Inductive function detection device and method

Abstract

The application discloses a kind of inductive function detection device and method thereof.The inductive function detection device includes communication module and anomaly detection module.Communication module receives the inductive signal of multiple inductive nodes.Anomaly detection module calculates the inductive frequency and total inductive times of each inductive node in the preset time interval.The anomaly detection module generates frequency threshold value according to normal inductive frequency, and compares inductive frequency with frequency threshold value to generate frequency comparison result.The anomaly detection module generates inductive times threshold value according to the average inductive times of one or more inductive nodes adjacent to the inductive node in the preset time interval, and compares total inductive times with inductive times threshold value to generate inductive times comparison result.The anomaly detection module generates detection result according to frequency comparison result and inductive times comparison result.

Description

TECHNICAL FIELD

[0001] The present application relates to a detection device, in particular, a sensing function detection device. The present application also relates to a sensing function detection method of the device. BACKGROUND

[0002] With the advancement of technology, people have increasingly high requirements for sensing lighting devices. Therefore, the performance of sensing lighting devices has been greatly improved, and they have been further improved to enhance environmental adaptability and reliability. In addition, sensing lighting devices also need to meet the needs of different applications, so they must be flexible and efficient to adapt to various complex external environments.

[0003] However, existing sensing lighting devices are prone to false positives due to various environmental factors (such as fans, insects, dust, etc.), which can affect their sensing accuracy. In addition, sensing lighting devices can also produce false positives due to self-excitation, which can reduce their sensing accuracy. The above situations can cause the sensing lighting device to malfunction. SUMMARY

[0004] According to an embodiment of the present application, a sensing function detection device is provided, which includes a communication module and an anomaly detection module. The communication module receives sensing signals of a plurality of sensing nodes. The anomaly detection module calculates a sensing frequency and a total sensing number of each sensing node in a preset time interval. The anomaly detection module generates a frequency threshold value according to a normal sensing frequency, and compares the sensing frequency with the frequency threshold value to generate a frequency comparison result. The anomaly detection module generates a sensing number threshold value according to an average sensing number of one or more sensing nodes adjacent to the sensing node in the preset time interval, and compares the total sensing number with the sensing number threshold value to generate a sensing number comparison result. The anomaly detection module generates a detection result according to the frequency comparison result and the sensing number comparison result.

[0005] In an embodiment, when the sensing frequency is greater than the frequency threshold value and the total sensing number is greater than the sensing number threshold value, the anomaly detection module generates a frequency comparison result indicating that the sensing frequency is abnormal and a sensing number comparison result indicating that the sensing number is abnormal, and generates a detection result indicating abnormal operation. The anomaly detection module reduces the sensitivity of the corresponding sensing node.

[0006] In an embodiment, when the sensing frequency is greater than the frequency threshold value and the total sensing number is less than the sensing number threshold value, the anomaly detection module generates a frequency comparison result indicating that the sensing frequency is abnormal and a sensing number comparison result indicating that the sensing number is normal, and generates a detection result indicating normal operation.

[0007] In one embodiment, when the sensing frequency is less than the frequency threshold value and the total sensing number is greater than the sensing number threshold value, the anomaly detection module generates a frequency comparison result indicating that the sensing frequency is normal and a sensing number comparison result indicating that the sensing number is abnormal, and generates a detection result indicating normal operation.

[0008] In one embodiment, when the sensing frequency is less than the frequency threshold value and the total sensing number is less than the sensing number threshold value, the anomaly detection module generates a frequency comparison result indicating that the sensing frequency is normal and a sensing number comparison result indicating that the sensing number is normal, and generates a detection result indicating normal operation. The anomaly detection module increases the sensitivity of the corresponding sensing node.

[0009] According to another embodiment of the present application, a sensing function detection method is provided, which comprises the following steps: receiving, by a communication module, sensing signals of a plurality of sensing nodes; calculating, by an anomaly detection module, a sensing frequency and a total sensing number of each sensing node in a preset time interval; generating, by the anomaly detection module, a frequency threshold value according to a normal sensing frequency, and comparing the sensing frequency with the frequency threshold value to generate a frequency comparison result; generating, by the anomaly detection module, a sensing number threshold value according to an average sensing number of one or more sensing nodes adjacent to the sensing node in the preset time interval, and comparing the total sensing number with the sensing number threshold value to generate a sensing number comparison result; and generating, by the anomaly detection module, a detection result according to the frequency comparison result and the sensing number comparison result.

