Method and system for detecting abnormal conditions of multiple mobile phone charging power supplies

Abstract

The invention discloses a method and system for detecting abnormal conditions of multiple mobile phone charging power supplies, and relates to the field of mobile power supplies, and the system comprises a sensing module which is used for monitoring the operation state of power supply equipment, and sensing the operation state information of the power supply equipment in real time when the power supply equipment operates; the judging module is used for traversing the running state information of the power equipment sensed by the sensing module and judging whether the power equipment runs abnormally or not based on the running state information of the power equipment; the interaction module is used for interacting with charging equipment on the power supply equipment in real time to feed back a judgment result about whether the power supply equipment operates abnormally; according to the invention, comprehensive and real-time monitoring is carried out on the operation state of the power supply equipment, key information such as input and output voltage and current, charging power and the like is covered, subtle changes during operation of the power supply can be timely perceived, whether the power supply has abnormal operation or not can be accurately judged by comparing the subtle changes with a safety judgment threshold value, the abnormal condition can be found at the first time, and the safety of the power supply is ensured. And the safety of the charging process is effectively ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile power supplies, and particularly to a detection method and system for abnormal conditions of a multi-mobile phone charging power supply. Background Art

[0002] As a device that can serve the power supply of multiple mobile phones as long as it has a wireless charging function, the wireless charger gets rid of the shackles of traditional charging cables. Just place the device on the charger to start charging. It is convenient to use, can effectively reduce the clutter of desktop cables, and provides a more convenient and tidy charging experience for users.

[0003] The invention patent application with the application number 202410042920.3 discloses a method for detecting the health status of a vehicle charger, including the following steps: obtaining real-time power output signal data of the vehicle charger within a preset time period, where the power output signal data includes current, voltage, and power data output by the vehicle charger; converting the power output signal into a spectrum signal based on the Fourier transform method to obtain the spectrum characteristics of the power output signal; classifying the spectrum characteristics of the power output signal through a clustering algorithm to obtain spectrum classification data; identifying the working mode of the vehicle charger according to the spectrum classification data to obtain the data on the change of the working mode of the vehicle charger within a preset time period; analyzing and evaluating the health status of the vehicle charger according to the data on the change of the working mode to obtain the health status level information of the vehicle charger; performing a safety assessment on the vehicle charger according to the health status level information, and giving a reusable suggestion to the user according to the safety. This application aims to solve the problem that "the traditional monitoring methods of vehicle chargers mainly focus on the real-time monitoring of basic electrical parameters, such as current, voltage, etc. However, these monitoring means are difficult to comprehensively reflect the performance changes and failure risks of vehicle chargers during long-term use. In actual applications, users lack a comprehensive understanding of the health status of vehicle chargers, and there are potential safety risks".

[0004] However, during the daily use of wireless chargers, the detection of their abnormal operating conditions often relies on means such as touching the surface temperature of the body or observing whether there are abnormalities. Such a detection method has poor comprehensiveness and poor predictability of abnormal operating states. As a result, when problems are discovered, the wireless charger has been completely damaged, and the repair cost and difficulty are relatively high.

[0005] Therefore, we propose a detection method and system for abnormal conditions of a multi-mobile phone charging power supply. Summary of the Invention

[0006] Aiming at the above-mentioned drawbacks of the prior art, the present invention provides a detection method and system for abnormal conditions of a multi-mobile phone charging power supply, which can effectively solve the problems of the prior art.

[0007] To achieve the above object, the present invention is implemented by the following technical solutions;

[0008] The present invention discloses a detection system for abnormal conditions of a multi-mobile phone charging power supply, including:

[0009] A sensing module, which is used to monitor the operating state of the power supply device, and when the power supply device is operating, it senses the operating state information of the power supply device in real time;

[0010] A sensing module and a visualization unit are arranged at the lower level of the sensing module. The sensing module is used to sense the operating state information of the power supply device in real time, and the visualization unit is used to visually present the operating state information of the power supply device in real time;

[0011] Among them, the operating state information of the power supply device sensed by the sensing module includes: input voltage and current, output voltage and current, charging power, electromagnetic radiation intensity, operating frequency, charging efficiency. The sensing module is integrated by sensors capable of sensing the corresponding operating state information of the power supply device. The visualization unit is integrated by a ranging sensor and a shape memory alloy. The shape memory alloy and the ranging sensor are deployed inside the power supply device. The end of the shape memory alloy is fixedly connected to the inner wall of the power supply device housing inside the power supply device. The shape memory alloy is set to deform at 68°C to 75°C and return to its original shape at normal temperature. A number of groups of ranging sensors are provided, and the number of groups of ranging sensors are evenly deployed in the area where the shape memory alloy deforms;

