the market employ a single-maze detection structure. This structure contains a light-emitting element and a receiving element. Under normal conditions, the receiving element cannot directly receive the light from the light-emitting element. When smoke particles enter the maze, the light is scattered, and some of the scattered light is captured by the receiving element and converted into an electrical signal, which is then collected and processed by a high-performance microcontroller (MCU). When the collected signal value exceeds a preset alarm threshold, the system determines that a fire has occurred and triggers an alarm. Depending on the product design, this structure can use either a single-emitting single-receiver or dual-emitting single-receiver optical arrangement, but its judgment logic relies on the signal change of a single channel.

[0004] However, in existing single-maze detection structures, foreign objects such as dust, fibers, or insects entering the maze will also scatter the optical fiber, causing it to be misjudged as smoke. In addition, the physical and optical properties of aerosol particles from non-fire sources such as water vapor and kitchen fumes are similar to those of smoke, which will also cause an increase in the scattered light signal, easily leading to misjudgment. The drift of the reference value caused by the aging of the components in the smoke alarm will also cause misjudgment. Summary of the Invention

[0005] This invention provides a smoke detection method, device, equipment, and storage medium based on dual-maze detection to solve the problem that existing smoke detectors are prone to false alarms due to dust, fibers, insects, water vapor, kitchen fumes, and component aging.

[0006] In a first aspect, embodiments of the present invention provide a smoke detection method based on dual-maze detection, comprising: Obtain the first sampled value sequence of the first detection unit and the second sampled value sequence of the second detection unit in the dual-maze smoke detector; Based on the usage time of the first detection unit and the usage time of the second detection unit, the first threshold drift amount of the first detection unit and the second threshold drift amount of the second detection unit are determined; Based on the first sampled value sequence, calculate the first rate of change of the first detection unit, and based on the second sampled value sequence, calculate the second rate of change of the second detection unit; Based on the first sampled value sequence, the second sampled value sequence, the first threshold drift, the second threshold drift, the first rate of change, and the second rate of change, the smoke detection result is obtained.

[0007] Secondly, embodiments of the present invention provide a smoke detection device based on dual-maze detection, comprising: The acquisition module is used to acquire the first sampled value sequence of the first detection unit and the second sampled value sequence of the second detection unit in the dual-maze smoke detector; The determination module is used to determine the first threshold drift amount of the first detection unit and the second threshold drift amount of the second detection unit based on the usage time of the first detection unit and the usage time of the second detection unit; The calculation module is used to calculate the first rate of change of the first detection unit based on the first sampled value sequence, and to calculate the second rate of change of the second detection unit based on the second sampled value sequence; The detection module is used to obtain smoke detection results based on the first sampled value sequence, the second sampled value sequence, the first threshold drift, the second threshold drift, the first rate of change, and the second rate of change.

[0008] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect or any possible implementation thereof.

[0009] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect or any possible implementation thereof.

[0010] In this embodiment of the invention, by simultaneously acquiring the independent first and second sampled value sequences of the dual maze detection units, the system can obtain complementary smoke concentration information from two physically separated optical channels, avoiding misjudgments caused by partial obstruction or scattering of foreign objects in a single channel. By calculating the threshold drift compensation for the usage time of the first and second detection units, dynamic correction can be performed for changes in the reference value caused by component aging, thereby avoiding false alarms or missed alarms caused by drift of fixed thresholds during long-term operation. By calculating the signal change rate of the two detection units respectively, the dynamic diffusion characteristics of smoke entering the maze can be effectively characterized. Combining these factors to determine the smoke detection result can not only eliminate interference from the environment itself, but also compare the changes of the two channels for mutual verification, reducing false alarms caused by accidental factors in a single channel. On the basis of resisting interference and dealing with the effects of component aging, it ensures a rapid response in the event of a fire and improves the accuracy of smoke detection results. Attached Figure Description

[0011] Figure 1a This is a top view of a smoke detector based on a dual-maze detection method provided in an embodiment of the present invention. Figure 1b This is a left view of a smoke detector based on a dual-maze detection smoke detection method provided in an embodiment of the present invention; Figure 2 This is a flowchart illustrating the implementation of the smoke detection method based on dual-maze detection provided in this embodiment of the invention. Figure 3 This is a flowchart illustrating the implementation of step S240 of the smoke detection method based on dual maze detection provided in this embodiment of the invention. Figure 4 This is a schematic diagram of the smoke detection device based on dual-maze detection provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0012] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0013] Figure 1a This is a top view of a smoke detector based on a dual-maze detection method provided in an embodiment of the present invention. Figure 1aAs shown, the dual-maze smoke detector includes a first detection unit 1 and a second detection unit 2. The first detection unit includes a first infrared emitter 11, a first blue light emitter 12, and a first receiver 13. The second detection unit includes a second infrared emitter 21, a second blue light emitter 22, and a second receiver 23. The first receiver 13 is used to simultaneously receive the light signals emitted by the first infrared emitter 11 and the first blue light emitter 12. The second receiver 23 is used to simultaneously receive the light signals emitted by the first infrared emitter 21 and the second blue light emitter 22. Furthermore... Figure 1a It also includes battery compartment a and battery compartment b. Battery compartment a is used to power the first detection unit 1, and battery compartment b is used to power the second detection unit 2. Figure 1b The image shows a left view of a smoke detector. In this view, 14 and 24 represent the mazes of the first and second detection units, respectively. The distance between these two mazes lies between a first distance and a second distance. The first distance is determined by optical anti-crosstalk conditions. To prevent the emitted light from one detection unit from being reflected or diffused by the maze walls and captured by the receiving tube of the other detection unit, the straight-line distance between them must be greater than the effective attenuation path of the light within the maze cavity. The first distance is typically taken as the distance between the centers of the two maze cavities not less than the sum of their radii plus a safety margin. Simultaneously, it must be ensured through actual measurement that when the emitting tube of one unit operates at its maximum rated power, the increase in the equivalent sampling value caused by stray light at the receiving tube of the other unit is lower than a preset crosstalk noise threshold, for example, lower than 5% of the clean air reference value. The specific value is related to the aspect ratio and surface roughness of the maze cavity and is generally set between 30mm and 50mm. The second distance is constrained by both the fire smoke diffusion rate and the system's allowable response time difference. The equivalent diffusion rate of smoke in the early stage of a fire driven by the thermal plume is set as v1. The maximum allowable response time difference for the system to ensure sufficient correlation between the two channels is set as ΔT. The value of ΔT can be between 2 and 5 seconds. If the time difference is too large, the signals collected by the two detection units will lose their synchronous change characteristics and will not be able to effectively perform mutual verification logic. In this case, the second distance is the product of v1 and ΔT. In practical applications, due to the limitation of the single housing size, if the second distance exceeds 100mm, it needs to be set to 100mm.

