Swimming pool storage cabinet magnetic induction intelligent management method and system based on artificial intelligence

Abstract

The invention relates to the technical field of intelligent management methods, in particular to a magnetic induction intelligent management method and system for a swimming pool storage cabinet based on artificial intelligence, and the method comprises the steps: carrying out the ultrasonic detection and analysis of the closing process of a door of the swimming pool storage cabinet through an ultrasonic phased array technology, and determining the defects of the swimming pool storage cabinet; through combination of a magnetic induction sensor and an ultrasonic phased array technology, dynamic behaviors of cabinet doors in the cabinet door closing process are monitored, the quality of the swimming pool storage cabinets in the cabinet door closing process is quantified, qualified swimming pool storage cabinets are determined, correlation analysis is carried out on the popularity degree of the qualified swimming pool storage cabinets by users and the quality of the swimming pool storage cabinets, and the quality of the swimming pool storage cabinets is determined. The method has the beneficial effects that potential structural defects and functional problems are identified, so that the use safety of the storage cabinet and the satisfaction degree of the user are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management, and in particular to an artificial intelligence-based magnetic induction intelligent management method and system for swimming pool lockers. Background Art

[0002] In public facilities such as swimming pools, the quality and safety of lockers are of vital importance. Lockers need to maintain good closing performance during use to ensure the safety of users' belongings. Traditional detection methods mainly rely on manual inspection or simple mechanical testing. These methods are often difficult to fully and accurately evaluate the actual status of lockers. Among them, the closing process of locker doors involves complex dynamic behaviors. Static testing alone cannot accurately judge the performance in actual use, it is difficult to identify hidden defects inside the lockers, and it is not easy to judge the relationship between lockers and user experience. Summary of the invention

[0003] The purpose of the present invention is to provide a magnetic induction intelligent management method and system for swimming pool lockers based on artificial intelligence to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] S1: Use ultrasonic phased array technology to perform ultrasonic detection and analysis on the closing process of the swimming pool locker door to determine the defects of the swimming pool locker and generate structural information of the swimming pool locker;

[0006] S2: By combining magnetic induction sensors and ultrasonic phased array technology, the dynamic behavior of the cabinet door during the closing process is monitored to obtain the cabinet door information of the swimming pool locker;

[0007] S3: Comprehensively analyze the structural information and door information of the swimming pool lockers, quantify the quality of the swimming pool lockers during the door closing process, and screen out unqualified swimming pool lockers;

[0008] S4: Determine qualified pool lockers, conduct a correlation analysis between the popularity of qualified pool lockers among users and the quality of the pool lockers, and reduce the correlation between the quality of the pool lockers and the popularity of the users.

[0009] Preferably, the structural information of the swimming pool locker includes:

[0010] The structural information of the locker is represented by the structural incompleteness coefficient. The logic for obtaining the structural incompleteness coefficient is as follows: the closing process of the swimming pool locker is scanned by ultrasonic wave through ultrasonic phased array technology, the number of times the ultrasonic wave scans during the closing process of the swimming pool locker is obtained, and the number of times the ultrasonic wave scans during the closing process of the swimming pool locker is marked as: n, the number of defects and defect areas of the swimming pool locker each time the ultrasonic wave scans during the closing process of the swimming pool locker are obtained, and the number of defects and defect areas of the swimming pool locker each time the ultrasonic wave scans during the closing process of the swimming pool locker are marked as: SL i and MJ i , where i=1, 2, 3, ..., n, i is the number of each scan;

[0011] Get the total area of ​​the pool locker scan area and label the total area of ​​the pool locker scan area as: MJ all , the structural incompleteness coefficient is calculated by the formula: Among them, JG wz is the structural incompleteness coefficient,

[0012] Preferably, the door information of the swimming pool locker includes:

[0013] The door information of the locker is represented by the door response coefficient. The logic of obtaining the door response coefficient is as follows: the closing process of the pool locker is monitored by combining ultrasonic phased array technology and magnetic induction sensors. The ultrasonic phased array technology transmits and receives high-frequency ultrasonic waves and uses phased array probes to control the transmission and reception time of each element to measure the distance during the door closing process. The magnetic induction sensor indirectly infers the position of the door by detecting changes in the magnetic field.