[0012] A determination module, which is used to traverse the operating state information of the power supply device sensed by the sensing module, and determine whether the power supply device has an abnormal operation based on the operating state information of the power supply device;

[0013] A receiving unit is arranged inside the determination module. The receiving unit is used to receive the latest operating state information of the power supply device sensed and stored in the sensing module in real time, and feedback the received latest operating state information of the power supply device to the determination module;

[0014] The determination module is provided with corresponding safety determination thresholds corresponding to the operating state information of the power supply device. The determination module compares the safety determination thresholds with the corresponding operating state information of the power supply device fed back by the receiving unit to determine whether the power supply device has an abnormal operation;

[0015] Among them, the determination module also stores a deformation shape model of the shape memory alloy that is completely deformed in an environment of 68°C to 75°C. The determination module compares the deformation shape model of the shape memory alloy in the operating state information of the power supply device received with the completely deformed deformation shape model to obtain a similarity comparison result, and then compares it with the corresponding safety determination threshold to determine whether the power supply device has an abnormal operation;

[0016] When the operating status information of any one or more power supply devices does not meet the corresponding safety judgment threshold, it is determined that the power supply device has an abnormal operation;

[0017] An interaction module for interacting with the charging device on the power supply device in real time to feedback the determination result of whether the power supply device is operating abnormally; A prediction module for receiving the operating status information of the power supply device sensed by the operation of the sensing module and predicting the power supply device failure risk based on the operating status information of the power supply device;

[0018] The lower level of the prediction module is connected with a multiplexing module, and the multiplexing module is used to access the cloud storing the operating status information of the power supply device, and calculate the power supply device failure risk performance value based on the power operation status information stored in the cloud with the same logic as the prediction module and generate a calculation result sequence. In the calculation result sequence, every three adjacent calculation results are used as the recognition target to identify whether three consecutive calculation results show a continuous upward trend. When any recognition result is yes, a jump is triggered based on the jump module, and the interaction module is used to feedback the recognition result;

[0019] The target of the jump triggered by the operation of the jump module is the interaction module. The jump module triggers a jump when the prediction module determines that there is a failure risk of the power supply device. After the jump module triggers a jump to the interaction module, the interaction module runs to send a pop-up window message to the charging device on the power supply device and display it on the charging device. The content of the pop-up window message is the text information preset by the system-side user expressing that the power supply device has a failure risk;

[0020] A jump module for obtaining the power supply device failure risk prediction result in the prediction module and triggering a jump based on the prediction result.

[0021] Furthermore, in the operation stage of the visualization unit, the ranging results of each ranging sensor are obtained, the same ranging results are classified into one category to obtain two ranging result sets, the corresponding position information of the ranging sensors from which the ranging results in the set with fewer ranging results are obtained is obtained, and they are connected adjacent to each other based on the position information to construct a shape model of the shape change of the memory metal, that is, a two-dimensional polyline, that is, the visualization unit visually presents the operating status information of the power supply device;

[0022] The sensing module runs continuously based on a preset period. The operating status information of the power supply device sensed by the operation of the sensing module is stored in the sensing module in real time, and after the sensing module monitors the end of the operation of the power supply device, the stored operating status information of the power supply device is copied to the cloud and cleared;

[0023] Among them, the cloud for storing the historical operating status information of the power supply device is created by the system-side user.

[0024] Further, the interaction module performs real-time interaction with the charging device on the power supply device based on Bluetooth technology, and in the operation stage, it obtains in real time the determination result of whether there is an abnormal operation of the power supply device in the determination module. When the obtained determination result is abnormal, the interaction module sends a pop-up message to the charging device on the power supply device for display on the charging device. The content of the pop-up message is the text information preset by the system-side user to express the abnormality of the power supply device;

[0025] Among them, the determination module continuously operates based on the update of the power supply device operation state information stored in the sensing module.

