Intelligent control method and system based on non-contact laboratory special door

Abstract

The invention discloses an intelligent control method and system based on a non-contact laboratory special door, and relates to the technical field of intelligent control, and the method comprises the steps: calling data, building a sound characteristic parameter scp through the data of footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd, and carrying out the remote sensing of the data of signal intensity st and signal frequency sr sent by a controller, thereby achieving the intelligent control of the footstep sound intensity fs, the footstep sound frequency sf and the footstep sound duration sd. Establishing a remote sensing signal parameter rp, establishing a power supply characteristic parameter sp by using the voltage vo, current cu and electric quantity eq data of the laboratory special door, setting a door opening and closing threshold value of the laboratory special door, establishing a laboratory special door control parameter sp through the sound characteristic parameter scp and the remote sensing signal parameter rp, and monitoring the laboratory special door control parameter sp in real time. The corresponding opening and closing operation and early warning operation of the special laboratory door are selected according to the real-time data state, non-contact intelligent control over the special laboratory door can be achieved, and the requirements for safety, convenience and energy conservation are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control of laboratory special doors, and in particular to an intelligent control method and system based on contactless laboratory special doors. Background Art

[0002] With the rapid development of Internet of Things technology, the intelligent control method and system of contactless laboratory doors have become an indispensable part of modern laboratories. Effective intelligent control can not only improve the convenience of laboratory doors, but also enhance safety and ensure the cleanliness and safety of the laboratory environment. However, the existing methods and systems often face the problem of insufficient accuracy in practical applications, and cannot accurately distinguish between door opening and door closing signals, which poses a risk of misoperation. In addition, in an environment with more signal interference, the system stability is reduced, affecting the normal operation of the door body and increasing laboratory safety hazards.

[0003] In the Chinese invention application with application publication number CN117166873A, an intelligent control method and system for movable doors and windows are disclosed, which obtains indoor temperature values ​​and outdoor temperature values ​​at multiple predetermined time points within a predetermined time period collected by a temperature sensor; performs feature extraction on the indoor temperature values ​​and outdoor temperature values ​​at the multiple predetermined time points to obtain a contextual indoor-outdoor temperature comparison time series feature vector; and, based on the contextual indoor-outdoor temperature comparison time series feature vector, determines a control strategy for the window opening angle, so that the temperature difference in the natural environment can be effectively utilized to reduce the use of air conditioners or other temperature control equipment.

[0004] In the above invention, although the use of air conditioners or other temperature control equipment is reduced by utilizing the temperature difference between indoor and outdoor, thereby reducing energy consumption and showing significant energy-saving and environmental protection advantages, the window opening angle is automatically adjusted based on the data of the temperature sensor, which not only improves the convenience and intelligence level of the system, but also can effectively utilize natural ventilation and temperature regulation to significantly improve indoor comfort. However, the system also has certain defects. First, it only considers temperature parameters and ignores other key environmental factors such as humidity, wind speed, and air quality, which may lead to poor control effects in complex environments.

[0005] To this end, the present invention provides an intelligent control method and system based on a contactless laboratory special door. Summary of the invention

[0006] 1. Technical issues to be resolved

[0007] In view of the shortcomings of the prior art, the present invention provides an intelligent control method and system based on a contactless laboratory-specific door. The method collects footstep sound intensity fs, footstep sound frequency sf, footstep sound duration sd, remote sensing controller signal strength st, remote sensing controller signal frequency sr, laboratory-specific door voltage vo, laboratory-specific door current cu and laboratory-specific door electric quantity eq data through a sound sensor, a receiver and a power monitoring chip, and transmits the above data to an Internet of Things platform; retrieves data, uses footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd to establish a sound characteristic parameter scp, uses the signal strength st and signal frequency sr emitted by the remote sensing controller to establish a remote sensing signal parameter rp, uses the laboratory-specific door voltage vo, current cu and electric quantity eq to establish a power characteristic parameter pc, uses the sound characteristic parameter scp and the remote sensing signal parameter rp to establish a laboratory-specific door control parameter sp, and sets the laboratory-specific door opening and closing threshold range according to the power characteristic parameter; by real-time monitoring of the laboratory-specific door control parameters, and selecting the corresponding laboratory-specific door opening and closing operations and early warning operations according to the real-time data status, contactless intelligent laboratory-specific door control can be achieved, and the requirements of safety, convenience and energy saving can be effectively improved.