[0014] Set the number of sampling points j, and use ultrasonic phased array technology and magnetic induction sensor to obtain the distance between the cabinet door and the monitoring point during the closing process at different sampling points, and mark the distance determined by ultrasonic phased array technology as: CS q , mark the distance determined by the magnetic induction sensor as: CG q , where q = 1, 2, 3, ..., j, q is the number of the sampling point;

[0015] According to the data points at the sampling points obtained by the ultrasonic phased array technology and the magnetic induction sensor, two different distance change curves are drawn by curve fitting. The distance change curve of the ultrasonic phased array technology is marked as: CS, and the distance change curve of the magnetic induction sensor is marked as: CG;

[0016] Obtain the derivatives of the two distance change curves at different data points, and mark the derivatives of the ultrasonic phased array technology at different data points as: dCS q, the derivative of the magnetic induction sensor at different data points is marked as: dCG q ;

[0017] By calculating the correlation coefficient between the derivatives of the two distance change curves at different data points, the cabinet door response coefficient is obtained. The calculation formula is:

[0018] Among them, XY gm is the cabinet door response coefficient,

[0019] Preferably, the quantifying the quality of the swimming pool locker during the door closing process includes:

[0020] Through comprehensive analysis of the structural information and door information of the swimming pool locker, the structural incompleteness coefficient and the door response coefficient are weighted and calculated to generate the quality assessment coefficient. The calculation formula of the quality assessment coefficient is: Among them, pg zl is the quality assessment coefficient, α1 and α2 are the proportional coefficients of the structural incomplete coefficient and the cabinet door response coefficient, and α1 and α2 are both greater than 0.

[0021] Preferably, the qualified swimming pool lockers include:

[0022] A first quality assessment coefficient threshold is set, and the quality assessment coefficient of the swimming pool locker in use is compared with the first quality assessment coefficient threshold. If the quality assessment coefficient of the swimming pool locker is greater than the first quality assessment coefficient threshold, the swimming pool locker is marked as a qualified locker and the swimming pool locker can continue to be used. If the quality assessment coefficient of the swimming pool locker is less than the first quality assessment coefficient threshold, the swimming pool locker is marked as an unqualified locker, indicating that the swimming pool locker may have safety problems and can no longer be provided to users, and the swimming pool locker needs to be inspected and repaired in a timely manner.

[0023] Preferably, the correlation analysis between the popularity of qualified swimming pool lockers among users and the quality of swimming pool lockers includes:

[0024] The optimal quality assessment coefficient range is identified through the analysis results of the Kendall correlation coefficient, and the relevance information of the pool lockers is determined. The relevance information of the pool lockers is represented by the welcome correlation coefficient. The logic for obtaining the welcome correlation coefficient is as follows: the quality assessment coefficients of different pool lockers and the usage frequency of the pool lockers are collected, the quality assessment coefficients are divided into multiple intervals, the usage frequencies of different pool lockers in the interval are sorted from large to small, and the quality assessment coefficients of different pool lockers in the interval are sorted from large to small.

[0025] Calculate the welcome correlation coefficient between the quality evaluation coefficient and the user's popularity in each interval. The calculation formula of the welcome correlation coefficient is: In the formula, τ b is the quality evaluation coefficient of the pool lockers in the interval and the welcome correlation coefficient of the frequency of use of the pool lockers, P is the number of consistent pairs, and Q is the number of disagreement pairs;

[0026] Setting a welcome correlation coefficient threshold, comparing the welcome correlation coefficients of different intervals with the welcome correlation coefficient threshold, obtaining intervals less than the welcome correlation coefficient threshold, identifying a critical point of transition from a high correlation interval to a low correlation interval, and using this point as a second quality assessment coefficient threshold;

[0027] The quality assessment coefficient of the swimming pool locker is compared with the second quality assessment coefficient threshold. If the quality assessment coefficient of the swimming pool locker is less than the second quality assessment coefficient threshold, the swimming pool locker is marked as a secondary locker. If the quality assessment coefficient of the swimming pool locker is greater than the second quality assessment coefficient threshold, the swimming pool locker is marked as a premium storage.