[0014] See Figure 2 The flowchart illustrating the implementation of the smoke detection method based on dual maze detection provided in this embodiment of the invention is described in detail below: Step S210: Obtain the first sampled value sequence of the first detection unit and the second sampled value sequence of the second detection unit in the dual maze smoke detector.

[0015] In some embodiments, a dual-maze smoke detector refers to a smoke detection device comprising two independent optical detection units, each with an independent light emitting component and a light receiving component. The first and second detection units are physically separated, each forming an independent optical maze structure, allowing aerosols such as smoke particles, dust, and water vapor in the external environment to enter the two maze areas and be detected independently. The first sampling value sequence refers to the numerical sequence obtained by analog-to-digital conversion of the electrical signals output by the light receiving component in the first detection unit at multiple consecutive sampling times. This sequence reflects the trend of light scattering intensity sensed by the first detection unit over time. The second sampling value sequence refers to the numerical sequence collected by the second detection unit within the same sampling time window, reflecting the change in light scattering intensity sensed by the second detection unit. The first sampling value sequence must include the sampling value of the first detection unit at the current moment, and the second sampling value sequence must include the sampling value of the second detection unit at the current moment.

[0016] It should be noted that during the sampling process, the microcontroller inside the dual-maze smoke detector reads the output signals of the first and second detection units according to a preset sampling frequency. Each sampled value is a digital quantity, and its magnitude is positively correlated with the concentration of smoke particles entering the corresponding maze area. The first and second sampled value sequences are stored in the detector's storage unit in chronological order. By acquiring the first and second sampled value sequences, subsequent signal processing and judgment can be based on dual-channel information, overcoming the defect of misjudgment caused by local interference in a single channel. In addition, the independent acquisition of the two sequences also allows for a horizontal comparison of the signal change trends of the two channels, thereby effectively distinguishing between global smoke events and local interference events.

[0017] Step S220: Based on the usage time of the first detection unit and the usage time of the second detection unit, determine the first threshold drift amount of the first detection unit and the second threshold drift amount of the second detection unit.

[0018] In some embodiments, usage time refers to the cumulative operating time of the first and second detection units since they were put into use, typically measured in hours or days. As usage time increases, the luminous efficiency of the light-emitting components within the detection units gradually decreases, and the sensitivity of the light-receiving components also changes slowly. These aging effects cause the reference output value of the detection units to drift in a clean air environment. Threshold drift refers to the amount of compensation required for the alarm threshold caused by the aging of the detection units, used to offset the impact of device aging on detection accuracy.

[0019] It should be noted that the determination of the first and second threshold drift amounts can be based on a pre-established aging model or drift prediction model. For example, before the detection unit leaves the factory, threshold drift data at different usage durations can be obtained through accelerated aging experiments, and a mapping relationship between usage duration and threshold drift amount can be fitted. During actual operation, the detector maintains a runtime counter internally. Each time smoke is detected, the corresponding threshold drift amount is queried or calculated based on the current accumulated usage duration. By introducing a threshold drift compensation mechanism, the alarm threshold can be dynamically adjusted as the detection unit ages, avoiding false alarms or missed alarms caused by the relative drift of a fixed threshold during long-term operation, effectively extending the effective service life of the detector.

[0020] In one possible implementation, the specific processing method for "determining the first threshold drift amount of the first detection unit based on the usage time of the first detection unit" in step S220 is as follows: based on the model of the first detection unit, determine the drift amount prediction model of the first detection unit; wherein, the drift amount prediction model is trained based on the aging dataset of the first detection unit; the aging dataset of the first detection unit is determined based on the model of the first detection unit; the usage time of the first detection unit is input into the drift amount prediction model to obtain the first threshold drift amount of the first detection unit.

[0021] In some embodiments, different models of detector units employ different optical components, electronic components, and structural designs, resulting in varying aging characteristics. Therefore, it is necessary to select the appropriate drift prediction model based on the specific model of the detector unit. The drift prediction model is a mathematical model used to describe the mapping relationship between usage time and threshold drift. This model can be an empirical formula fitted based on experimental data or a regression model trained using machine learning methods. The aging dataset refers to a collection of sample data obtained through accelerated aging experiments or long-term tracking tests on multiple detector units of the same model. Each sample contains usage time and corresponding threshold drift measurements.