[0010] In one embodiment, the step of generating, by the anomaly detection module, a detection result according to the frequency comparison result and the sensing number comparison result further comprises the following steps: generating, by the anomaly detection module, a frequency comparison result indicating that the sensing frequency is abnormal and a sensing number comparison result indicating that the sensing number is abnormal when the sensing frequency is greater than the frequency threshold value and the total sensing number is greater than the sensing number threshold value; generating, by the anomaly detection module, a detection result indicating abnormal operation; and decreasing, by the anomaly detection module, the sensitivity of the corresponding sensing node.

[0011] In one embodiment, the step of generating, by the anomaly detection module, a detection result according to the frequency comparison result and the sensing number comparison result further comprises the following steps: generating, by the anomaly detection module, a frequency comparison result indicating that the sensing frequency is abnormal and a sensing number comparison result indicating that the sensing number is normal when the sensing frequency is greater than the frequency threshold value and the total sensing number is less than the sensing number threshold value; and generating, by the anomaly detection module, a detection result indicating normal operation.

[0012] In one embodiment, the step of generating the detection result by the anomaly detection module according to the frequency comparison result and the sensing frequency comparison result further comprises the steps of: generating, by the anomaly detection module, a frequency comparison result indicating that the sensing frequency is normal and a sensing frequency comparison result indicating that the sensing frequency is abnormal when the sensing frequency is less than the frequency threshold value and the total sensing frequency is greater than the sensing frequency threshold value; and generating, by the anomaly detection module, a detection result indicating normal operation.

[0013] In one embodiment, the step of generating the detection result by the anomaly detection module according to the frequency comparison result and the sensing frequency comparison result further comprises the steps of: generating, by the anomaly detection module, a frequency comparison result indicating that the sensing frequency is normal and a sensing frequency comparison result indicating that the sensing frequency is normal when the sensing frequency is less than the frequency threshold value and the total sensing frequency is less than the sensing frequency threshold value; generating, by the anomaly detection module, a detection result indicating normal operation; and increasing, by the anomaly detection module, the sensitivity of the corresponding sensing node.

[0014] As described above, the sensing function detection device and the method thereof according to the embodiments of the present application can have one or more of the following advantages:

[0015] (1) In one embodiment of the present application, the sensing function detection device comprises a communication module and an anomaly detection module. The communication module receives sensing signals of a plurality of sensing nodes. The anomaly detection module calculates a sensing frequency and a total sensing frequency of each sensing node in a preset time interval. The anomaly detection module generates a frequency threshold value according to a normal sensing frequency, and compares the sensing frequency with the frequency threshold value to generate a frequency comparison result. The anomaly detection module generates a sensing frequency threshold value according to an average sensing frequency of one or more sensing nodes adjacent to the sensing node in the preset time interval, and compares the total sensing frequency with the sensing frequency threshold value to generate a sensing frequency comparison result. The anomaly detection module generates a detection result according to the frequency comparison result and the sensing frequency comparison result. The two-stage detection mechanism integrates the frequency comparison and the sensing frequency comparison, so that the detection mechanism can more effectively detect whether each sensing node generates a false alarm to find out the sensing node that is prone to false alarm due to self-excitation or environmental factors. Therefore, the sensing function detection device can more accurately perform sensing function detection, so that the sensing system can operate normally and improve its reliability.

[0016] (2) In an embodiment of the present application, the abnormality detection module of the inductive function detection device can generate the frequency threshold value according to the normal inductive frequency. The abnormality detection module can multiply the normal inductive frequency by a first adjustment coefficient to generate the frequency threshold value. Thus, the abnormality detection module does not directly use the normal inductive frequency as the frequency threshold value, but appropriately adjusts the normal inductive frequency to generate the frequency threshold value. In this way, the detection fault tolerance of the abnormality detection module can be greatly improved to avoid false adjustment to a normally operating inductive node. Thus, the accuracy of inductive function detection of the inductive function detection device can be further improved to meet the requirements of actual applications.

[0017] (3) In an embodiment of the present application, the abnormality detection module of the inductive function detection device can generate the inductive frequency threshold value according to the average inductive frequency of one or more inductive nodes adjacent to the inductive node. The abnormality detection module can multiply the average inductive frequency by a second adjustment coefficient to generate the inductive frequency threshold value. Thus, the abnormality detection module does not directly use the average inductive frequency as the inductive frequency threshold value, but appropriately adjusts the average inductive frequency to generate the inductive frequency threshold value. In this way, the detection fault tolerance of the abnormality detection module can be greatly improved to avoid false adjustment to a normally operating inductive node. Thus, the accuracy of inductive function detection of the inductive function detection device can be further improved to meet the requirements of actual applications.