[0028] Preferably, the magnetic induction intelligent management system for swimming pool lockers based on artificial intelligence includes an ultrasonic module, a magnetic induction module, a quality assessment module and a screening module, and the modules are signal-connected;

[0029] Ultrasonic module, used to transmit and receive high-frequency ultrasonic waves, obtain internal structural information of the pool locker through beam scanning, conduct comprehensive ultrasonic testing on the closing process of the pool locker door, and identify internal defects;

[0030] The magnetic induction module is used to measure the change of magnetic field to infer the position and closing state of the cabinet door, and to fuse and analyze the magnetic induction data with the ultrasonic data to obtain the position change and dynamic behavior of the cabinet door during the closing process;

[0031] The quality assessment module is used to calculate the quality assessment coefficient of the locker during the closing process based on the comprehensive analysis of the structure information and door information of the swimming pool locker;

[0032] The screening module is used to distinguish qualified lockers from unqualified lockers, and to conduct a correlation analysis between the quality of qualified lockers and the popularity of users to identify superior lockers.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention uses ultrasonic phased array technology and magnetic induction sensors to monitor the performance of swimming pool lockers during the closing process, obtains structural information and door information of the swimming pool lockers, generates quality evaluation standards for swimming pool lockers, and classifies swimming pool lockers based on the popularity of swimming pool lockers among users, ensuring that the quality of swimming pool lockers will not affect the user experience, and helps to identify potential structural defects and functional problems, thereby improving the safety of use of lockers and user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the process of the present invention;

[0036] Figure 2 It is a schematic diagram of the structure of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose and technical solution of the present invention clearly and completely described, and the advantages more clearly understood, the embodiments of the present invention are further described in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are part of the embodiments of the present invention, rather than all of the embodiments, and are only used to explain the embodiments of the present invention, and are not used to limit 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.

[0038] Example 1 Please refer to Figure 1 The present invention provides a magnetic induction intelligent management method for swimming pool lockers based on artificial intelligence, which specifically includes the following steps:

[0039] S1: Use ultrasonic phased array technology to perform ultrasonic detection and analysis on the closing process of the swimming pool locker door to determine the defects of the swimming pool locker and generate structural information of the swimming pool locker;

[0040] S2: By combining magnetic induction sensors and ultrasonic phased array technology, the dynamic behavior of the cabinet door during the closing process is monitored to obtain the cabinet door information of the swimming pool locker;

[0041] S3: Comprehensively analyze the structural information and door information of the swimming pool lockers, quantify the quality of the swimming pool lockers during the door closing process, and screen out unqualified swimming pool lockers;

[0042] S4: Determine qualified pool lockers, conduct a correlation analysis between the popularity of qualified pool lockers among users and the quality of the pool lockers, and reduce the correlation between the quality of the pool lockers and the popularity of the users.

[0043] The swimming pool lockers are equipped with high-sensitivity magnetic induction sensors, which can sense the status of the doors in real time. Whether the doors are opened manually by the user or remotely controlled by the intelligent system, they can respond quickly and make corresponding adjustments. In the management system of the intelligent swimming pool lockers, rigorous testing is carried out and ultrasonic phased array technology is used for ultrasonic detection and analysis to determine possible defects in the swimming pool lockers.

[0044] Among them, the high-sensitivity magnetic induction sensor is used to detect the magnetic field changes of the cabinet door. The high-sensitivity magnetic induction sensor can monitor the opening and closing of the swimming pool locker cabinet door, and indirectly determine the distance between the cabinet door and the high-sensitivity magnetic induction sensor by recording the magnetic field strength.