[0022] It should be noted that when determining the drift prediction model, the first step is to match the corresponding model parameters or model files from a pre-built model library based on the model of the first detection unit. After substituting the current cumulative usage time as an input variable into the drift prediction model, the model will output the predicted value of the threshold drift for that usage time, i.e., the first threshold drift. Determining the threshold drift through model matching and model prediction fully considers the differences in aging characteristics between different detection units, making drift compensation more accurate. Simultaneously, the prediction model trained on the aging dataset reflects the actual aging patterns, thereby effectively improving the accuracy and adaptability of threshold drift compensation.

[0023] Step S230: Calculate the first rate of change of the first detection unit based on the first sampled value sequence, and calculate the second rate of change of the second detection unit based on the second sampled value sequence.

[0024] In some embodiments, the rate of change refers to the magnitude of change in the sampled value of the detection unit per unit time, reflecting the speed of change in smoke concentration. The first rate of change corresponds to the rate of change of the sampled value of the first detection unit over time, and the second rate of change corresponds to the rate of change of the sampled value of the second detection unit over time. In the early stages of a fire, after smoke particles enter the maze-like area, the sampled values ​​show a continuous upward trend, with a large and positive rate of change; while in normal environments without fire, the sampled values ​​remain relatively stable, with a rate of change close to zero; for slowly accumulating interference factors such as dust, although the sampled values ​​may rise slowly, their rate of change is much smaller than that caused by fire smoke. Therefore, the rate of change is an important discriminative feature for distinguishing real fires from other interference sources.

[0025] It should be noted that when calculating the rate of change, a fitting estimate can be made based on multiple sampling points prior to the current moment to smooth short-term fluctuations and reflect trend changes. For example, the sampled values ​​from the most recent N sampling moments can be taken, and the slope of the fitted line can be calculated using linear regression. This slope can then be determined as the rate of change at the current moment. Alternatively, a simpler method can be used: calculating the ratio of the difference between the sampled values ​​from the two most recent sampling moments to the sampling time interval. To suppress the influence of measurement noise on the rate of change calculation, a sliding window fitting method based on multiple sampling points is preferred. The window length can be configured according to the actual application scenario and sampling frequency. By calculating the rate of change, the dynamic characteristics of the sampled signal can be effectively characterized, providing a strong basis for distinguishing between real smoke events and non-fire interference sources.

[0026] In one possible implementation, the specific processing method of "calculating the first rate of change of the first detection unit according to the first sampled value sequence" in step S230 is as follows: on a preset coordinate system, draw the sampling curve of the first sampled value sequence; wherein, the horizontal axis of the preset coordinate system is the sampling time and the vertical axis is the sampled value; calculate the slope of the tangent line at multiple preset times on the sampling curve, and determine the average value of the slope of the tangent line at multiple preset times as the first rate of change of the first detection unit; wherein, the multiple preset times are the multiple times in the first sampled value sequence whose sampling time is closest to the current time.

[0027] In some embodiments, the preset coordinate system refers to a two-dimensional planar coordinate system with the sampling time as the horizontal axis and the sampled value as the vertical axis. The sampling curve is a curve formed by connecting the sampling points in the first sampled value sequence in the first sampled value sequence in chronological order in this coordinate system, which intuitively reflects the overall trend of the sampled value evolution over time. The tangent line refers to the instantaneous direction of change on the sampling curve at a certain moment, and its slope represents the instantaneous rate of signal change at that moment. Multiple preset moments refer to the current moment selected from the first sampled value sequence and multiple sampling moments whose sampling time is closest to the current moment. The sampled values ​​corresponding to these moments contain the latest signal change information and best reflect the current smoke concentration change trend. The first sample value sequence contains sample values ​​from multiple historical times before the current time and the sample value at the current time. For example, if the current time is 'a' and the sampling interval is 1, the first sample value sequence contains sample values ​​at times a-10, a-9, a-8, ..., a-1, and a. Suppose we need to calculate the slope of the tangent at 5 preset times. In this case, these 5 preset times are times a, a-1, a-2, a-3, and a-4.

[0028] It should be noted that when calculating the rate of change, the sampling curve of the first sampled value sequence is first plotted in a preset coordinate system. Then, a preset number of sampling points on the curve closest to the current time are selected, and the slope of the tangent line at each sampling point is calculated. The preset number can be set as needed; for example, more preset numbers can be set to observe changes over a longer period. The arithmetic mean of the obtained tangent line slopes is taken as the current rate of change of the detection unit. By averaging the tangent line slopes at multiple times, the influence of random fluctuations at individual sampling points on the rate of change calculation can be effectively suppressed, making the rate of change index smoother and more stable. At the same time, since multiple times closest to the current time are selected, the rate of change can reflect the signal change trend near the current time in a timely manner, ensuring the timeliness of the rate of change and enabling a rapid response in the early stages of a fire.

[0029] Step S240: Based on the first sampled value sequence, the second sampled value sequence, the first threshold drift, the second threshold drift, the first rate of change, and the second rate of change, the smoke detection result is obtained.