[0018] (4) In an embodiment of the present application, the abnormality detection module of the inductive function detection device can generate the normal inductive frequency according to statistical data, which can be generated by big data analysis. Through the above mechanism, the abnormality detection module can obtain the most suitable normal inductive frequency as the basis for calculating the frequency threshold value. Through the statistical data based on big data analysis, the abnormality detection module can improve the accuracy of the frequency comparison result. Thus, the accuracy of inductive function detection of the inductive function detection device can be further improved to meet the requirements of actual applications.

[0019] (5) In an embodiment of the present application, the abnormality detection module of the inductive function detection device can not only lower the inductive sensitivity of the corresponding inductive node according to the detection result, but also increase the inductive sensitivity of the corresponding inductive node according to the detection result. Thus, the abnormality detection module can not only prevent false alarms of any inductive module, but also prevent the problem of too low inductive sensitivity of any inductive module. The above inductive sensitivity adjustment mechanism can ensure that the inductive system can operate normally to meet the requirements of different applications.

[0020] (6) In an embodiment of the present application, the inductive function detection device is simple in design, so the desired effects can be achieved without significantly increasing the cost. Thus, the inductive function detection device can achieve very high practicality and can be more widely applied. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 a block diagram of a circuit structure of an inductive function detection device of a first embodiment of the present application;

[0022] Figure 2 a schematic diagram of an operation state of an inductive function detection device of a first embodiment of the present application;

[0023] Figure 3 a schematic diagram of an operation state of an inductive function detection device of a second embodiment of the present application;

[0024] Figure 4 a block diagram of a circuit structure of an inductive function detection device of a third embodiment of the present application;

[0025] Figure 5 a first flowchart of an inductive function detection method of a fourth embodiment of the present application.

[0026] BRIEF DESCRIPTION OF DRAWINGS

[0027] 1 - inductive function detection device; 11 - communication module; 12 - abnormality detection module; 13 - power supply module; 14 - display module; Ds - inductive signal; As - adjustment signal; Cs - control signal; S51 ~ S55 - step flow.

[0028] The detailed features and advantages of the present application will be described in detail in the embodiments below, which are sufficient for any person skilled in the art to understand the technical content of the present application and to implement it, and according to the content disclosed in the specification, claims and drawings, any person skilled in the art can easily understand the purposes and advantages related to the present application. DETAILED DESCRIPTION

[0029] Embodiments of an inductive function detection device and method thereof according to the present application will be described below with reference to the drawings. In the drawings, the components in the drawings can be exaggerated or reduced in size for the purpose of clarity and convenience of the drawing description. In the following description and / or claims, when referring to a component "connected" or "coupled" to another component, it can be directly connected or coupled to the other component or there can be intervening components; and when referring to a component "directly connected" or "directly coupled" to another component, there are no intervening components for describing the relationship between components or layers. For the purpose of convenience of understanding, the same components in the following embodiments are described with the same symbols.

[0030] Referring to Figure 1Fig. 1 is a block diagram of a circuit structure of a sensing function detection device according to a first embodiment of the present application. As shown in the figure, the sensing function detection device 1 can be used to perform sensing function detection for a plurality of detection nodes. The detection nodes mentioned above can be devices with moving object detection function, such as microwave sensors, passive infrared (PIR) sensors or sensing lighting devices (lighting devices with moving object detection function). The sensing function detection device 1 comprises a communication module 11, an abnormality detection module 12 and a power module 13.

[0031] The abnormality detection module 12 is connected with the communication module 11 and the power module 13. In an embodiment, the abnormality detection module 12 can be a microcontroller (MCU). In another embodiment, the abnormality detection module 12 can be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other similar components. In an embodiment, the communication module 11 can be a Bluetooth module. In another embodiment, the communication module 11 can be a WiFi module, a ZigBee module or other similar components. In an embodiment, the power module 13 can be a power supply. In another embodiment, the power module 13 can also be various existing batteries.

[0032] Of course, the present embodiment is only used for illustration and is not intended to limit the scope of the present application. Equivalent modifications or changes made to the sensing function detection device according to the present embodiment should still be included in the patent scope of the present application.

[0033] Please refer to Figure 2 Fig. 2 is a schematic diagram of the operating state of the sensing function detection device according to the first embodiment of the present application. As shown in the figure, the power module 13 can supply power to the abnormality detection module 12.

[0034] The signal receiving module 11 receives sensing signals Ds of a plurality of sensing nodes.