[0008] (II) Technical solution

[0009] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent control method based on a contactless laboratory dedicated door, comprising the following steps:

[0010] S1, a sound sensor is installed outside the laboratory door, and the sound sensor collects the data of footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd. The laboratory door is equipped with an electronic mechanical lock body, and the door body is equipped with a remote sensing controller outside. The receiver collects the signal strength st and signal frequency sr sent by the remote sensing controller, and the power monitoring chip collects the laboratory door voltage vo, current cu and power eq data;

[0011] S2, transmitting the above data collected by the sound sensor, receiver and power monitoring chip to the IoT platform through the IoT gateway;

[0012] S3, retrieve data, use footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd to establish sound characteristic parameter scp, use signal strength st and signal frequency sr sent by remote sensing controller to establish remote sensing signal parameter rp, use laboratory-specific gate voltage vo, current cu and electric quantity eq to establish power characteristic parameter pc, use sound characteristic parameter scp and remote sensing signal parameter rp to establish laboratory-specific door control parameter sp, and set the door opening and closing threshold range of laboratory-specific door according to power characteristic parameter;

[0013] S4, by real-time monitoring of the laboratory-specific door control parameter sp, the corresponding switch laboratory-specific door operation and early warning operation are selected according to the real-time data status.

[0014] Furthermore, the laboratory door data is retrieved and the footstep sound intensity fs is used to i , footstep sound frequency sf i and footstep sound duration sd i The sound feature parameter scp is established, and the entropy weight method is used to calculate the weight of each parameter. The entropy weight method is a weight determination method based on information entropy theory. The information entropy of each indicator is measured to evaluate its information volume, so as to determine the weight of each indicator. The entropy weight method reflects the richness of its information by calculating the information entropy value of each indicator. The lower the information entropy value, the higher the concentration of the indicator information and the greater its weight. Conversely, the weight is smaller. This method can effectively quantify the influence of multiple indicators for comprehensive evaluation and decision-making.

[0015] Furthermore, the footstep sound intensity fs i , footstep sound frequency sf i and footstep sound duration sd i The data is standardized to obtain fs i ''、sf i '' and sd i '', calculate the weight ratio of each standardized parameter, the formula is as follows:

[0016]

[0017] Among them, fs i ''、sf i '' and sd i '' are the standard deviations of footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd respectively. The proportion of the standardized footstep sound intensity, footstep sound frequency and footstep sound duration parameters is calculated. The formula is as follows:

[0018]

[0019] Where i is the sampling time number, i = 1, 2, 3, ..., n, n is the number of samples, pfs i 、psfi i and psd i They are the weights of the footstep sound intensity, footstep sound frequency and footstep sound duration parameters respectively.

[0020] Furthermore, the information entropy of each parameter is calculated by the weight of the footstep sound intensity, footstep sound frequency and footstep sound duration parameters. The formula is as follows:

[0021]

[0022] Among them, efs i ,esf i and esd i The information entropy representing the intensity, frequency and duration of footstep sounds is used to calculate the weights of the intensity, frequency and duration of footstep sounds. The formula is as follows:

[0023]

[0024]

[0025] Among them, 1-esf i 、1-esf i and 1-esd i The mutual information of the information entropy representing the intensity, frequency and duration of footstep sounds.

[0026] Furthermore, according to the weights a1, a2 and a3 of the acquired footstep sound intensity, footstep sound frequency and footstep sound duration, the sound feature parameter scp is established:

[0027]

[0028] The calculation formula of the corresponding sound characteristic parameter scp is as above.

[0029] Furthermore, by calling the signal strength st sent by the remote sensing controller i and signal frequency sr i Data, and establish remote sensing signal parameters rp, use entropy weight method to calculate the weight coefficient of each parameter, first of all, the signal strength st i and signal frequency sr i The data was standardized to obtain st i '' and sr i '', calculate the proportion of each parameter after standardization is Pst i and Psr i , and then calculate the information entropy of each parameter est i and esr i , calculate the weights b1 and b2 of signal strength and signal frequency according to information entropy, and use the weights to calculate the remote sensing signal parameter rp:

[0030]

[0031] The calculation formula of the corresponding remote sensing signal parameter rp is as above.