[0045] Magnetic field changes: When a magnet (such as a magnet mounted on a cabinet door) moves or its position changes, the magnetic field strength detected by the magnetic induction sensor changes;

[0046] Sensor and magnet position: Install the magnetic sensor in a fixed position on the cabinet, make sure it can detect the magnet on the cabinet door, and install the magnet in an appropriate position on the cabinet door so that it is close to the sensor when the cabinet door is fully closed.

[0047] Using ultrasonic phased array technology for ultrasonic testing and analysis is an effective method to determine possible defects. By utilizing the characteristics of high-frequency sound waves (ultrasound) propagating in materials, defects or discontinuities inside the material can be detected. By controlling the emission and reception time of each independent element in the array probe, electronic scanning, focusing and deflection of the beam can be achieved, which can cover a wider area and provide high-resolution imaging, and ultimately generate a two-dimensional or three-dimensional image of the interior of the locker in real time for easy analysis and judgment.

[0048] When the ultrasonic probe scans the locker, it will capture various reflected signals inside. When the sound wave encounters discontinuity (such as cracks, gaps or corrosion), the reflected signal will change. The system will automatically identify these abnormal reflected signals and count each independent defect. After the detection process is completed, the total number of defects inside the locker can be directly obtained;

[0049] By analyzing the intensity and distribution of the reflected signal, the system can generate two-dimensional or three-dimensional images of the defects, in which the boundaries of the defects can be clearly shown, and the system calculates the area or volume of each defect based on these boundaries.

[0050] It should be noted that ultrasonic phased array technology is able to emit high-frequency sound waves to penetrate the locker material and generate detailed images of the internal structure, thereby identifying internal defects such as cracks and voids. Artificial intelligence algorithms can be used to analyze these images, automatically detect and classify defects, and provide more accurate evaluation results.

[0051] By analyzing the swimming pool lockers using magnetic induction sensors and ultrasonic phased array technology, the structural information and door information of the swimming pool lockers are generated, the structural integrity coefficient and the door response coefficient are obtained, the structural information of the lockers is represented by the structural incompleteness coefficient, and the door information of the lockers is represented by the door response coefficient.

[0052] The logic for obtaining the structural incompleteness coefficient is as follows: use ultrasonic phased array technology to scan the closing process of the swimming pool locker with ultrasonic waves, obtain the number of times the ultrasonic waves scan during the closing process of the swimming pool locker, and mark the number of times the ultrasonic waves scan during the closing process of the swimming pool locker as: n, obtain the number of defects and defect areas of the swimming pool locker each time the ultrasonic waves scan the swimming pool locker during the closing process, and mark the number of defects and defect areas of the swimming pool locker each time the ultrasonic waves scan the swimming pool locker during the closing process as: SL i and MJ i , where i=1, 2, 3, ..., n, i is the number of each scan;

[0053] It should be noted that the pool locker closing process is a fixed process, which is a specific time period to complete the closing of the pool locker, and is set by professionals in the field.

[0054] Get the total area of ​​the pool locker scan area and label the total area of ​​the pool locker scan area as: MJ all , the structural incompleteness coefficient is calculated by the formula: Among them, JG wz is the structural incompleteness coefficient,

[0055] It can be seen from the formula that the larger the structural incompleteness coefficient is, the more likely it is that key components such as hinges and locking mechanisms may be worn, deformed, or improperly installed during the closing process of the locker, indicating that the swimming pool locker may have safety issues.

[0056] The logic for obtaining the cabinet door response coefficient is as follows: the closing process of the pool locker is monitored by combining ultrasonic phased array technology and magnetic induction sensors. The ultrasonic phased array technology transmits and receives high-frequency ultrasonic waves and uses a phased array probe to control the transmission and reception time of each element to measure the distance during the cabinet door closing process. The magnetic induction sensor indirectly infers the position of the cabinet door by detecting changes in the magnetic field.