[0035] The abnormality detection module 12 calculates the sensing frequency and the total sensing times of each sensing node in a preset time interval (e.g. 5 hours, 12 hours, 24 hours, which can be adjusted according to actual needs). The abnormality detection module 12 generates a frequency threshold value according to the normal sensing frequency, and compares the sensing frequency with the frequency threshold value to generate a frequency comparison result. In this embodiment, the abnormality detection module 12 can generate the normal sensing frequency according to statistical data, and the statistical data can be generated by big data analysis. For example, the user can set a plurality of sensing nodes in a stable environment (e.g. an office building, a residence, etc.), and collect data for a long time (e.g. several months, one year or several years), and perform big data analysis to obtain the sensing frequency of these sensing nodes in the stable environment, so as to obtain the normal sensing frequency. Through the above mechanism, the abnormality detection module 12 can obtain the most suitable normal sensing frequency as the basis for calculating the frequency threshold value. The abnormality detection module 12 can multiply the normal sensing frequency by a first adjustment coefficient to generate the frequency threshold value. In this embodiment, the first adjustment coefficient can be greater than 1 but less than 2, for example, 1.5, 1.6, 1.8, which can be adjusted according to actual needs. In another embodiment, the first adjustment coefficient can also be greater than 2, which can be adjusted according to actual needs.

[0036] Then, the abnormality detection module 12 can generate a sensing times threshold value according to the average sensing times of one or more sensing nodes adjacent to the sensing node in the above-mentioned preset time interval, and compare the total sensing times with the sensing times threshold value to generate a sensing times comparison result. For example, the abnormality detection module 12 can find out one or more sensing nodes adjacent to the sensing node according to a lookup table (the lookup table can record the coordinates of all sensing nodes). The abnormality detection module 12 can obtain the sensing times of each sensing node adjacent to the sensing node in the above-mentioned preset time interval, and calculate the average value of the sensing times of all sensing nodes adjacent to the sensing node to obtain the above-mentioned average sensing times. Similarly, the abnormality detection module 12 can multiply the average sensing times by a second adjustment coefficient to generate the sensing times threshold value. In this embodiment, the second adjustment coefficient can be greater than 1 but less than 2, for example, 1.5, 1.6, 1.8, which can be adjusted according to actual needs. In another embodiment, the second adjustment coefficient can also be greater than 2, which can be adjusted according to actual needs.

[0037] Finally, the abnormality detection module 12 generates a detection result according to the frequency comparison result and the sensing times comparison result. In this embodiment, when the sensing frequency is greater than the frequency threshold value and the total sensing times is greater than the sensing times threshold value, the abnormality detection module 12 generates a frequency comparison result indicating that the sensing frequency is abnormal and a sensing times comparison result indicating that the sensing times is abnormal, and generates a detection result indicating abnormal operation. Then, the abnormality detection module 12 can transmit an adjustment signal As through the communication module 11 to lower the sensitivity of the corresponding sensing node.

[0038] When the sensing frequency is greater than the frequency threshold value and the total sensing frequency is less than the sensing frequency threshold value, the abnormality detection module 12 generates the frequency comparison result indicating a sensing frequency abnormality and the sensing frequency comparison result indicating a sensing frequency normality, and generates the detection result indicating a normal operation. At this time, the abnormality detection module 12 judges that each sensing node is in a normal operation state.

[0039] When the sensing frequency is less than the frequency threshold value and the total sensing frequency is greater than the sensing frequency threshold value, the abnormality detection module 12 generates the frequency comparison result indicating a sensing frequency normality and the sensing frequency comparison result indicating a sensing frequency abnormality, and generates the detection result indicating a normal operation. At this time, the abnormality detection module 12 judges that each sensing node is in a normal operation state.

[0040] When the sensing frequency is less than the frequency threshold value and the total sensing frequency is less than the sensing frequency threshold value, the abnormality detection module 12 generates the frequency comparison result indicating a sensing frequency normality and the sensing frequency comparison result indicating a sensing frequency normality, and generates the detection result indicating a normal operation. At this time, the abnormality detection module 12 can transmit an adjustment signal As to increase the sensitivity of the corresponding sensing node through the communication module 11. In this case, although the abnormality detection module 12 judges that each sensing node is in a normal operation state, a specific sensing node can have a problem of insufficient sensitivity, so the abnormality detection module 12 increases the sensitivity of the corresponding sensing node.

[0041] As described above, in the present embodiment, the two-stage detection mechanism integrates the frequency comparison and the sensing frequency comparison. In this way, the sensing function detection device 1 can more effectively detect whether each sensing node generates a false positive situation to find out the sensing node that is prone to false positives due to self-excitation or environmental factors. Therefore, the sensing function detection device 1 can more accurately perform sensing function detection to enable the sensing system to operate normally and improve its reliability.