[0032] Furthermore, by adjusting the voltage vo of the laboratory dedicated gate i , current cu i and the amount of electricity eq i , and establish the power characteristic parameter pc, and use the entropy weight method to calculate the weight coefficient of each parameter. First, the voltage vo of the laboratory dedicated gate i , current cu i and the amount of electricity eq i The data was standardized to obtain i '',cu i '' and eq i '', calculate the weights c1, c2 and c3 of voltage, current and power according to the information entropy, and use the weights to calculate the power characteristic parameter pc:

[0033]

[0034] The calculation formula of the corresponding power characteristic parameter pc is as above. The mean and standard deviation are basic statistics that describe the distribution characteristics of the data set. The mean is the arithmetic average of all values ​​in the data set, reflecting the center position of the data. The standard deviation measures the degree of dispersion of the data relative to the mean, indicating the fluctuation or dispersion of the data. When calculating the threshold range of the power characteristic parameter pc, the mean and standard deviation are used to determine the normal fluctuation range of the data, thereby setting the upper and lower limits of the threshold to facilitate the identification of abnormal values ​​or faults. Therefore, the mean standard deviation is used to calculate the threshold range of the power characteristic parameter pc. The formula is as follows:

[0035]

[0036] in, is the mean of the power characteristic parameters, σpc is the standard deviation of the power characteristic parameters, and the range of the laboratory-specific door opening threshold r1 and the range of the laboratory-specific door closing threshold r2 are defined according to the standard deviation σpc. The formula is as follows:

[0037]

[0038] Among them, k is the error tolerance deviation, k1=1, k2=2, k2=3.

[0039] Furthermore, the sound characteristic parameter scp and the remote sensing signal parameter rp are used to establish the laboratory-specific door control parameter sp, and the entropy weight method is used to calculate the weight coefficient of each parameter. The calculation formula of the laboratory-specific door control parameter sp is as follows:

[0040] sp=α*scp+γ*rp

[0041] Among them, α and γ are the weight coefficients of the sound characteristic parameters and the remote sensing signal parameters.

[0042] Furthermore, by real-time monitoring of the laboratory-specific door control parameter sp, it is checked whether the laboratory-specific door control parameter sp is within the laboratory-specific door opening and closing threshold ranges, and different adjustment strategies are adopted, specifically:

[0043] when When the system sends out a door opening signal, the system will feedback that the current laboratory door is operating well and will not cause safety hazards;

[0044] when When the system sends a door closing signal, the system will feedback that the current laboratory door is operating well and will not cause safety hazards;

[0045] when When the system sends out a first-level alarm signal, it indicates a serious safety hazard or failure;

[0046] when When the system sends out a secondary alarm signal, it indicates a minor safety hazard or fault.

[0047] An intelligent control system based on a non-contact laboratory dedicated door, comprising:

[0048] The data acquisition module collects the data of footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd through the sound sensor, collects the signal strength st and signal frequency sr sent by the remote sensing controller through the receiver, and collects the laboratory-specific gate voltage vo, current cu and electric quantity eq data through the power monitoring chip;

[0049] The IoT transmission module transmits the above data collected by the sound sensor, receiver and power monitoring chip to the IoT platform through the IoT gateway;

[0050] The intelligent control module retrieves data, establishes sound characteristic parameters scp using footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd, establishes remote sensing signal parameters rp using signal intensity st and signal frequency sr sent by the remote sensing controller, establishes power characteristic parameters pc using laboratory-specific door voltage vo, current cu and electric quantity eq, establishes laboratory-specific door control parameters sp using sound characteristic parameters scp and remote sensing signal parameters rp, and sets the door opening and closing threshold range of the laboratory-specific door according to the power characteristic parameters;

[0051] The safety warning module monitors the control parameters sp of the laboratory special door in real time and selects the corresponding switch operation and warning operation of the laboratory special door according to the real-time data status.

[0052] (III) Beneficial effects

[0053] The present invention provides an intelligent control method and system based on a contactless laboratory special door, which has the following features:

[0054] Beneficial effects:

[0055] 1. Collect the data of footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd through the sound sensor, collect the signal strength st and signal frequency sr sent by the remote sensing controller through the receiver, and collect the laboratory-specific gate voltage vo, current cu and power eq data through the power monitoring chip to monitor the power status and ensure the stability of the power supply.

[0056] 2. The above data collected by the sound sensor, receiver and power monitoring chip are transmitted to the IoT platform through the IoT gateway to realize real-time transmission and centralized management of data and improve the overall collaborative efficiency of the system.