[0057] Set the number of sampling points j, and use ultrasonic phased array technology and magnetic induction sensor to obtain the distance between the cabinet door and the monitoring point during the closing process at different sampling points, and mark the distance determined by ultrasonic phased array technology as: CS q , mark the distance determined by the magnetic induction sensor as: CG q, where q = 1, 2, 3, ..., j, q is the number of the sampling point;

[0058] It should be noted that the monitoring point position is the placement position of the ultrasonic device and the magnetic induction sensor, and the dynamic behavior of the cabinet door is determined by the changes in the monitoring point position during the closing process of the cabinet door.

[0059] According to the data points at the sampling points obtained by the ultrasonic phased array technology and the magnetic induction sensor, two different distance change curves are drawn by curve fitting. The distance change curve of the ultrasonic phased array technology is marked as: CS, and the distance change curve of the magnetic induction sensor is marked as: CG;

[0060] Obtain the derivatives of the two distance change curves at different data points, and mark the derivatives of the ultrasonic phased array technology at different data points as: dCS q , the derivative of the magnetic induction sensor at different data points is marked as: dCG q ;

[0061] By calculating the correlation coefficient between the derivatives of the two distance change curves at different data points, the cabinet door response coefficient is obtained. The calculation formula is:

[0062] Among them, XY gm is the cabinet door response coefficient,

[0063]

[0064] It can be seen from the formula that the larger the cabinet door response coefficient is, the more obvious the abnormality is during the closing process of the cabinet door, such as incomplete closing or obstruction, and the entire closing process conforms to the expected dynamic behavior.

[0065] It should be noted that the sampling point provides static information of the measurement value, that is, the position of the cabinet door at a certain moment, and the derivative provides dynamic information, that is, the speed and direction of the curve change. By analyzing the derivative, we can understand the changing trend of the closing process, such as at which positions the cabinet door accelerates, decelerates or encounters obstacles.

[0066] Through comprehensive analysis of the structural information and door information of the swimming pool locker, the structural incompleteness coefficient and the door response coefficient are weighted and calculated to generate the quality assessment coefficient. The calculation formula of the quality assessment coefficient is: Among them, pg zl is the quality assessment coefficient, α1 and α2 are the proportional coefficients of the structural incomplete coefficient and the cabinet door response coefficient, and α1 and α2 are both greater than 0.

[0067] A first quality assessment coefficient threshold is set, and the quality assessment coefficient of the swimming pool locker in use is compared with the first quality assessment coefficient threshold. If the quality assessment coefficient of the swimming pool locker is greater than the first quality assessment coefficient threshold, the swimming pool locker is marked as a qualified locker and the swimming pool locker can continue to be used. If the quality assessment coefficient of the swimming pool locker is less than the first quality assessment coefficient threshold, the swimming pool locker is marked as an unqualified locker, indicating that the swimming pool locker may have safety problems and can no longer be provided to users, and the swimming pool locker needs to be inspected and repaired in a timely manner.

[0068] Regularly determine the quality assessment coefficient of the swimming pool lockers, ensure that the quality assessment coefficient of the swimming pool lockers is greater than the first quality assessment coefficient threshold, obtain qualified lockers, and determine the relationship between the quality assessment coefficients of qualified lockers and qualified lockers based on the usage records of qualified lockers.

[0069] It should be noted that the higher the quality assessment coefficient of a swimming pool locker, the more popular it may be among users. However, when the quality assessment coefficient of a swimming pool locker exceeds a certain limit, the user experience of using the swimming pool locker does not increase the popularity of the swimming pool locker according to the increase in the quality assessment coefficient. That is, below a certain critical limit, the popularity of the swimming pool locker shows a strong correlation with its quality assessment coefficient, which means that below this limit, as the quality assessment coefficient increases, user popularity (such as frequency of use, satisfaction, etc.) will increase significantly. However, once the quality assessment coefficient exceeds this limit, further improvement will not have a significant impact on popularity.