[0042] In addition, in the present embodiment, the abnormality detection module 12 of the sensing function detection device 1 can generate the frequency threshold value according to the normal sensing frequency. The abnormality detection module 12 can multiply the normal sensing frequency by a first adjustment coefficient to generate the frequency threshold value. Therefore, the abnormality detection module 12 does not directly use the normal sensing frequency as the frequency threshold value, but appropriately adjusts the normal sensing frequency to generate the frequency threshold value. In this way, the detection fault tolerance of the abnormality detection module 12 can be greatly improved to avoid false adjustment to the sensing node in a normal operation state. Therefore, the accuracy of the sensing function detection of the sensing function detection device 1 can be further improved to meet the needs of practical applications.

[0043] In addition, in the present embodiment, the abnormality detection module 12 of the induction function detection device 1 can generate the induction frequency threshold value according to the average induction frequency of one or more induction nodes adjacent to the induction node. The abnormality detection module 12 can multiply the average induction frequency by a second adjustment coefficient to generate the induction frequency threshold value. Thus, the abnormality detection module 12 does not directly use the average induction frequency as the induction frequency threshold value, but appropriately adjusts the average induction frequency to generate the induction frequency threshold value. In this way, the detection fault tolerance of the abnormality detection module 12 can be greatly improved to avoid false adjustment to the normally operating induction node. Therefore, the accuracy of the induction function detection of the induction function detection device 1 can be further improved to meet the requirements of practical applications.

[0044] Of course, the present embodiment is only used for illustration and not limit the scope of the present application, and equivalent modifications or changes made according to the induction function detection device of the present embodiment should still be included in the patent scope of the present application.

[0045] Please refer to Figure 3 which is a schematic diagram of the operation state of the induction function detection device of the second embodiment of the present application. As shown in the figure, the induction function detection device 1 includes a communication module 11, an abnormality detection module 12 and a power supply module 13.

[0046] The operation mechanism of each component described above is similar to the previous embodiment, so it will not be described here. Unlike the previous embodiment, when the abnormality detection module 12 generates a detection result indicating abnormal operation, the abnormality detection module 12 can not only transmit an adjustment signal As through the communication module 11 to lower the sensitivity of the corresponding induction node, but also transmit a control signal Cs through the communication module 11 to change the operation mode of the corresponding induction node. For example, the abnormality detection module 12 can transmit a control signal Cs to adjust the brightness of the induction node to 10% of the maximum brightness (which can be adjusted according to actual needs). In this way, the user can quickly find out the faulty induction node to repair or replace the induction node.

[0047] Of course, the present embodiment is only used for illustration and not limit the scope of the present application, and equivalent modifications or changes made according to the induction function detection device of the present embodiment should still be included in the patent scope of the present application.

[0048] It is worth mentioning that the existing induction lighting device is prone to false positives due to various environmental factors (such as fans, insects, dust, etc.), which affects its induction accuracy. In addition, the induction lighting device may also produce false positives due to self-excitation, which reduces its induction accuracy. The above situation may cause the induction lighting device to malfunction. In contrast, according to the embodiment of the present application, the induction function detection device includes a communication module and an anomaly detection module. The communication module receives the induction signals of multiple induction nodes. The anomaly detection module calculates the induction frequency and the total induction times of each induction node in a preset time interval. The anomaly detection module generates a frequency threshold value according to the normal induction frequency, and compares the induction frequency with the frequency threshold value to generate a frequency comparison result. The anomaly detection module generates an induction times threshold value according to the average induction times of one or more induction nodes adjacent to the induction node in a preset time interval, and compares the total induction times with the induction times threshold value to generate an induction times comparison result. The anomaly detection module generates a detection result according to the frequency comparison result and the induction times comparison result. The two-stage detection mechanism integrates frequency comparison and induction times comparison, which can more effectively detect whether each induction node produces false positives to find out the induction nodes that are prone to false positives due to self-excitation or environmental factors. Therefore, the induction function detection device can more accurately perform induction function detection, so that the induction system can operate normally and improve its reliability.

[0049] According to the embodiment of the present application, the anomaly detection module of the induction function detection device can generate a frequency threshold value according to the normal induction frequency. The anomaly detection module can multiply the normal induction frequency by a first adjustment coefficient to generate the frequency threshold value. Therefore, the anomaly detection module does not directly use the normal induction frequency as the frequency threshold value, but appropriately adjusts the normal induction frequency to generate the frequency threshold value. In this way, the detection fault tolerance of the anomaly detection module can be greatly improved to avoid incorrectly adjusting the normally operating induction nodes. Therefore, the accuracy of the induction function detection of the induction function detection device can be further improved to meet the needs of practical applications.