[0057] 3. Retrieve data, and use the footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd to establish the sound characteristic parameter scp, use the signal strength st and signal frequency sr sent by the remote sensing controller to establish the remote sensing signal parameter rp, use the laboratory-specific door voltage vo, current cu and electric quantity eq to establish the power characteristic parameter pc, use the sound characteristic parameter scp and remote sensing signal parameter rp to establish the laboratory-specific door control parameter sp, set the laboratory-specific door opening and closing threshold range according to the power characteristic parameters, realize comprehensive monitoring of power supply parameters, and improve the reliability of power management.

[0058] 4. Through real-time monitoring of laboratory door control parameters, corresponding switch laboratory door operation and early warning operation are selected according to real-time data status to ensure timely response of laboratory door in various states and improve the safety and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A schematic flow chart of an intelligent control method based on a contactless laboratory dedicated door according to an embodiment of the present invention;

[0060] Figure 2 The present invention is a schematic structural diagram of an intelligent control system based on a contactless laboratory-specific door according to an embodiment of the present invention. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] See also Figure 1The present invention provides an intelligent control method based on a contactless laboratory dedicated door, comprising the following steps:

[0063] S1, collects footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd data through the sound sensor, collects the signal strength st and signal frequency sr sent by the remote sensing controller through the receiver, and collects the laboratory-specific gate voltage vo, current cu and power eq data through the power monitoring chip.

[0064] The S1 includes the following contents:

[0065] 101. Install the sound sensor at the appropriate position outside the laboratory dedicated door to capture the footsteps. The sound sensor converts the footsteps detected in real time into an electrical signal, and then measures and records the footsteps sound intensity fs, footsteps sound frequency sf and footsteps sound duration sd.

[0066] 102. Install the receiver in the dedicated door area of ​​the laboratory to receive the signal sent by the remote sensing controller. The receiver converts the signal into an electrical signal and measures and records the signal strength ST and signal frequency SR of the remote sensing signal.

[0067] 103. Install a power monitoring chip in the power supply system of the laboratory special door to monitor and record the voltage vo, current cu and power eq of the door body in real time.

[0068] When using, combine the contents in 101 to 103:

[0069] The sound sensor collects the data of footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd, the receiver collects the signal strength st and signal frequency sr sent by the remote sensing controller, and the power monitoring chip collects the laboratory-specific door voltage vo, current cu and electricity eq data. It can comprehensively monitor the operating status of the laboratory-specific door to ensure that the door's switching operation is timely and accurate, and at the same time provide real-time power status monitoring to enhance the intelligence level and safety of the system.

[0070] S2, transmits the above data collected by the sound sensor, receiver and power monitoring chip to the IoT platform through the IoT gateway.

[0071] 201. Use wireless communication technology Zigbee to transmit data to the IoT gateway.

[0072] 202. After the data is transmitted to the IoT platform, the platform will receive the data through the connected API and then store the data in the backend database.

[0073] When used, combine the contents of 201 to 202:

[0074] The above data collected by the sound sensor, receiver and power monitoring chip are transmitted to the IoT platform through the IoT gateway, realizing real-time transmission and centralized management of data and improving the overall collaborative efficiency of the system.

[0075] S3, retrieve data, use footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd to establish sound characteristic parameters scp, use the signal strength st and signal frequency sr sent by the remote sensing controller to establish remote sensing signal parameters rp, use the laboratory-specific door voltage vo, current cu and electric quantity eq to establish power characteristic parameters pc, use the sound characteristic parameters scp and remote sensing signal parameters rp to establish laboratory-specific door control parameters sp, and set the laboratory-specific door opening and closing threshold range according to the power characteristic parameters.

[0076] The S3 includes the following contents:

[0077] 301. Retrieve the laboratory door data and use the footstep sound intensity fs i , footstep sound frequency sf i and footstep sound duration sd i The sound feature parameter scp is established, and the entropy weight method is used to calculate the weight of each parameter. The entropy weight method is a weight determination method based on information entropy theory. The information entropy of each indicator is measured to evaluate its information volume, so as to determine the weight of each indicator. The entropy weight method reflects the richness of its information by calculating the information entropy value of each indicator. The lower the information entropy value, the higher the concentration of the indicator information and the greater its weight. Conversely, the weight is smaller. This method can effectively quantify the influence of multiple indicators for comprehensive evaluation and decision-making.