[0030] In some embodiments, the smoke detection result refers to the final judgment conclusion output by the dual-maze smoke detector, used to characterize whether fire smoke exists in the current environment. This detection result includes at least two states: fire alarm present and no fire alarm present. In the fire alarm state, it can be further distinguished into different confidence levels such as confirmed fire alarm and suspected fire alarm. Determining the smoke detection result requires integrating multiple information sources. The sampled value reflects the current smoke concentration level, the threshold drift reflects the impact of device aging on the judgment benchmark, and the rate of change reflects the dynamic characteristics of smoke concentration changes. By fusing the above multi-dimensional information, the accuracy and robustness of smoke detection can be effectively improved.

[0031] It should be noted that in obtaining smoke detection results, the alarm thresholds of the first and second detection units are first corrected in real time using the first and second threshold drift values, respectively, to obtain the real-time alarm threshold at the current moment. Then, the current real-time sampled value in the first sampled value sequence is compared with the first real-time alarm threshold, and the current real-time sampled value in the second sampled value sequence is compared with the second real-time alarm threshold to obtain the preliminary judgment results for each channel. Based on this, a comprehensive judgment is made by combining the relationship between the first and second rates of change. When the sampled values ​​of both channels exceed their respective real-time alarm thresholds, and the rates of change of both channels conform to the typical change characteristics of smoke entry, it is judged as a real fire alarm; when only one channel triggers an alarm while the other does not, or when the rate of change characteristics do not conform to the smoke diffusion pattern, it is judged as an interference event. Through the above multi-information fusion judgment strategy, the false alarm rate caused by non-fire interference sources such as dust, water vapor, and kitchen fumes is significantly reduced, while ensuring that the system can issue alarms promptly and accurately when a real fire occurs.

[0032] like Figure 3 As shown, the specific processing method of step S240 includes steps S2401-S2404, and the specific content is as follows: Step S2401: Based on the first and second rates of change, determine the third rate of change of the dual-maze smoke detector.

[0033] In some embodiments, the third rate of change is a comprehensive rate of change index obtained by fusing the first and second rates of change, used to characterize the overall smoke concentration change trend perceived by the dual-maze smoke detector. Since the two detection units are physically independent, their respective rates of change may deviate due to factors such as local airflow differences and uneven distribution of foreign objects. The role of the third rate of change is to integrate the change information from both channels to obtain a more stable and reliable overall trend representation.

[0034] It should be noted that the method for determining the third rate of change can be flexibly chosen based on the degree of difference between the first and second rates of change. When the two rates of change are relatively close, it indicates that the smoke concentration changes sensed by the two detection units are basically consistent. In this case, the average of the two rates can be used as the third rate of change to integrate the information from the two channels and smooth out random fluctuations. When the two rates of change differ significantly, it indicates that a certain detection unit may be experiencing local interference. In this case, taking the smaller value of the two rates as the third rate of change can effectively avoid false alarms caused by abnormally high values ​​in a single channel. The third rate of change determined in the above manner retains the change information from both detection units and can adaptively adjust the fusion strategy according to the actual situation, thereby improving the reliability and robustness of the rate of change index.

[0035] In one possible implementation, step S2401 is specifically processed as follows: if the difference between the first rate of change and the second rate of change is greater than a preset difference threshold, then the minimum value between the first rate of change and the second rate of change is determined as the third rate of change of the dual-maze smoke detector; if the difference between the first rate of change and the second rate of change is less than or equal to the preset difference threshold, then the average value between the first rate of change and the second rate of change is determined as the third rate of change of the dual-maze smoke detector.

[0036] In some embodiments, the difference threshold is a pre-defined numerical limit used to determine whether the difference between the first rate of change and the second rate of change is significant. When the absolute value of the difference between the first rate of change and the second rate of change is greater than the difference threshold, it is considered that there is a significant difference in the rates of change between the two channels, indicating that at least one detection unit is affected by local interference factors. In this case, the smaller value of the two rates of change is more representative of the overall smoke concentration change trend in the environment, because the larger rate of change may be an anomaly caused by local interference, while the smaller value reflects a relatively conservative and reliable trend.

[0037] It should be noted that when the difference between the first and second rates of change is no greater than the difference threshold, it indicates that the smoke concentration changes perceived by the two detection units are basically consistent, and the difference between them is within an acceptable range of normal fluctuations. In this case, both rates of change have high reliability. Taking their arithmetic mean as the third rate of change not only integrates the information from both channels to improve the signal-to-noise ratio but also smooths out random measurement noise in a single channel. Through the aforementioned fusion strategy based on the difference threshold, the third rate of change can adaptively select the most reasonable fusion method under different scenarios, effectively improving the representativeness and reliability of the rate of change index.

[0038] Step S2402: Based on the first threshold drift amount and the second threshold drift amount, determine the first real-time alarm threshold of the first detection unit and the second real-time alarm threshold of the second detection unit.

[0039] In some embodiments, both the first and second detection units are preset with a reference sampling value threshold for determining whether a fire has occurred at the factory. However, as usage time increases, the reference output value of the detection units will drift due to device aging, at which point the fixed reference sampling value threshold will no longer be applicable. Therefore, it is necessary to use the first threshold drift amount to determine the first real-time alarm threshold of the first detection unit, and use the second threshold drift amount to determine the second real-time alarm threshold of the second detection unit.

[0040] In one possible implementation, step S2402 is specifically processed as follows: the sum of the first threshold drift and the first alarm threshold of the first detection unit is determined as the first real-time alarm threshold of the first detection unit; the sum of the second threshold drift and the second alarm threshold of the second detection unit is determined as the second real-time alarm threshold of the second detection unit.