[0070] The optimal quality assessment coefficient range is identified through the analysis results of the Kendall correlation coefficient, and the relevance information of the pool lockers is determined. The relevance information of the pool lockers is represented by the welcome correlation coefficient. The logic for obtaining the welcome correlation coefficient is as follows: the quality assessment coefficients of different pool lockers and the usage frequency of the pool lockers are collected, the quality assessment coefficients are divided into multiple intervals, the usage frequencies of different pool lockers in the interval are sorted from large to small, and the quality assessment coefficients of different pool lockers in the interval are sorted from large to small.

[0071] Calculate the welcome correlation coefficient between the quality evaluation coefficient and the user's popularity in each interval. The calculation formula of the welcome correlation coefficient is: In the formula, τ b is the quality assessment coefficient of swimming pool lockers and the welcome correlation coefficient of the usage frequency of swimming pool lockers in the interval, P is the number of consistent pairs, Q is the number of disagreement pairs, and the calculation result usually ranges from -1 to 1. Positive and negative represent positive correlation and negative correlation. The larger the absolute value of the calculation result, the higher the correlation.

[0072] Set a welcome correlation coefficient threshold, and compare the welcome correlation coefficients of different intervals with the welcome correlation coefficient threshold to obtain intervals that are smaller than the welcome correlation coefficient threshold, that is, find intervals where the Kendall correlation coefficient is low or even close to zero, identify the critical point of transition from a high correlation interval to a low correlation interval, and use this point as the second quality assessment coefficient threshold.

[0073] The quality assessment coefficient of the swimming pool locker is compared with the second quality assessment coefficient threshold. If the quality assessment coefficient of the swimming pool locker is less than the second quality assessment coefficient threshold, the swimming pool locker is marked as a secondary locker, indicating that the swimming pool locker is a lower-quality swimming pool locker, and the user can perceive a poor user experience from the quality of the locker, and it is used as a spare locker. If the quality assessment coefficient of the swimming pool locker is greater than the second quality assessment coefficient threshold, the swimming pool locker is marked as a superior locker, indicating that the swimming pool locker is a better swimming pool locker, and the user cannot perceive a different user experience from other lockers from the quality of the locker, and it is provided to users first.

[0074] The present invention uses ultrasonic phased array technology and magnetic induction sensors to monitor the performance of swimming pool lockers during the closing process, obtains structural information and door information of the swimming pool lockers, generates quality evaluation standards for swimming pool lockers, and classifies swimming pool lockers based on the popularity of swimming pool lockers among users, ensuring that the quality of swimming pool lockers will not affect the user experience, and helps to identify potential structural defects and functional problems, thereby improving the safety of use of lockers and user satisfaction.

[0075] For example 2, please refer to Figure 2 , the present invention provides a magnetic induction intelligent management system for swimming pool lockers based on artificial intelligence, including an ultrasonic module, a magnetic induction module, a quality assessment module and a screening module, and signal connections between the modules;

[0076] Ultrasonic module, used to transmit and receive high-frequency ultrasonic waves, obtain internal structural information of the pool locker through beam scanning, conduct comprehensive ultrasonic testing on the closing process of the pool locker door, and identify internal defects;

[0077] The magnetic induction module is used to measure the change of magnetic field to infer the position and closing state of the cabinet door, and to fuse and analyze the magnetic induction data with the ultrasonic data to obtain the position change and dynamic behavior of the cabinet door during the closing process;

[0078] The quality assessment module is used to calculate the quality assessment coefficient of the locker during the closing process based on the comprehensive analysis of the structure information and door information of the swimming pool locker;