[0078] First, the footstep sound intensity fs i , footstep sound frequency sf i and footstep sound duration sd i The data is standardized to obtain fs i ''、sf i '' and sd i '', calculate the weight ratio of each standardized parameter, the formula is as follows:

[0079]

[0080] Among them, fs i ''、sf i '' and sd i '' are the standard deviations of footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd respectively. The proportion of the standardized footstep sound intensity, footstep sound frequency and footstep sound duration parameters is calculated. The formula is as follows:

[0081]

[0082] Where i is the sampling time number, i = 1, 2, 3, ..., n, n is the number of samples, pfs i 、psf i and psd i They are the weights of the footstep sound intensity, footstep sound frequency and footstep sound duration parameters respectively.

[0083] 302. The information entropy of each parameter is calculated by the weight of the footstep sound intensity, footstep sound frequency and footstep sound duration parameters. The formula is as follows:

[0084]

[0085]

[0086] Among them, efs i ,esf i and esd i The information entropy representing the intensity, frequency and duration of footstep sounds is used to calculate the weights of the intensity, frequency and duration of footstep sounds. The formula is as follows:

[0087]

[0088] Among them, 1-efs i 、1-esf i and 1-esd i The mutual information of the information entropy representing the intensity, frequency and duration of footstep sounds.

[0089] 303. According to the weights a1, a2 and a3 of the acquired footstep sound intensity, footstep sound frequency and footstep sound duration, establish the sound feature parameter scp:

[0090]

[0091] The calculation formula of the corresponding sound characteristic parameter scp is as above.

[0092] 304. By calling the signal strength st sent by the remote sensing controller i and signal frequency st i Data, and establish remote sensing signal parameters rp, use entropy weight method to calculate the weight coefficient of each parameter, first of all, the signal strength st i and signal frequency st i The data was standardized to obtain st i '' and sr i '', calculate the proportion of each parameter after standardization is Psti and Psr i , and then calculate the information entropy of each parameter est i and esr i , calculate the weights b1 and b2 of signal strength and signal frequency according to information entropy, and use the weights to calculate the remote sensing signal parameter rp:

[0093]

[0094] The calculation formula of the corresponding remote sensing signal parameter rp is as above.

[0095] 305. By calling the voltage vo of the laboratory special door i , current cu i and the amount of electricity eq i , and establish the power characteristic parameter pc, and use the entropy weight method to calculate the weight coefficient of each parameter. First, the voltage vo of the laboratory dedicated gate i , current cu i and the amount of electricity eq i The data was standardized to obtain i '',cu i '' and eq i '', calculate the weights c1, c2 and c3 of voltage, current and power according to the information entropy, and use the weights to calculate the power characteristic parameter pc:

[0096]

[0097] The calculation formula of the corresponding power characteristic parameter pc is as above. The mean and standard deviation are basic statistics that describe the distribution characteristics of the data set. The mean is the arithmetic average of all values ​​in the data set, reflecting the center position of the data. The standard deviation measures the degree of dispersion of the data relative to the mean, indicating the fluctuation or dispersion of the data. When calculating the threshold range of the power characteristic parameter pc, the mean and standard deviation are used to determine the normal fluctuation range of the data, thereby setting the upper and lower limits of the threshold to facilitate the identification of abnormal values ​​or faults. Therefore, the mean standard deviation is used to calculate the threshold range of the power characteristic parameter pc. The formula is as follows:

[0098]

[0099] in, is the mean of the power characteristic parameters, σpc is the standard deviation of the power characteristic parameters, and the range of the laboratory-specific door opening threshold r1 and the range of the laboratory-specific door closing threshold r2 are defined according to the standard deviation σpc. The formula is as follows:

[0100]

[0101] Among them, k is the error tolerance deviation, k1=1, k2=2, k2=3.

[0102] 306. The laboratory-specific door control parameter sp is established using the sound characteristic parameter scp and the remote sensing signal parameter rp. The weight coefficient of each parameter is calculated using the entropy weight method. The calculation formula of the laboratory-specific door control parameter sp is as follows:

[0103] sp=α*scp+γ*rp

[0104] Among them, α and γ are the weight coefficients of the sound characteristic parameters and the remote sensing signal parameters.

