Wearable multi-mode flexible microwave sensor

Abstract

The invention relates to the technical field of microwave sensors, in particular to a wearable multi-mode flexible microwave sensor. According to the method, the deformation state value is obtained by analyzing the deformation data, the stress state value is obtained by analyzing the stress data, the element connection state information is obtained through further analysis, then corresponding self-adaptive adjustment is performed according to the element connection state, the result after self-adaptive adjustment is obtained, and the self-adaptive adjustment result is obtained. The connection of each internal element can be monitored and analyzed to obtain a corresponding connection state, so that a user can find an abnormality in time to increase the controllability; the signal state is obtained by identifying the signal comprehensive parameters, a corresponding signal gain control instruction is generated, signal gain execution is carried out according to the signal gain control instruction, corresponding signal abnormal information is generated according to gain execution, and the signal abnormal information is obtained by judging the signal gain result and secondarily confirming the connection state. And the accuracy of monitoring element connection abnormity is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of microwave sensors, and in particular to a wearable multi-modal flexible microwave sensor. Background Art

[0002] As people pay more and more attention to health management and quality of life, wearable devices such as smart bracelets and smart watches are gradually becoming popular, which are used to monitor basic health data and sports information. Wearable multimodal flexible microwave sensors have further expanded their functions on this basis, and can monitor human physiological parameters and surrounding environmental information more comprehensively and deeply, meeting people's higher needs for health monitoring and convenience of life.

[0003] Existing wearable multimodal flexible microwave sensors will be stretched and twisted during use. The connections between the elements in the microwave sensor will be subjected to external forces in different directions, which can easily lead to loose connections, causing the sensitivity of the sensor elements to decrease or fail to work properly. In addition, the loose connection problem is difficult to troubleshoot, resulting in inconvenience in use. Summary of the invention

[0004] The present invention provides a wearable multimodal flexible microwave sensor for solving the above-mentioned technical problems.

[0005] A first aspect of the present invention provides a wearable multimodal flexible microwave sensor including a microwave sensor body; the microwave sensor body includes a flexible substrate material, a microwave sensing unit multimodal sensing module, a signal processing unit, a power supply and communication unit and a protective layer.

[0006] The flexible substrate material is used to install and support various modules and provide flexibility for the sensor. The flexible substrate material includes but is not limited to polymer films, fabrics, and nanofiber materials.

[0007] The microwave sensing unit is used to receive and transmit microwave signals and detect relevant information of the target object according to the changes of the microwave signals.

[0008] The multimodal sensing module obtains various physical data through pressure sensors, temperature sensors, and humidity sensors, and converts the physical data into electrical signals for processing.

[0009] The signal processing unit is used to receive the electrical signals from the sensing unit and the multimodal sensing module, and to amplify and transmit the electrical signals.

[0010] The power supply and communication module provides power to the sensor and transmits the information processed by each module to external devices.

[0011] The protective layer is used to protect the modules of the sensor; it protects the internal structure and components of the sensor from interference and damage from the external environment. The materials of the protective layer include but are not limited to polymer materials, inorganic materials, and composite materials, and have functions such as waterproof, dustproof, and corrosion-resistant.

[0012] A wearable multimodal flexible microwave sensor also includes: a data acquisition module, a connection status monitoring module, a signal gain control module, an adaptive adjustment module, a sensing working module, a user interaction module and a data storage module.

[0013] The data acquisition module obtains deformation data and stress data of each internal component by monitoring the internal components of the microwave sensor, obtains corresponding working data through the microwave sensor, and sends the deformation data, stress data and working data to the data storage module;

[0014] The deformation data of each component inside the microwave sensor during the stretching and torsion process is obtained through the strain sensor, and the deformation data includes displacement, deformation direction and deformation mode; the stress data of the internal components of the microwave sensor when subjected to external force is analyzed, and the stress data includes stress magnitude, stress distribution data and stress direction; the working data generated by the microwave sensor collection during operation includes sensing acquisition data and signal comprehensive parameters.

[0015] The connection status monitoring module is used to obtain deformation data and stress data, analyze the deformation data to obtain the deformation status value, analyze the stress data to obtain the stress status value, comprehensively analyze the deformation status value and the stress status value to obtain the component connection status information, and send the component connection status information to the data storage module.

[0016] As a further improvement of the present invention, the deformation data is analyzed in the following specific analysis method:

[0017] The component position information, deformation direction and deformation mode are obtained by identifying the deformation data; a preset detection time point is obtained, the component position information of each internal component corresponding to each detection time point is obtained, the component position information corresponding to two adjacent detection time points is overlapped and compared to obtain the component displacement, a preset displacement upper limit value is obtained, the component displacement corresponding to each component is compared with the displacement upper limit value, and when the component displacement is greater than the displacement upper limit value, the component displacement and the displacement upper limit value are difference calculated to obtain the displacement abnormality.