[0079] The screening module is used to distinguish qualified lockers from unqualified lockers, and to perform correlation analysis between the quality of qualified lockers and the popularity of users to identify superior lockers. Although the embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A magnetic induction intelligent management method for swimming pool lockers based on artificial intelligence, characterized in that: The specific steps include: S1: Use ultrasonic phased array technology to perform ultrasonic detection and analysis on the closing process of the swimming pool locker door to determine the defects of the swimming pool locker and generate structural information of the swimming pool locker; S2: By combining magnetic induction sensors and ultrasonic phased array technology, the dynamic behavior of the cabinet door during the closing process is monitored to obtain the cabinet door information of the swimming pool locker; S3: Comprehensively analyze the structural information and door information of the swimming pool lockers, quantify the quality of the swimming pool lockers during the door closing process, and screen out unqualified swimming pool lockers; S4: Determine qualified pool lockers, conduct a correlation analysis between the popularity of qualified pool lockers among users and the quality of the pool lockers, and reduce the correlation between the quality of the pool lockers and the popularity of the users.

2. The magnetic induction intelligent management method for swimming pool lockers based on artificial intelligence according to claim 1 is characterized in that: The structural information of the swimming pool locker includes: The structural information of the locker is represented by the structural incompleteness coefficient. The logic for obtaining the structural incompleteness coefficient is as follows: the closing process of the swimming pool locker is scanned by ultrasonic wave through ultrasonic phased array technology, the number of times the ultrasonic wave scans during the closing process of the swimming pool locker is obtained, and the number of times the ultrasonic wave scans during the closing process of the swimming pool locker is marked as: n, the number of defects and defect areas of the swimming pool locker each time the ultrasonic wave scans during the closing process of the swimming pool locker are obtained, and the number of defects and defect areas of the swimming pool locker each time the ultrasonic wave scans during the closing process of the swimming pool locker are marked as: SL i and MJ i , where i=1, 2, 3, ..., n, i is the number of each scan; Get the total area of ​​the pool locker scan area and label the total area of ​​the pool locker scan area as: MJ all , the structural incompleteness coefficient is calculated by the formula: Among them, JG wz is the structural incompleteness coefficient, 3. The magnetic induction intelligent management method for swimming pool lockers based on artificial intelligence according to claim 1 is characterized in that: The door information of the swimming pool locker includes: The door information of the locker is represented by the door response coefficient. The logic of obtaining the door response coefficient is as follows: the closing process of the pool locker is monitored by combining ultrasonic phased array technology and magnetic induction sensors. The ultrasonic phased array technology transmits and receives high-frequency ultrasonic waves and uses phased array probes to control the transmission and reception time of each element to measure the distance during the door closing process. The magnetic induction sensor indirectly infers the position of the door by detecting changes in the magnetic field. Set the number of sampling points j, and use ultrasonic phased array technology and magnetic induction sensor to obtain the distance between the cabinet door and the monitoring point during the closing process at different sampling points, and mark the distance determined by ultrasonic phased array technology as: CS q , mark the distance determined by the magnetic induction sensor as: CG q , where q = 1, 2, 3, ..., j, q is the number of the sampling point; According to the data points at the sampling points obtained by the ultrasonic phased array technology and the magnetic induction sensor, two different distance change curves are drawn by curve fitting. The distance change curve of the ultrasonic phased array technology is marked as: CS, and the distance change curve of the magnetic induction sensor is marked as: CG; Obtain the derivatives of the two distance change curves at different data points, and mark the derivatives of the ultrasonic phased array technology at different data points as: dCS q , the derivative of the magnetic induction sensor at different data points is marked as: dCG q ; By calculating the correlation coefficient between the derivatives of the two distance change curves at different data points, the cabinet door response coefficient is obtained. The calculation formula is: Among them, XY gm is the cabinet door response coefficient, 4. The magnetic induction intelligent management method for swimming pool lockers based on artificial intelligence according to claim 1 is characterized in that: The quantification of the quality of the pool locker during the door closing process includes: Through comprehensive analysis of the structural information and door information of the swimming pool locker, the structural incompleteness coefficient and the door response coefficient are weighted and calculated to generate the quality assessment coefficient. The calculation formula of the quality assessment coefficient is: Among them, pg zl is the quality assessment coefficient, α1 and α2 are the proportional coefficients of the structural incomplete coefficient and the cabinet door response coefficient, and α1 and α2 are both greater than 0.