[0105] When used, combine the content from 301 to 306:

[0106] The sound characteristic parameter scp is established using the footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd, the remote sensing signal parameter rp is established using the signal strength st and signal frequency sr emitted by the remote sensing controller, the power characteristic parameter pc is established using the laboratory-specific door voltage vo, current cu and electric quantity eq, the laboratory-specific door control parameter sp is established using the sound characteristic parameter scp and the remote sensing signal parameter rp, and the door opening and closing threshold range of the laboratory-specific door is set according to the power characteristic parameters, which improves the intelligence and safety of the laboratory-specific door, is able to accurately judge and respond to changes in external footsteps and remote sensing signals, and at the same time ensures the stable operation of the system under different power supply states, thereby achieving a higher level of security protection and user convenience.

[0107] S4, by real-time monitoring of the laboratory-specific door control parameter sp, the corresponding switch laboratory-specific door operation and early warning operation are selected according to the real-time data status.

[0108] The S4 includes the following contents:

[0109] 401. Obtain the laboratory-specific door control parameter sp according to the data of the footstep sound characteristic parameter scp and the remote sensing signal parameter rp, and perform real-time monitoring of the laboratory-specific door control parameter sp.

[0110] 402. When When the system sends a door opening signal, feedback that the current laboratory dedicated door is operating well and will not cause safety hazards; when When the system sends a door closing signal, feedback that the current laboratory dedicated door is operating well and will not cause safety hazards; when When the system sends out a first-level alarm signal, indicating a serious safety hazard or failure; when When the system sends out a secondary alarm signal, it indicates a minor safety hazard or fault.

[0111] When used, combine the content from 401 to 402:

[0112] By real-time monitoring of the laboratory-specific door control parameters sp, the corresponding switch laboratory-specific door operations and early warning operations are selected according to the real-time data status to improve safety, enhance intelligence, ensure system stability and enhance user convenience, thereby achieving a higher level of security protection and user experience.

[0113] See also Figure 2 The present invention provides an intelligent control system based on a contactless laboratory dedicated door, comprising:

[0114] The data acquisition module collects the footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd data through the sound sensor, collects the signal strength st and signal frequency sr emitted by the remote sensing controller through the receiver, and collects the laboratory-specific gate voltage vo, current cu and electric quantity eq data through the power monitoring chip.

[0115] The IoT transmission module transmits the above data collected by the sound sensor, receiver and power monitoring chip to the IoT platform through the IoT gateway.

[0116] The intelligent control module retrieves data and uses the footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd to establish the sound characteristic parameter scp, uses the signal strength st and signal frequency sr emitted by the remote sensing controller to establish the remote sensing signal parameter rp, uses the laboratory-specific door voltage vo, current cu and electric quantity eq to establish the power supply characteristic parameter pc, uses the sound characteristic parameter scp and the remote sensing signal parameter rp to establish the laboratory-specific door control parameter sp, and sets the door opening and closing threshold range of the laboratory-specific door according to the power supply characteristic parameter.

[0117] The safety warning module monitors the control parameters sp of the laboratory special door in real time and selects the corresponding switch operation and warning operation of the laboratory special door according to the real-time data status.

[0118] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0119] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0120] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An intelligent control method based on a contactless laboratory special door, characterized in that: The steps include: S1, collects footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd data through the sound sensor, collects the signal strength st and signal frequency sr sent by the remote sensing controller through the receiver, and collects the laboratory-specific gate voltage vo, current cu and power eq data through the power monitoring chip; S2, transmitting the above data collected by the sound sensor, receiver and power monitoring chip to the IoT platform through the IoT gateway; S3, retrieve data, use footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd to establish sound characteristic parameter scp, use signal strength st and signal frequency sr sent by remote sensing controller to establish remote sensing signal parameter rp, use laboratory-specific gate voltage vo, current cu and electric quantity eq to establish power characteristic parameter pc, use sound characteristic parameter scp and remote sensing signal parameter rp to establish laboratory-specific door control parameter sp, and set the door opening and closing threshold range of laboratory-specific door according to power characteristic parameter; S4, by real-time monitoring of the laboratory-specific door control parameter sp, the corresponding switch laboratory-specific door operation and early warning operation are selected according to the real-time data status.