[0041] In some embodiments, the first alarm threshold refers to a reference sampling value threshold preset at the factory for the first detection unit. The first alarm threshold is typically determined by adding a certain margin to the standard output value of the detection unit under clean air conditions. However, as usage time increases, the reference output value of the detection unit may drift due to device aging, at which point the fixed first alarm threshold will no longer be applicable. The first real-time alarm threshold refers to a dynamic alarm threshold consistent with the current usage state, obtained by adding the first threshold drift amount to the first alarm threshold. This threshold adaptively adjusts as the device aging progresses.

[0042] It should be noted that the first threshold drift can be either positive or negative. When the reference output value increases due to aging of the detection unit, the first threshold drift is positive, and the first real-time alarm threshold is increased accordingly to avoid false alarms triggered by the increased reference value. When the reference output value decreases, the first threshold drift is negative, and the first real-time alarm threshold is decreased accordingly to ensure that the detector maintains sufficient sensitivity to real fires even after aging. By superimposing the threshold drift onto the fixed alarm threshold, dynamic adaptive adjustment of the alarm threshold is achieved, ensuring that the detector's judgment reference always matches the current device state, effectively overcoming the performance degradation problem caused by device aging during long-term operation of the fixed threshold strategy.

[0043] In some embodiments, the second alarm threshold refers to the baseline sampling value threshold preset at the factory for the second detection unit. The determination method for the second real-time alarm threshold is exactly the same as that for the first real-time alarm threshold; that is, a second threshold drift is added to the second alarm threshold to obtain a dynamic alarm threshold applicable to the current aging state of the second detection unit. By configuring independent real-time alarm thresholds for the two detection units, each detection unit can operate on a judgment benchmark that matches its current aging state, thereby ensuring that both channels maintain accurate and reliable detection performance during long-term use.

[0044] The first and second real-time alarm thresholds are calculated independently and do not affect each other. This ensures that even if the aging levels of the two detection units differ, each detection unit can obtain accurate drift compensation. This independent compensation mechanism can address the inconsistent aging issues caused by manufacturing process deviations or differences in usage conditions between the two detection units, allowing the two channels of the dual maze detector to maintain good performance consistency even after long-term operation.

[0045] Step S2403: Extract the first real-time sampled value from the first sampled value sequence, and extract the second real-time sampled value from the second sampled value sequence.

[0046] In some embodiments, the first real-time sampled value refers to the latest sampled value in the first sampled value sequence corresponding to the current time, representing the smoke concentration level sensed by the first detection unit at the current time. Similarly, the second real-time sampled value refers to the latest sampled value in the second sampled value sequence corresponding to the current time, representing the smoke concentration level sensed by the second detection unit at the current time. The real-time sampled values ​​are the basic data for comparison with the real-time alarm threshold, and the comparison result directly determines whether each detection unit triggers an alarm.

[0047] It is important to note that when extracting real-time sampled values, the timestamp of the sampled value must be consistent with or close to the current time to ensure timely comparison. In actual implementation, the microcontroller can update the real-time sampled value in each sampling interrupt service routine and store the latest sampled value in a dedicated register or memory variable for quick retrieval when smoke judgment is needed. By extracting the real-time sampled values ​​from the two detection units, the current smoke concentration status information of the two channels can be obtained, providing a data basis for subsequent alarm judgment.

[0048] Step S2404: Determine the smoke detection result based on the first real-time sampled value, the second real-time sampled value, the first real-time alarm threshold, the second real-time alarm threshold, and the third rate of change.

[0049] In some embodiments, after obtaining the first real-time sampled value, the second real-time sampled value, the first real-time alarm threshold, the second real-time alarm threshold, and the third rate of change, it is necessary to combine this information to make a comprehensive logical judgment in order to determine the final smoke detection result.

[0050] In one possible implementation, step S2404 is specifically processed as follows: when the first real-time sampled value is greater than or equal to the first real-time alarm threshold, the second real-time sampled value is compared with the second real-time alarm threshold, and the third rate of change is compared with the preset alarm rate of change; if the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the first detection result; if the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then the smoke detection result is determined as the second detection result; if the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the second detection result; if the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then... The smoke detection result is determined as the third detection result. When the first real-time sampled value is less than the first real-time alarm threshold, the second real-time sampled value is compared with the second real-time alarm threshold, and the third rate of change is compared with the preset alarm rate of change. If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the second detection result. If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then the smoke detection result is determined as the third detection result. If the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then the smoke detection result is determined as the third detection result. If the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the third detection result.

[0051] In some embodiments, after acquiring the first real-time sampled value, the second real-time sampled value, the first real-time alarm threshold, the second real-time alarm threshold, and the third rate of change, this information needs to be comprehensively processed according to a preset judgment logic to determine the final smoke detection result. During the judgment, the concentration level information and concentration change trend information from both channels need to be utilized simultaneously. A multi-condition combination approach is used to perform refined classification and judgment of different scenarios, thereby effectively improving the accuracy and anti-interference capability of smoke detection. The following details this process with specific judgment branches.

[0052] First, when the first real-time sampled value is greater than or equal to the first real-time alarm threshold, it indicates that the smoke concentration currently sensed by the first detection unit has reached the level that triggers an alarm. In this case, it is necessary to further examine the sampling status and overall trend of the second detection unit to distinguish between a real fire and a disturbance event.