[0026] Further, the power supply device failure risk prediction logic in the prediction module is expressed as:

[0027] Taking the power supply device operation state information sensed by each operation of the sensing module as the calculation parameter of the power supply device failure risk performance value ;

[0028] ;

[0029] In the formula: is the input voltage, rated input voltage; is the input current, rated input current; is the output voltage, rated output voltage; is the output current, rated output current; is the charging power, rated charging power; is the electromagnetic radiation intensity, rated electromagnetic radiation intensity; is the operating frequency, rated operating frequency; is the charging efficiency, rated charging efficiency; is the correction;

[0030] Among them, the power supply device failure risk performance value is obtained based on the power supply device operation state parameters sensed by each operation of the sensing module , then there is , always performing the prediction operation with the latest three calculation results in . When the latest three calculation results show a continuous upward trend, it is determined that the power supply device has a failure risk. Otherwise, it is determined that the power supply device has no failure risk.

[0031] Further, the correction takes values subject to:

[0032] Obtain the shape memory alloy deformation form model in the latest three groups of power supply device operation state information, denoted as ;

[0033] ;

[0034] Where: and and are the differences between the deformation state models of two shape memory metals;

[0035] Among them, and and are all determined based on the feature matching algorithm, and their values are all in the range of 0 to 1.

[0036] Furthermore, the lower level of the perception module is connected to a sensing module and a visualization unit through wireless network interaction. The perception module is connected to a determination module through wireless network interaction. Inside the determination module, a receiving unit is connected through wireless network interaction. The determination module is connected to an interaction module and a prediction module through wireless network interaction. The prediction module is connected to a jump module and a multiplexing module through wireless network interaction.

[0037] On the other hand, a method for detecting abnormal conditions of a multi - mobile - phone charging power supply includes the following steps:

[0038] Monitor the operating state of the power supply device. When the power supply device is operating, real - time sense the operating state information of the power supply device and store the operating state information of the power supply device; copy the stored operating state information of the power supply device to the cloud for backup; set a safety determination threshold for the operation of the power supply device, and compare it with the stored operating state information of the power supply device to determine whether the operation of the power supply device is abnormal; the feedback stage of the abnormal determination result; predict the fault risk of the power supply device based on the operating state information of the power supply device; the feedback stage of the fault risk prediction result.

[0039] Adopting the technical solution provided by the present invention, compared with the known prior art, it has the following beneficial effects:

[0040] The present invention provides a method and a system for detecting abnormal conditions of a multi - mobile - phone charging power supply. During the operation of this method and system, it can comprehensively and real - time monitor the operating state of the power supply device, covering key information such as input and output voltage and current, charging power, etc. This helps to promptly detect subtle changes during the operation of the power supply. By comparing with the safety determination threshold, it can accurately determine whether there is an abnormal operation of the power supply, and can discover it at the first time when an abnormal situation occurs, effectively ensuring the safety of the charging process. In addition, it can predict the fault risk of the power supply device based on the monitoring data, give an early warning of potential faults, avoid affecting mobile - phone charging due to power supply failures and even causing damage to the mobile phone. Moreover, this system can visually present the operating state information of the power supply device and copy the relevant information to the cloud for storage after the power supply device finishes operating, which is convenient for subsequent viewing and analysis, helps to continuously optimize the performance of the power supply device, and improves the overall reliability and stability of multi - mobile - phone charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0042] Figure 1 It is a schematic structural diagram of a detection system for abnormal conditions of a multi - mobile - phone charging power supply;

[0043] Figure 2 It is a schematic flow diagram of a detection method for abnormal conditions of a multi - mobile - phone charging power supply. Detailed implementation manners

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0045] The following further describes the present invention with reference to the embodiments.

[0046] Embodiment 1:

[0047] A detection system for abnormal conditions of a multi - mobile - phone charging power supply in this embodiment, as Figure 1 shown, includes:

[0048] A sensing module, used to monitor the operating state of the power supply device, and when the power supply device is operating, it can sense the operating state information of the power supply device in real - time;

[0049] Under the sensing module, there are a sensing module group and a visualization unit. The sensing module group is used to sense the operating state information of the power supply device in real - time, and the visualization unit is used to visually present the operating state information of the power supply device in real - time;