5. The magnetic induction intelligent management method for swimming pool lockers based on artificial intelligence according to claim 1 is characterized in that: The qualified pool lockers include: A first quality assessment coefficient threshold is set, and the quality assessment coefficient of the swimming pool locker in use is compared with the first quality assessment coefficient threshold. If the quality assessment coefficient of the swimming pool locker is greater than the first quality assessment coefficient threshold, the swimming pool locker is marked as a qualified locker and the swimming pool locker can continue to be used. If the quality assessment coefficient of the swimming pool locker is less than the first quality assessment coefficient threshold, the swimming pool locker is marked as an unqualified locker, indicating that the swimming pool locker may have safety problems and can no longer be provided to users, and the swimming pool locker needs to be inspected and repaired in a timely manner.

6. The magnetic induction intelligent management method for swimming pool lockers based on artificial intelligence according to claim 1 is characterized in that: The correlation analysis between the popularity of qualified swimming pool lockers among users and the quality of swimming pool lockers includes: The optimal quality assessment coefficient range is identified through the analysis results of the Kendall correlation coefficient, and the relevance information of the pool lockers is determined. The relevance information of the pool lockers is represented by the welcome correlation coefficient. The logic for obtaining the welcome correlation coefficient is as follows: the quality assessment coefficients of different pool lockers and the usage frequency of the pool lockers are collected, the quality assessment coefficients are divided into multiple intervals, the usage frequencies of different pool lockers in the interval are sorted from large to small, and the quality assessment coefficients of different pool lockers in the interval are sorted from large to small. Calculate the welcome correlation coefficient between the quality evaluation coefficient and the user's popularity in each interval. The calculation formula of the welcome correlation coefficient is: In the formula, τ b is the quality evaluation coefficient of the pool lockers in the interval and the welcome correlation coefficient of the frequency of use of the pool lockers, P is the number of consistent pairs, and Q is the number of disagreement pairs; Setting a welcome correlation coefficient threshold, comparing the welcome correlation coefficients of different intervals with the welcome correlation coefficient threshold, obtaining intervals less than the welcome correlation coefficient threshold, identifying a critical point of transition from a high correlation interval to a low correlation interval, and using this point as a second quality assessment coefficient threshold; The quality assessment coefficient of the swimming pool locker is compared with the second quality assessment coefficient threshold. If the quality assessment coefficient of the swimming pool locker is less than the second quality assessment coefficient threshold, the swimming pool locker is marked as a secondary locker. If the quality assessment coefficient of the swimming pool locker is greater than the second quality assessment coefficient threshold, the swimming pool locker is marked as a premium storage.

7. The magnetic induction intelligent management system for swimming pool lockers based on artificial intelligence is used to implement the magnetic induction intelligent management method for swimming pool lockers based on artificial intelligence as described in any one of claims 1 to 6, characterized in that: It includes ultrasonic module, magnetic induction module, quality assessment module and screening module, and the signal connection between the modules; Ultrasonic module, used to transmit and receive high-frequency ultrasonic waves, obtain internal structural information of the pool locker through beam scanning, conduct comprehensive ultrasonic testing on the closing process of the pool locker door, and identify internal defects; The magnetic induction module is used to measure the change of magnetic field to infer the position and closing state of the cabinet door, and to fuse and analyze the magnetic induction data with the ultrasonic data to obtain the position change and dynamic behavior of the cabinet door during the closing process; The quality assessment module is used to calculate the quality assessment coefficient of the locker during the closing process based on the comprehensive analysis of the structure information and door information of the swimming pool locker; The screening module is used to distinguish qualified lockers from unqualified lockers, and to conduct a correlation analysis between the quality of qualified lockers and the popularity of users to identify superior lockers.

Images