[0053] If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, it indicates that both detection units have detected smoke concentration signals exceeding the limit. This significantly reduces the possibility of a single channel being falsely triggered due to local interference. At this point, the third rate of change is further compared with the preset alarm rate of change. When the third rate of change is greater than or equal to the preset alarm rate of change, it indicates that the smoke concentration has not only exceeded the limit but is also rising rapidly. This characteristic is highly consistent with the physical law of rapid smoke spread in the early stages of a fire. In this case, the smoke detection result is determined as the first detection result, i.e., a fire alarm is confirmed, and an alarm is triggered. When the third rate of change is less than the preset alarm rate of change, although the sampled values ​​of both channels have exceeded the limit, the rate of increase in smoke concentration is relatively slow, possibly caused by factors such as dust accumulation or slow environmental changes. In this case, the smoke detection result is determined as the second detection result, i.e., a suspected fire alarm. At this point, the third rate of change can be compared with the first preset value. If the third rate of change exceeds the first preset value, it indicates that a fire alarm has occurred; if the third rate of change does not exceed the first preset value, it indicates that no fire alarm has occurred. The first preset value is used to indicate the upper limit of the rate of change of the sampled value caused by the accumulation of dust when there is a lot of dust.

[0054] If the second real-time sampled value is less than the second real-time alarm threshold, it indicates that although the first detection unit has triggered an alarm, the second detection unit has not yet detected an over-limit signal, and the concentration judgment results of the two channels are inconsistent. In this case, the third rate of change becomes the key basis for distinguishing between a real fire and local interference. When the third rate of change is greater than or equal to the preset alarm rate of change, although the sampled value of the second detection unit has not yet exceeded the limit, the overall smoke concentration is rising rapidly. Considering the time difference in the spread of fire smoke, the second detection unit may be about to trigger an alarm. At this time, the smoke detection result is determined as the second detection result, i.e., a suspected fire alarm, and a high-level monitoring state is maintained. When the third rate of change is less than the preset alarm rate of change, the over-limit signal of the first detection unit lacks the support of a rapidly rising rate of concentration, and the second detection unit has not exceeded the limit synchronously. It is very likely that a single detection unit has been subjected to local interference. At this time, the smoke detection result is determined as the third detection result, i.e., no fire alarm, and no alarm is triggered.

[0055] Secondly, when the first real-time sampled value is less than the first real-time alarm threshold, it indicates that the smoke concentration currently sensed by the first detection unit has not yet reached the level to trigger an alarm. In this case, it is also necessary to make a comprehensive judgment by combining the sampling status of the second detection unit and the overall rate of change.

[0056] If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, it indicates that the second detection unit has detected an over-limit signal, while the first detection unit has not yet exceeded the limit. When the third rate of change is greater than or equal to the preset alarm rate of change, it indicates that although the first detection unit has not yet exceeded the limit, the overall smoke concentration is in the process of rapid increase. Considering the spatial distance between the two detection units and the time difference of smoke diffusion, the first detection unit may be about to trigger an alarm. At this time, the smoke detection result is determined as the second detection result, i.e., a suspected fire alarm. When the third rate of change is less than the preset alarm rate of change, the over-limit signal of the second detection unit lacks rapid rate of change support and may be a local anomaly caused by non-fire factors. At this time, the smoke detection result is determined as the third detection result, i.e., no fire alarm.

[0057] If the second real-time sampled value is less than the second real-time alarm threshold, it indicates that the real-time sampled values ​​of both detection units are within limits. At this point, the relationship between the third rate of change and the preset alarm rate of change is further determined. When the third rate of change is less than the preset alarm rate of change, it indicates that the smoke concentration level is normal and stable, and there are no signs of fire in the current environment. The smoke detection result is then determined as the third detection result, i.e., no fire alarm. When the third rate of change is greater than or equal to the preset alarm rate of change, although the sampled values ​​of both detection units are not yet within limits, the overall smoke concentration is rising at a relatively fast rate. This indicates that the third rate of change may exceed the preset alarm rate of change due to water vapor instantaneously entering the first and second detection units. In this case, the smoke detection result can be determined as the third detection result, i.e., no fire alarm, to avoid false alarms.

[0058] Through the aforementioned multi-condition combination and hierarchical judgment logic, the process of determining smoke detection results achieves a comprehensive fusion of the dual-channel sampling value exceeding the limit state and the concentration change trend. This judgment strategy can output detection results with different confidence levels based on different condition combinations, ensuring that the system can trigger alarms promptly and reliably when a real fire occurs, while effectively suppressing false alarms in complex scenarios such as local interference and slow changes. It achieves a good balance between system response speed and anti-interference capability, significantly improving the overall performance of the dual-maze smoke detector.

[0059] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0060] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0061] Figure 4A schematic diagram of a smoke detection device based on dual-maze detection provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below: like Figure 4 As shown, the smoke detection device 4 based on dual-maze detection includes: Acquisition module 41 is used to acquire the first sampled value sequence of the first detection unit and the second sampled value sequence of the second detection unit in the dual maze smoke detector; The determining module 42 is used to determine the first threshold drift amount of the first detection unit and the second threshold drift amount of the second detection unit based on the usage time of the first detection unit and the usage time of the second detection unit. The calculation module 43 is used to calculate the first rate of change of the first detection unit based on the first sampled value sequence, and to calculate the second rate of change of the second detection unit based on the second sampled value sequence; The detection module 44 is used to obtain smoke detection results based on the first sampled value sequence, the second sampled value sequence, the first threshold drift, the second threshold drift, the first rate of change, and the second rate of change.