[0050] In addition, according to the embodiment of the present application, the anomaly detection module of the induction function detection device can generate an induction times threshold value according to the average induction times of one or more induction nodes adjacent to the induction node. The anomaly detection module can multiply the average induction times by a second adjustment coefficient to generate the induction times threshold value. Therefore, the anomaly detection module does not directly use the average induction times as the induction times threshold value, but appropriately adjusts the average induction times to generate the induction times threshold value. In this way, the detection fault tolerance of the anomaly detection module can be greatly improved to avoid incorrectly adjusting the normally operating induction nodes. Therefore, the accuracy of the induction function detection of the induction function detection device can be further improved to meet the needs of practical applications.

[0051] In addition, according to the embodiment of the present application, the abnormality detection module of the induction function detection device can generate a normal induction frequency according to statistical data, and the statistical data can be generated by big data analysis. Through the above mechanism, the abnormality detection module can obtain the most suitable normal induction frequency as the basis for calculating the frequency threshold value. Through the statistical data based on big data analysis, the abnormality detection module can improve the accuracy of the frequency comparison result. Therefore, the accuracy of the induction function detection of the induction function detection device can be further improved to meet the needs of practical applications.

[0052] In addition, according to the embodiment of the present application, the abnormality detection module of the induction function detection device can not only lower the induction sensitivity of the corresponding induction node according to the detection result, but also increase the induction sensitivity of the corresponding induction node according to the detection result. Therefore, the abnormality detection module can not only prevent false positives of any induction module, but also prevent the problem of too low induction sensitivity of any induction module. The above induction sensitivity adjustment mechanism can ensure that the induction system can operate normally to meet the needs of different applications.

[0053] Furthermore, according to the embodiment of the present application, the induction function detection device is simple in design, so the desired effect can be achieved without significantly increasing the cost. Therefore, the induction function detection device can achieve extremely high practicality and can be more widely applied. As described above, the induction function detection device according to the embodiment of the present application can indeed achieve excellent technical effects.

[0054] Please refer to Figure 4 which is a block diagram of the circuit structure of the induction function detection device of the third embodiment of the present application. As shown in the figure, the induction function detection device 1 includes a communication module 11, an abnormality detection module 12, and a power supply module 13.

[0055] The operation mechanism of the above components is similar to the previous embodiments, so it will not be described here. Unlike the previous embodiments, the induction function detection device 1 of the present embodiment further includes a display module 14. The display module 14 is connected to the abnormality detection module 12. The display module 14 can be a liquid crystal display or various computer devices (such as smartphones, tablet computers, etc.). When the abnormality detection module 12 generates a detection result indicating abnormal operation, the abnormality detection module 12 can not only transmit an adjustment signal As through the communication module 11 to lower the sensitivity of the corresponding induction node, but also display the induction node through the display module 14. In this way, the user can quickly find out the faulty induction node for repair or replacement.

[0056] Of course, the present embodiment is only used for illustration and does not limit the scope of the present application, and equivalent modifications or changes made according to the induction function detection device of the present embodiment should still be included in the patent scope of the present application.

[0057] Referring to Figure 5 FIG. 4 is a first flowchart of a sensing function detection method according to a fourth embodiment of the present application. As shown in the figure, the sensing function detection method according to the present embodiment comprises the following steps:

[0058] Step S51: receiving, by the communication module, sensing signals of the plurality of sensing nodes.

[0059] Step S52: calculating, by the anomaly detection module, a sensing frequency and a total sensing number of each sensing node in a preset time interval.

[0060] Step S53: generating, by the anomaly detection module, a frequency threshold value according to the normal sensing frequency, and comparing the sensing frequency with the frequency threshold value to generate a frequency comparison result.

[0061] Step S54: generating, by the anomaly detection module, a sensing number threshold value according to the average sensing number of one or more sensing nodes adjacent to the sensing node in the preset time interval, and comparing the total sensing number with the sensing number threshold value to generate a sensing number comparison result.

[0062] Step S55: generating, by the anomaly detection module, a detection result according to the frequency comparison result and the sensing number comparison result.

[0063] Of course, the present embodiment is only used for illustration and not limit the scope of the present application, and equivalent modifications or changes made according to the sensing function detection method of the present embodiment should still be included in the patent scope of the present application.

[0064] Although the steps of the method described in the present application are shown and described in a specific order, the order of the operations of each method can be changed, and certain steps can be performed in reverse order, or simultaneously with other steps. In another embodiment, not all steps can be implemented intermittently and / or alternately.