[0050] Among them, the power device operation status information sensed by the sensing module includes: input voltage and current, output voltage and current, charging power, electromagnetic radiation intensity, operating frequency, and charging efficiency. The sensing module is integrated by sensors capable of sensing the corresponding power device operation status information. The visualization unit is integrated by a distance sensor and a shape memory alloy. The shape memory alloy and the distance sensor are deployed inside the power device. The end of the shape memory alloy is fixedly connected to the inner wall of the power device housing inside the power device. The shape memory alloy is set to deform at 68°C to 75°C and return to its original shape at normal temperature. There are several groups of distance sensors, and several groups of distance sensors are evenly deployed in the area where the shape memory alloy deforms;

[0051] During the operation stage of the visualization unit, the ranging results of each distance sensor are obtained, the same ranging results are classified into one category to obtain two ranging result sets, and the corresponding position information of the distance sensors from which the ranging results in the set with fewer ranging results are obtained is obtained. Based on the adjacent position information, they are connected to each other to construct a deformation shape model of the shape memory alloy, that is, a two-dimensional polyline, that is, the power device operation status information is visually presented in the visualization unit;

[0052] The sensing module operates continuously based on a preset period. The power device operation status information sensed by the sensing module is stored in the sensing module in real time. And after the sensing module monitors that the power device ends its operation, the stored power device operation status information is copied to the cloud and cleared;

[0053] Among them, the cloud for storing the historical operation status information of the power device is created by the system-end user;

[0054] The determination module is used to traverse the power device operation status information sensed by the sensing module and determine whether the power device has an operation abnormality based on the power device operation status information;

[0055] A receiving unit is provided inside the determination module. The receiving unit is used to receive the latest power device operation status information sensed and stored in the sensing module in real time and feedback the received latest power device operation status information to the determination module;

[0056] The determination module is provided with a corresponding number of safety determination thresholds corresponding to the power device operation status information. The determination module compares the safety determination thresholds with the corresponding power device operation status information fed back by the receiving unit to determine whether the power device has an operation abnormality;

[0057] Among them, the determination module also stores a deformation shape model in which the shape memory alloy is completely deformed at 68°C to 75°C. The determination module compares the deformation shape model of the shape memory alloy in the received power device operation status information with the completely deformed deformation shape model to obtain a similarity comparison result, and then compares it with the corresponding safety determination threshold to determine whether the power device has an operation abnormality;

[0058] When the operating status information of any one or more power supply devices does not meet the corresponding safety judgment threshold, it is determined that there is an abnormal operation of the power supply device;

[0059] An interaction module, used to interact with the charging device on the power supply device in real time and feedback the determination result of whether the power supply device is operating abnormally;

[0060] The interaction module performs real-time interaction with the charging device on the power supply device based on Bluetooth technology, and in the operation stage, it obtains in real time the determination result of whether there is an abnormal operation of the power supply device in the determination module. When the obtained determination result is abnormal, the interaction module sends a pop-up window message to the charging device on the power supply device and displays it on the charging device. The content of the pop-up window message is the text information preset by the system-side user to express the abnormality of the power supply device;

[0061] Among them, the determination module continuously operates based on the update of the operating status information of the power supply device stored in the sensing module;

[0062] A prediction module, used to receive the operating status information of the power supply device sensed by the sensing module and predict the power supply device failure risk based on the operating status information of the power supply device;

[0063] The power supply device failure risk prediction logic in the prediction module is expressed as:

[0064] Taking the operating status information of the power supply device sensed by the sensing module each time as the calculation parameter of the power supply device failure risk performance value ;

[0065] ;

[0066] In the formula: is the input voltage, rated input voltage; is the input current, rated input current; is the output voltage, rated output voltage; is the output current, rated output current; is the charging power, rated charging power; is the electromagnetic radiation intensity, rated electromagnetic radiation intensity; is the operating frequency, rated operating frequency; is the charging efficiency, rated charging efficiency; is the correction;

[0067] Among them, the power supply device failure risk performance value is obtained based on the operating status parameters of the power supply device sensed by each operation of the sensing module , then there is , always taking Perform a prediction operation on the latest three calculation results. When the latest three calculation results show a continuous upward trend, it is determined that there is a risk of failure of the power supply device; otherwise, it is determined that there is no risk of failure of the power supply device.

[0068] Through the operation of the above logical formula, the risk of power supply device failure is predicted in a digital form, so as to further protect the power supply device from hidden dangers and abnormalities in a timely manner, so as to maintain the power supply device earlier and ensure the long-term stable operation of the power supply device.