[0062] In one possible implementation, the determining module 42 is specifically used to: determine the drift prediction model of the first detection unit based on the model of the first detection unit; wherein the drift prediction model is trained based on the aging dataset of the first detection unit; the aging dataset of the first detection unit is determined based on the model of the first detection unit; and input the usage time of the first detection unit into the drift prediction model to obtain the first threshold drift of the first detection unit.

[0063] In one possible implementation, the calculation module 43 is specifically used to: draw a sampling curve of the first sampled value sequence on a preset coordinate system; wherein the horizontal axis of the preset coordinate system is the sampling time and the vertical axis is the sampled value; calculate the slope of the tangent lines at multiple preset times on the sampling curve, and determine the average slope of the tangent lines at multiple preset times as the first rate of change of the first detection unit; wherein the multiple preset times are the multiple times in the first sampled value sequence whose sampling time is closest to the current time.

[0064] In one possible implementation, the detection module 44 is specifically used to: determine a third rate of change for the dual-maze smoke detector based on a first rate of change and a second rate of change; determine a first real-time alarm threshold for the first detection unit and a second real-time alarm threshold for the second detection unit based on a first threshold drift and a second threshold drift; extract a first real-time sampled value from a first sampled value sequence and extract a second real-time sampled value from a second sampled value sequence; and determine the smoke detection result based on the first real-time sampled value, the second real-time sampled value, the first real-time alarm threshold, the second real-time alarm threshold, and the third rate of change.

[0065] In one possible implementation, the detection module 44 is further configured to: determine the sum of the first threshold drift amount and the first alarm threshold of the first detection unit as the first real-time alarm threshold of the first detection unit; and determine the sum of the second threshold drift amount and the second alarm threshold of the second detection unit as the second real-time alarm threshold of the second detection unit.

[0066] In one possible implementation, the detection module 44 is further configured to: if the difference between the first rate of change and the second rate of change is greater than a preset difference threshold, then determine the minimum value between the first rate of change and the second rate of change as the third rate of change of the dual-maze smoke detector; if the difference between the first rate of change and the second rate of change is less than or equal to the preset difference threshold, then determine the average value between the first rate of change and the second rate of change as the third rate of change of the dual-maze smoke detector.

[0067] In one possible implementation, the detection module 44 is further configured to: when the first real-time sampled value is greater than or equal to the first real-time alarm threshold, compare the second real-time sampled value with the second real-time alarm threshold, and compare the third rate of change with a preset alarm rate of change; if the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then determine the smoke detection result as the first detection result; if the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then determine the smoke detection result as the second detection result; if the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then determine the smoke detection result as the second detection result; if the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then determine the smoke detection result as the second detection result; if the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then determine the smoke detection result as the second detection result. The smoke detection result is determined as the third detection result. When the first real-time sampled value is less than the first real-time alarm threshold, the second real-time sampled value is compared with the second real-time alarm threshold, and the third rate of change is compared with the preset alarm rate of change. If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the second detection result. If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then the smoke detection result is determined as the third detection result. If the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then the smoke detection result is determined as the third detection result. If the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the third detection result.

[0068] Figure 5 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. For example... Figure 5 As shown, the electronic device 5 of this embodiment includes a processor 50 and a memory 51. The memory 51 stores a computer program 52. When the processor 50 executes the computer program 52, it implements the steps in the various method embodiments described above. Alternatively, when the processor 50 executes the computer program 52, it implements the functions of each module / unit in the various device embodiments described above.

[0069] For example, computer program 52 may be divided into one or more modules / units, which are stored in memory 51 and executed by processor 50 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 52 in electronic device 5.

[0070] Electronic device 5 may include, but is not limited to, processor 50 and memory 51. Those skilled in the art will understand that... Figure 5 This is merely an example of electronic device 5 and does not constitute a limitation on electronic device 5. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 5 may also include input / output devices, network access devices, buses, etc.

[0071] The processor 50 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0072] The memory 51 can be an internal storage unit of the electronic device 5, such as a hard disk or RAM. The memory 51 can also be an external storage device of the electronic device 5, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 51 can include both internal and external storage units of the electronic device 5. The memory 51 is used to store the computer program 52 and other programs and data required by the electronic device 5. The memory 51 can also be used to temporarily store data that has been output or will be output.

[0073] For the sake of simplicity and clarity, only the above-described functional modules / units are used as examples. In practical applications, the functions described above can be assigned to different functional modules / units as needed. These modules / units can be implemented in hardware, software, or a combination of both.

[0074] This invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.