[0065] In summary, according to the embodiment of the present application, the inductive function detection device includes a communication module and an abnormality detection module. The communication module receives inductive signals of a plurality of inductive nodes. The abnormality detection module calculates an inductive frequency and a total inductive number of each inductive node in a preset time interval. The abnormality detection module generates a frequency threshold value according to the normal inductive frequency, and compares the inductive frequency with the frequency threshold value to generate a frequency comparison result. The abnormality detection module generates an inductive number threshold value according to an average inductive number of one or more inductive nodes adjacent to the inductive node in the preset time interval, and compares the total inductive number with the inductive number threshold value to generate an inductive number comparison result. The abnormality detection module generates a detection result according to the frequency comparison result and the inductive number comparison result. The two-stage detection mechanism integrates the frequency comparison and the inductive number comparison, so that the detection mechanism can more effectively detect whether each inductive node generates a false alarm to find the inductive node that is prone to false alarm due to self-excitation or environmental factors. Therefore, the inductive function detection device can more accurately perform inductive function detection, so that the inductive system can operate normally and improve its reliability.

[0066] According to the embodiment of the present application, the abnormality detection module of the inductive function detection device can generate a frequency threshold value according to the normal inductive frequency. The abnormality detection module can multiply the normal inductive frequency by a first adjustment coefficient to generate the frequency threshold value. Therefore, the abnormality detection module does not directly use the normal inductive frequency as the frequency threshold value, but appropriately adjusts the normal inductive frequency to generate the frequency threshold value. In this way, the detection fault tolerance of the abnormality detection module can be greatly improved to avoid false adjustment to the inductive node operating normally. Therefore, the accuracy of inductive function detection of the inductive function detection device can be further improved to meet the requirements of actual applications.

[0067] In addition, according to the embodiment of the present application, the abnormality detection module of the inductive function detection device can generate an inductive number threshold value according to the average inductive number of one or more inductive nodes adjacent to the inductive node. The abnormality detection module can multiply the average inductive number by a second adjustment coefficient to generate the inductive number threshold value. Therefore, the abnormality detection module does not directly use the average inductive number as the inductive number threshold value, but appropriately adjusts the average inductive number to generate the inductive number threshold value. In this way, the detection fault tolerance of the abnormality detection module can be greatly improved to avoid false adjustment to the inductive node operating normally. Therefore, the accuracy of inductive function detection of the inductive function detection device can be further improved to meet the requirements of actual applications.

[0068] In addition, according to the embodiment of the present application, the abnormality detection module of the induction function detection device can generate a normal induction frequency according to statistical data, and the statistical data can be generated by big data analysis. Through the above mechanism, the abnormality detection module can obtain the most suitable normal induction frequency as the basis for calculating the frequency threshold value. Through the statistical data based on big data analysis, the abnormality detection module can improve the accuracy of the frequency comparison result. Therefore, the accuracy of the induction function detection of the induction function detection device can be further improved to meet the needs of practical applications.

[0069] In addition, according to the embodiment of the present application, the abnormality detection module of the induction function detection device can not only lower the induction sensitivity of the corresponding induction node according to the detection result, but also increase the induction sensitivity of the corresponding induction node according to the detection result. Therefore, the abnormality detection module can not only prevent false positives of any induction module, but also prevent the problem of too low induction sensitivity of any induction module. The above induction sensitivity adjustment mechanism can ensure that the induction system can operate normally to meet the needs of different applications.

[0070] Furthermore, according to the embodiment of the present application, the induction function detection device is simple in design, so the desired effect can be achieved without significantly increasing the cost. Therefore, the induction function detection device can achieve very high practicality and can be more widely applied.

[0071] It should be noted that although the above embodiments have been described in this paper, the patent protection scope of the present application is not limited thereby. Therefore, based on the innovative idea of the present application, changes and modifications to the embodiments described herein, or equivalent structures or equivalent process transformations made using the contents of the present application specification and drawings, directly or indirectly apply the above technical solutions to other related technical fields, are all included in the protection scope of the present application patent.

Claims

1. A sensing function detection device, characterized in that: include: A communication module, configured to receive sensing signals from a plurality of sensing nodes; as well as An anomaly detection module, used to calculate the sensing frequency and total sensing times of each sensing node in a preset time interval; The abnormality detection module is configured to multiply a normal sensing frequency by a first adjustment coefficient to generate a frequency threshold value, and compare the sensing frequency with the frequency threshold value to generate a frequency comparison result. The abnormality detection module is configured to multiply an average number of sensing times of one or more sensing nodes adjacent to the sensing node within the preset time interval by a second adjustment coefficient to generate a sensing times threshold value, and compare the total number of sensing times with the sensing times threshold value to generate a sensing times comparison result. The abnormality detection module is configured to generate a detection result based on the frequency comparison result and the sensing times comparison result, and to not adjust, lower, or increase the sensitivity of the corresponding sensing node based on the detection result.