[0069] Correction The value follows:

[0070] Obtain the shape memory alloy deformation morphology model in the latest three sets of power supply device operation status information, denoted as ;

[0071] ;

[0072] In the formula: 、 、 is the difference between two shape memory alloy deformation morphology models;

[0073] Among them, 、 、 are all determined based on the feature matching algorithm, and the values are all in the range of 0 to 1;

[0074] Through the above logical formula, the correction applied in the power supply device failure risk prediction logic is obtained to ensure the stable application and execution of the power supply device failure risk prediction logic.

[0075] The prediction module is connected to a multiplexing module at the lower level. The multiplexing module is used to access the cloud that stores the power supply device operation status information, and based on the power operation status information stored in the cloud, the power supply device failure risk manifestation value is obtained, and a result sequence is generated. In the result sequence, every three adjacent obtained results are used as the recognition target to identify whether three consecutive obtained results show a continuous upward trend. When any recognition result is yes, a jump is triggered based on the jump module, and the interaction module is used to feedback the recognition result.

[0076] The target of the jump triggered by the operation of the jump module is the interaction module. The jump module triggers a jump when the prediction module determines that there is a risk of failure of the power supply device. After the jump module triggers a jump to the interaction module, the interaction module runs to send a pop-up message to the charging device on the power supply device and displays it on the charging device. The content of the pop-up message is the text information preset by the system-side user indicating that there is a risk of failure of the power supply device.

[0077] A jump module, configured to obtain the prediction result of the power device failure risk in the prediction module and trigger a jump based on the prediction result;

[0078] The lower level of the sensing module is connected with a sensing module and a visualization unit through wireless network interaction. The sensing module is connected with a determination module through wireless network interaction. Inside the determination module, there is a receiving unit connected through wireless network interaction. The determination module is connected with an interaction module and a prediction module through wireless network interaction. The prediction module is connected with a jump module and a multiplexing module through wireless network interaction.

[0079] In this embodiment, the sensing module runs to monitor the operating state of the power device. When the power device is running, it senses the operating state information of the power device in real time. The sensing module runs to sense the operating state information of the power device in real time. The visualization unit visually presents the operating state information of the power device in real time. The determination module runs later to traverse the operating state information of the power device sensed by the sensing module, and determines whether there is an abnormal operation of the power device based on the operating state information of the power device. The receiving unit receives the latest operating state information of the power device sensed and stored in the sensing module in real time, and feeds back the received latest operating state information of the power device to the determination module. The interaction module is configured to interact with the charging device on the power device in real time and feedback the determination result of whether the power device is operating abnormally. The prediction module further receives the operating state information of the power device sensed by the sensing module running, predicts the power device failure risk based on the operating state information of the power device. The multiplexing module synchronously accesses the cloud that stores the operating state information of the power device, and obtains the power device failure risk manifestation value with the same logic as the prediction module based on the operating state information of the power supply stored in the cloud and generates a result sequence of obtaining. In the result sequence of obtaining, every three adjacent obtained results are used as an identification target to identify whether three consecutive obtained results show a continuously rising trend. When the identification result is yes at any time, a jump is triggered based on the jump module, and the interaction module is used to feedback the identification result. Finally, the prediction result of the power device failure risk in the prediction module is obtained through the jump module, and a jump is triggered based on the prediction result.

[0080] Through the operation of the system in the above embodiment, it brings effective and comprehensive detection of abnormal operating states for the power device providing wireless charging, ensures the safety and stability of the power device, and timely informs the user when an abnormal problem or failure risk occurs, avoiding the further aggravation of the abnormal problem or failure risk.

[0081] Embodiment 2:

[0082] A method for detecting abnormal conditions of a multi - mobile - phone charging power supply, comprising the following steps:

[0083] Monitor the operating status of the power supply device. When the power supply device is running, continuously sense the operating status information of the power supply device and store the operating status information of the power supply device; copy the stored operating status information of the power supply device to the cloud for backup; set the safety determination threshold for the operation of the power supply device, compare it with the stored operating status information of the power supply device based on the set threshold, and determine whether the operation of the power supply device is abnormal; the feedback stage of the abnormal determination result; predict the fault risk of the power supply device based on the operating status information of the power supply device; the feedback stage of the fault risk prediction result.