[0075] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0076] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A smoke detection method based on dual-maze detection, characterized in that, include: Obtain the first sampled value sequence of the first detection unit and the second sampled value sequence of the second detection unit in the dual-maze smoke detector; Based on the usage time of the first detection unit and the usage time of the second detection unit, the first threshold drift amount of the first detection unit and the second threshold drift amount of the second detection unit are determined; Based on the first sampled value sequence, calculate the first rate of change of the first detection unit, and based on the second sampled value sequence, calculate the second rate of change of the second detection unit; Based on the first sampled value sequence, the second sampled value sequence, the first threshold drift, the second threshold drift, the first rate of change, and the second rate of change, the smoke detection result is obtained; The process of obtaining smoke detection results based on the first sampled value sequence, the second sampled value sequence, the first threshold drift, the second threshold drift, the first rate of change, and the second rate of change includes: Based on the first rate of change and the second rate of change, a third rate of change is determined for the dual-maze smoke detector; Based on the first threshold drift and the second threshold drift, a first real-time alarm threshold for the first detection unit and a second real-time alarm threshold for the second detection unit are determined. Extract the first real-time sampled value from the first sampled value sequence, and extract the second real-time sampled value from the second sampled value sequence; Based on the first real-time sampled value, the second real-time sampled value, the first real-time alarm threshold, the second real-time alarm threshold, and the third rate of change, the smoke detection result is determined; The step of determining the first real-time alarm threshold of the first detection unit and the second real-time alarm threshold of the second detection unit based on the first threshold drift and the second threshold drift includes: The sum of the first threshold drift and the first alarm threshold of the first detection unit is determined as the first real-time alarm threshold of the first detection unit. The sum of the second threshold drift and the second alarm threshold of the second detection unit is determined as the second real-time alarm threshold of the second detection unit. Determining the third rate of change of the dual-maze smoke detector based on the first rate of change and the second rate of change includes: If the difference between the first rate of change and the second rate of change is greater than a preset difference threshold, then the minimum value between the first rate of change and the second rate of change is determined as the third rate of change of the dual-maze smoke detector. If the difference between the first rate of change and the second rate of change is less than or equal to a preset difference threshold, then the average of the first rate of change and the second rate of change is determined as the third rate of change of the dual-maze smoke detector.

2. The smoke detection method based on dual-maze detection according to claim 1, characterized in that, Based on the usage time of the first detection unit, the first threshold drift of the first detection unit is determined, including: Based on the model of the first detection unit, a drift prediction model for the first detection unit is determined; wherein, the drift prediction model is trained based on the aging dataset of the first detection unit; the aging dataset of the first detection unit is determined based on the model of the first detection unit. The usage time of the first detection unit is input into the drift prediction model to obtain the first threshold drift of the first detection unit.

3. The smoke detection method based on dual-maze detection according to claim 2, characterized in that, The step of calculating the first rate of change of the first detection unit based on the first sampled value sequence includes: On a preset coordinate system, plot the sampling curve of the first sampled value sequence; wherein, the horizontal axis of the preset coordinate system represents the sampling time, and the vertical axis represents the sampled value; Calculate the slope of the tangent lines at multiple preset times on the sampling curve, and determine the average slope of the tangent lines at multiple preset times as the first rate of change of the first detection unit; wherein, the multiple preset times are the multiple times in the first sampling value sequence whose sampling time is closest to the current time.

4. The smoke detection method based on dual-maze detection according to claim 3, characterized in that, The determination of the smoke detection result based on the first real-time sampled value, the second real-time sampled value, the first real-time alarm threshold, the second real-time alarm threshold, and the third rate of change includes: When the first real-time sampled value is greater than or equal to the first real-time alarm threshold, the second real-time sampled value is compared with the second real-time alarm threshold, and the third rate of change is compared with the preset alarm rate of change. If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the first detection result. If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then the smoke detection result is determined as the second detection result. If the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the second detection result. If the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then the smoke detection result is determined as the third detection result. When the first real-time sampled value is less than the first real-time alarm threshold, the second real-time sampled value is compared with the second real-time alarm threshold, and the third rate of change is compared with the preset alarm rate of change. If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the second detection result. If the second real-time sampled value is greater than or equal to the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then the smoke detection result is determined as the third detection result. If the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is less than the preset alarm rate of change, then the smoke detection result is determined as the third detection result. If the second real-time sampled value is less than the second real-time alarm threshold, and the third rate of change is greater than or equal to the preset alarm rate of change, then the smoke detection result is determined as the third detection result.

5. A smoke detection device based on dual-maze detection, characterized in that, include: The acquisition module is used to acquire the first sampled value sequence of the first detection unit and the second sampled value sequence of the second detection unit in the dual-maze smoke detector; The determining module is used to determine the first threshold drift amount of the first detection unit and the second threshold drift amount of the second detection unit based on the usage time of the first detection unit and the usage time of the second detection unit; The calculation module is configured to calculate a first rate of change of the first detection unit based on the first sampled value sequence, and to calculate a second rate of change of the second detection unit based on the second sampled value sequence; The detection module is used to obtain smoke detection results based on the first sampled value sequence, the second sampled value sequence, the first threshold drift, the second threshold drift, the first rate of change, and the second rate of change; The detection module is further configured to: determine a third rate of change of the dual-maze smoke detector based on the first rate of change and the second rate of change; determine a first real-time alarm threshold of the first detection unit and a second real-time alarm threshold of the second detection unit based on the first threshold drift and the second threshold drift; extract a first real-time sampled value from the first sampled value sequence and extract a second real-time sampled value from the second sampled value sequence; and determine a smoke detection result based on the first real-time sampled value, the second real-time sampled value, the first real-time alarm threshold, the second real-time alarm threshold, and the third rate of change. The detection module is further configured to determine the sum of the first threshold drift and the first alarm threshold of the first detection unit as the first real-time alarm threshold of the first detection unit. The sum of the second threshold drift and the second alarm threshold of the second detection unit is determined as the second real-time alarm threshold of the second detection unit. The detection module is further configured to: if the difference between the first rate of change and the second rate of change is greater than a preset difference threshold, determine the minimum value between the first rate of change and the second rate of change as the third rate of change of the dual-maze smoke detector; if the difference between the first rate of change and the second rate of change is less than or equal to a preset difference threshold, determine the average value between the first rate of change and the second rate of change as the third rate of change of the dual-maze smoke detector.

6. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 4.

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