2. The sensing function detection device according to claim 1, wherein: When the sensing frequency is greater than the frequency threshold and the total number of sensing times is greater than the sensing number threshold, the abnormality detection module generates the frequency comparison result indicating that the sensing frequency is abnormal and the sensing number comparison result indicating that the sensing number is abnormal, and generates the detection result indicating abnormal operation. The abnormality detection module reduces the sensitivity of the corresponding sensing node.

3. The sensing function detection device according to claim 1, characterized in that: When the sensing frequency is greater than the frequency threshold and the total sensing times is less than the sensing times threshold, the abnormality detection module generates the frequency comparison result indicating that the sensing frequency is abnormal and the sensing times comparison result indicating that the sensing times are normal, and generates the detection result indicating normal operation.

4. The sensing function detection device according to claim 1, wherein: When the sensing frequency is less than the frequency threshold and the total sensing times is greater than the sensing times threshold, the abnormality detection module generates the frequency comparison result indicating that the sensing frequency is normal and the sensing times comparison result indicating that the sensing times are abnormal, and generates the detection result indicating normal operation.

5. The sensing function detection device according to claim 1, wherein: When the sensing frequency is less than the frequency threshold and the total number of sensing times is less than the sensing number threshold, the abnormality detection module generates the frequency comparison result indicating that the sensing frequency is normal and the sensing number comparison result indicating that the sensing number is normal, and generates the detection result indicating normal operation. The abnormality detection module increases the sensitivity of the corresponding sensing node.

6. A method for detecting a sensing function, characterized in that: include: The communication module receives sensing signals from a plurality of sensing nodes; Calculating the sensing frequency and total sensing times of each sensing node in a preset time interval through an anomaly detection module; multiplying the normal sensing frequency by a first adjustment coefficient to generate a frequency threshold value by the abnormality detection module, and comparing the sensing frequency with the frequency threshold value to generate a frequency comparison result; multiplying, by the anomaly detection module, an average number of sensing times of one or more sensing nodes adjacent to the sensing node within the preset time interval by a second adjustment coefficient to generate a sensing times threshold value, and comparing the total number of sensing times with the sensing times threshold value to generate a sensing times comparison result; as well as The abnormality detection module generates a detection result according to the frequency comparison result and the sensing number comparison result, and does not adjust, lowers, or increases the sensitivity of the corresponding sensing node according to the detection result.

7. The sensing function detection method according to claim 6, wherein: The step of generating the detection result according to the frequency comparison result and the sensing number comparison result by the abnormality detection module further includes: generating, by the abnormality detection module, the frequency comparison result indicating abnormality in the sensing frequency and the sensing number comparison result indicating abnormality in the sensing number when the sensing frequency is greater than the frequency threshold and the total sensing number is greater than the sensing number threshold; generating the detection result indicating abnormal operation by the abnormality detection module; and The abnormality detection module lowers the sensitivity of the corresponding sensing node.

8. The sensing function detection method according to claim 6, wherein: The step of generating the detection result according to the frequency comparison result and the sensing number comparison result by the abnormality detection module further includes: generating, by the abnormality detection module, the frequency comparison result indicating abnormal sensing frequency and the sensing number comparison result indicating normal sensing number when the sensing frequency is greater than the frequency threshold and the total sensing number is less than the sensing number threshold; and The abnormality detection module generates the detection result indicating normal operation.

9. The sensing function detection method according to claim 6, wherein: The step of generating the detection result according to the frequency comparison result and the sensing number comparison result by the abnormality detection module further includes: The abnormality detection module generates the frequency comparison result indicating that the sensing frequency is normal and the sensing number comparison result indicating that the sensing number is abnormal when the sensing frequency is less than the frequency threshold and the total sensing number is greater than the sensing number threshold; and The abnormality detection module generates the detection result indicating normal operation.

10. The sensing function detection method according to claim 6, wherein: The step of generating the detection result according to the frequency comparison result and the sensing number comparison result by the abnormality detection module further includes: generating, by the abnormality detection module, the frequency comparison result indicating that the sensing frequency is normal and the sensing number comparison result indicating that the sensing number is normal when the sensing frequency is less than the frequency threshold and the total sensing number is less than the sensing number threshold; The abnormality detection module generates the detection result indicating normal operation; and The sensitivity of the corresponding sensing node is increased by the abnormality detection module.

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