[0084] In summary, during the operation of the method and system in the above embodiments, it can comprehensively and continuously monitor the operating status of the power supply device, covering key information such as input and output voltage and current, charging power, etc. This helps to promptly detect subtle changes during the operation of the power supply. By comparing with the safety determination threshold, it can accurately determine whether there is an abnormal operation of the power supply and discover it at the first moment when an abnormal situation occurs, effectively ensuring the safety of the charging process. In addition, it can predict the fault risk of the power supply device based on the monitoring data, give an early warning of potential faults in advance, avoid affecting the mobile phone charging due to power supply faults, and even damage to the mobile phone. Moreover, the system can visually present the operating status information of the power supply device and copy the relevant information to the cloud for storage after the power supply device finishes running, which is convenient for subsequent viewing and analysis, helps to continuously optimize the performance of the power supply device, and improve the overall reliability and stability of multi-mobile phone charging.

[0085] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements will not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A detection system for abnormal conditions of charging power supplies for multiple mobile phones, characterized in that: include: A sensing module is used to monitor the operating status of the power supply device and sense the operating status information of the power supply device in real time when the power supply device is running; A determination module, used for traversing the operating status information of the power supply device sensed by the sensing module, and determining whether the power supply device has an operating abnormality based on the operating status information of the power supply device; An interactive module is used to interact with the charging device on the power supply device in real time to feedback the result of whether the power supply device is operating abnormally; A prediction module, used for receiving the operating status information of the power supply device sensed by the sensing module, and predicting the failure risk of the power supply device based on the operating status information of the power supply device; The jump module is used to obtain the power supply equipment failure risk prediction result in the prediction module and trigger the jump based on the prediction result.

2. A detection system for abnormal conditions of charging power supplies for multiple mobile phones according to claim 1, characterized in that: The sensing module is provided with a sensor module and a visualization unit at the lower level. The sensor module is used to sense the operating status information of the power supply device in real time, and the visualization unit is used to visually present the operating status information of the power supply device in real time. Among them, the operating status information of the power supply equipment sensed by the sensor module includes: input voltage and current, output voltage and current, charging power, electromagnetic radiation intensity, operating frequency, and charging efficiency. The sensor module is integrated with sensors that can sense the operating status information of the corresponding power supply equipment. The visualization unit is integrated with a ranging sensor and a memory metal. The memory metal and the ranging sensor are deployed inside the power supply equipment. The end of the memory metal is fixedly connected to the inner wall of the power supply equipment casing inside the power supply equipment. The memory metal is set to deform at 68°C ~ 75°C and restore to its original shape under normal temperature. There are several groups of ranging sensors, and several groups of ranging sensors are evenly deployed in the area where the memory metal is deformed.

3. A detection system for abnormal conditions of charging power supplies for multiple mobile phones according to claim 2, characterized in that: During the operation phase of the visualization unit, the ranging results of each ranging sensor are obtained, the same ranging results are classified into one category to obtain two ranging result sets, the corresponding position information of the ranging sensor from each ranging result in the set with fewer ranging results is obtained, and the adjacent ones are connected to each other based on the position information to construct a memory metal deformation morphology model, that is, a two-dimensional polyline, that is, the visual presentation of the operating status information of the power supply device in the visualization unit; The sensing module operates continuously based on a preset cycle, and the operating status information of the power supply device sensed by the sensing module is stored in the sensing module in real time. After the sensing module detects that the power supply device has finished operating, the stored operating status information of the power supply device is copied to the cloud and cleared; Among them, the cloud used to store the historical operating status information of the power supply equipment is created by the system end user.

4. A detection system for abnormal conditions of charging power supplies for multiple mobile phones according to claim 1, characterized in that: The determination module is internally provided with a receiving unit, and the receiving unit is used to receive in real time the latest power supply device operating status information sensed and stored in the sensing module, and feed back the received latest power supply device operating status information to the determination module; The determination module is provided with a corresponding number of safety determination thresholds corresponding to the operation status information of the power supply device, and the determination module compares the safety determination thresholds with the operation status information of the corresponding power supply device fed back by the receiving unit to determine whether the power supply device has an operation abnormality; The judgment module also stores a deformation morphology model of memory metal that is completely deformed under a temperature of 68°C to 75°C. The judgment module compares the deformation morphology model of memory metal in the received operating status information of the power supply device with the deformation morphology model of complete deformation, obtains the similarity comparison result, and then compares it with the corresponding safety judgment threshold to determine whether the power supply device has an operating abnormality. When any one or more of the power supply equipment operating status information does not meet the corresponding safety judgment threshold, it is determined that the power supply equipment has an operating abnormality.