2. According to claim 1, the intelligent control method based on the contactless laboratory special door is characterized in that: Retrieve the laboratory door data and use the footstep sound intensity fs i , footstep sound frequency sf i and footstep sound duration sd i , establish the sound characteristic parameter scp, the calculation formula of the sound characteristic parameter scp is as follows: Wherein, i is the sampling time number, i=1, 2, 3, ..., n, n is the number of samples, a1, a2 and a3 are the weight coefficients of footstep sound intensity, footstep sound frequency and footstep sound duration, which are obtained by entropy weight method.

3. According to claim 1, the intelligent control method based on the contactless laboratory special door is characterized in that: According to the signal strength st sent by the remote sensing controller i and signal frequency sr i Data, and establish the remote sensing signal parameter rp, the calculation formula of the remote sensing signal parameter rp is as follows: Among them, b1 and b2 are the weight coefficients of the signal strength and signal frequency emitted by the remote sensing controller, which are obtained by the entropy weight method.

4. According to claim 1, the intelligent control method based on the contactless laboratory special door is characterized in that: According to the voltage vo of the laboratory dedicated door i , current cu i and the amount of electricity eq i Data, and establish the power characteristic parameter pc, the calculation formula of the power characteristic parameter pc is as follows: Among them, c1, c2 and c3 are the weight coefficients of voltage, current and power of the laboratory special door, which are obtained by entropy weight method.

5. The intelligent control method based on the contactless laboratory special door according to claim 4 is characterized in that: Calculate the mean value of the power characteristic parameter pc, the formula is as follows: in, is the mean of the power characteristic parameters, and σpc is the standard deviation of the power characteristic parameters.

6. The intelligent control method based on the contactless laboratory special door according to claim 5 is characterized in that: Calculate the standard deviation of the power characteristic parameter pc, the formula is as follows: Among them, σpc is the standard deviation of the power characteristic parameters.

7. The intelligent control method based on the contactless laboratory special door according to claim 6 is characterized in that: The range of the laboratory door opening threshold r1 and the range of the laboratory door closing threshold r2 are defined according to the standard deviation σpc. The formula is as follows: Among them, k is the error tolerance deviation, k1=1, k2=2, k2=3.

8. The intelligent control method based on the contactless laboratory special door according to claim 7 is characterized in that: The sound characteristic parameter scp and the remote sensing signal parameter rp are used to establish the laboratory-specific door control parameter sp. The calculation formula of the laboratory-specific door control parameter sp is as follows: sp=α*scp+γ*rp Among them, α and γ are the weight coefficients of sound feature parameters and remote sensing signal parameters, which are obtained by entropy weight method.

9. The intelligent control method based on the contactless laboratory special door according to claim 8 is characterized in that: By real-time monitoring of the laboratory-specific door control parameter sp, check whether the laboratory-specific door control parameter sp is within the range of the door opening threshold and the door closing threshold, and adopt different adjustment strategies, specifically: when When the system sends out a door opening signal, the system will feedback that the current laboratory door is operating well and will not cause safety hazards; when When the system sends a door closing signal, the system will feedback that the current laboratory door is operating well and will not cause safety hazards; when When the system sends out a first-level alarm signal, it indicates a serious safety hazard or failure; when When the system sends out a secondary alarm signal, it indicates a minor safety hazard or fault.

10. An intelligent control system based on a contactless laboratory dedicated door, used to implement the method according to any one of claims 1 to 9, characterized in that: include: The data acquisition module collects the data of footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd through the sound sensor, collects the signal strength st and signal frequency sr sent by the remote sensing controller through the receiver, and collects the laboratory-specific gate voltage vo, current cu and electric quantity eq data through the power monitoring chip; The IoT transmission module transmits the above data collected by the sound sensor, receiver and power monitoring chip to the IoT platform through the IoT gateway; The intelligent control module retrieves data, establishes sound characteristic parameters scp using footstep sound intensity fs, footstep sound frequency sf and footstep sound duration sd, establishes remote sensing signal parameters rp using signal intensity st and signal frequency sr sent by the remote sensing controller, establishes power characteristic parameters pc using laboratory-specific door voltage vo, current cu and electric quantity eq, establishes laboratory-specific door control parameters sp using sound characteristic parameters scp and remote sensing signal parameters rp, and sets the door opening and closing threshold range of the laboratory-specific door according to the power characteristic parameters; The safety warning module monitors the control parameters sp of the laboratory special door in real time and selects the corresponding switch operation and warning operation of the laboratory special door according to the real-time data status.

Images