5. A detection system for abnormal conditions of charging power supplies for multiple mobile phones according to claim 1, characterized in that: The interaction module interacts with the charging device on the power supply device in real time based on Bluetooth technology, and obtains the determination result of whether the power supply device has an operation abnormality in the determination module in real time during the operation stage. When the determination result is abnormal, the interaction module sends a pop-up window message to the charging device on the power supply device, which is displayed on the charging device. The content of the pop-up window message is text information preset by the system end user to describe the abnormality of the power supply device; Wherein, the determination module operates continuously based on the update of the power supply device operation status information stored in the perception module.

6. A detection system for abnormal conditions of charging power supplies for multiple mobile phones according to claim 1, characterized in that: The power supply equipment failure risk prediction logic in the prediction module is expressed as: The power supply equipment operating status information sensed by the sensing module each time is used as the power supply equipment failure risk performance value Calculation parameters of ； Where: is the input voltage, the rated input voltage; is the input current and the rated input current; is the output voltage, the rated output voltage; is the output current, the rated output current; is charging power and rated charging power; is the electromagnetic radiation intensity and the rated electromagnetic radiation intensity; is the operating frequency and the rated operating frequency; is the charging efficiency and the rated charging efficiency; To amend; Among them, the power supply equipment failure risk performance value is calculated based on the power supply equipment operation status parameters sensed by each sensing module operation. , then , always The prediction operation is performed based on the three latest calculation results. When the three latest calculation results show a continuous upward trend, it is determined that the power supply device has a failure risk. Otherwise, it is determined that the power supply device does not have a failure risk.

7. A detection system for abnormal conditions of charging power supplies for multiple mobile phones according to claim 6, characterized in that: The amendment The value is subject to: Obtain the latest three sets of power supply equipment operating status information in the memory metal deformation morphology model, recorded as ; ； Where: , , The difference between the two memory metal deformation morphology models; in, , , They are all determined based on the feature matching algorithm, and their values ​​are all in the range of 0 to 1.

8. A detection system for abnormal conditions of charging power supplies for multiple mobile phones according to claim 1, characterized in that: The prediction module is connected to a multiplexing module at the lower level, and the multiplexing module is used to access the cloud that stores the power supply equipment operation status information, and obtain the power supply equipment failure risk performance value based on the power supply operation status information stored in the cloud that is the same as the prediction module logic. , and generate a sequence of obtained results, in which every three adjacent obtained results are used as recognition targets, and whether three consecutive obtained results show a continuous upward trend is recognized. When any recognition result is yes, a jump is triggered based on a jump module, and the recognition result is fed back by an interactive module; The target of the jump module is the interaction module. The jump module is triggered to jump when the prediction module determines that the power supply device has a failure risk. After the jump module triggers the jump to the interaction module, the interaction module runs to send a pop-up message to the charging device on the power supply device, which is displayed on the charging device. The content of the pop-up message is text information preset by the system user that expresses the failure risk of the power supply device.

9. A detection system for abnormal conditions of charging power supplies for multiple mobile phones according to claim 1, characterized in that: The perception module is interactively connected to a sensor module and a visualization unit at its lower level through a wireless network, the perception module is interactively connected to a determination module through a wireless network, the determination module is interactively connected to a receiving unit through a wireless network, the determination module is interactively connected to an interaction module and a prediction module through a wireless network, and the prediction module is interactively connected to a jump module and a multiplexing module through a wireless network.

10. A method for detecting abnormal conditions of charging power supplies for multiple mobile phones, the method being an implementation method of a system for detecting abnormal conditions of charging power supplies for multiple mobile phones as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: monitor the operating status of the power supply device. When the power supply device is running, the operating status information of the power supply device is sensed in real time, and the operating status information of the power supply device is stored; Step 2: Copy the stored power supply equipment operating status information to the cloud for backup; Step 3: Setting a power supply device operation safety determination threshold, and comparing the set threshold with the stored power supply device operation status information to determine whether the power supply device is operating abnormally; Step 4: Feedback stage of abnormal determination results; Step 5: predicting the power supply device failure risk based on the power supply device operation status information; Step 6: Feedback phase of failure risk prediction results.

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