[0018] The material of each internal component is extracted from the cloud data repository, and the material of each internal component is identified to obtain anisotropic materials and isotropic materials; corresponding deformation influence values ​​are set for anisotropic materials and isotropic materials respectively, and the high-impact deformation directions corresponding to each type of material are obtained, and the deformation directions corresponding to each internal component are matched with the high-impact deformation directions to obtain the affected directions, and the number of affected directions corresponding to each internal component is counted and recorded as the affected direction value; for anisotropic materials, such as some metals and alloys, the deformation direction will significantly affect their physical and mechanical properties. For example, metals will form specific deformation textures during drawing or rolling. This anisotropy may cause internal components to be more susceptible to failure or damage in specific directions; for isotropic materials, the deformation direction has a relatively small effect on their performance, and excessive deformation or improper deformation direction will lead to internal defects.

[0019] Deformation modes include but are not limited to tensile deformation, compression deformation, bending deformation, and torsional deformation. The deformation process of each internal component corresponding to each deformation mode is obtained, and the duration of the deformation process is recorded to obtain the deformation duration. The deformation time is calculated by ratioing the deformation duration with the corresponding component displacement to obtain the deformation rate. The deformation rate is divided into multiple deformation rate intervals, each deformation rate interval corresponds to a rate influence value, and the deformation rate of each current internal component corresponding to each deformation mode is matched with multiple deformation rate intervals to obtain the corresponding rate influence value.

[0020] The displacement anomaly, the affected direction value and the velocity impact value are normalized and their values ​​are taken. The formula is used to The deformation state value XB is calculated; among them, WY, FX, and SL represent the displacement anomaly, the affected direction value, and the velocity influence value, respectively. It is expressed as the sum of the rate influence values ​​corresponding to n deformation modes of each internal component, where n is a positive integer; t1, t2, and t3 are all preset weight factors, with values ​​of 2.15, 1.74, and 2.12, respectively.

[0021] As a further improvement of the present invention, the stress data is analyzed, and the specific analysis method is as follows:

[0022] By identifying the stress number, the stress magnitude, stress distribution data and stress direction are obtained; the pre-set stress upper limit value is obtained, and the current stress value corresponding to each internal component is obtained according to the stress magnitude, and the stress value corresponding to each internal component is compared with the stress upper limit value. When the stress value is greater than the stress upper limit value, the stress value of the corresponding internal component is marked as an abnormal stress value.

[0023] The stress distribution data is identified to obtain the stressed area of ​​each internal component, the ratio of the stressed area to the total area of ​​the corresponding internal component is calculated to obtain the stress area ratio value, and a preset area ratio threshold is obtained. When the stress area ratio value is less than the area ratio threshold, the area ratio threshold and the stress area ratio value are difference-calculated to obtain a difference, and the difference is marked as the stress area influence value; based on the same stress condition, the smaller the stressed area, the greater the damage to the stressed part of the corresponding internal component.

[0024] The stress direction of the stress on each internal component is obtained, one stress direction is set as the reference stress direction, the reference stress direction is overlapped and compared with the remaining stress directions to obtain the stress angle value, a pre-set standard angle interval is obtained, the stress angle values ​​corresponding to the remaining stress directions are matched with the standard angle interval corresponding to the reference stress direction, the stress angle values ​​exceeding the standard angle interval are marked as opposite influence angles, the number of opposite influence angles is counted to obtain the opposite influence angle value, and the number of stress directions in the standard angle interval corresponding to the reference stress direction is obtained, and the difference between the opposite influence angle value and the number of stress directions is calculated to obtain the angle direction difference; the smaller the angle direction difference is, the greater the influence of multi-dimensional stress on the internal component is, and the larger the value is, the stress value of a single direction on the internal component is.

[0025] The abnormal stress value, stress area influence value and angle direction difference are normalized and their values ​​are taken. The formula is used The stress state value YL is calculated; among them, ycz, ylm, and jdc represent the abnormal stress value, stress area influence value, and angle direction difference, respectively; b1, b2, and b3 are all preset weight factors, and their values ​​are 2.405, 3.704, and 2.235, respectively.

[0026] As a further improvement of the present invention, the deformation state value and the stress state value are comprehensively analyzed, and the specific analysis method is as follows:

[0027] Two circles are constructed with the deformation state value and the stress state value as the radius. The centers of the two circles are on the same center line and the two circles are parallel. The centers of the two circles are connected to obtain a straight line perpendicular to the two circles. The length of the straight line is a fixed constant. A frustum is constructed with the two circles and the straight line. The volume of the frustum is calculated and the value of the volume is marked as the comprehensive state value. When the comprehensive state value is greater than the preset threshold, the corresponding component connection state information is generated as an internal component connection abnormality.

[0028] The signal gain control module is used to obtain working data and perform signal status analysis to obtain corresponding signal gain control instructions; identify the working data to obtain signal comprehensive parameters, and identify the signal comprehensive parameters to obtain signal status. When the signal status corresponds to a weak signal, a corresponding signal gain control instruction is generated, and signal gain is executed according to the signal gain control instruction. The result of the gain execution is identified, and when the signal gain has no response, corresponding signal abnormality information is generated, and the signal abnormality information is sent to the user interaction module.

[0029] The adaptive adjustment module performs corresponding adaptive adjustments according to the connection status of the component; it is used to obtain component connection status information and identify the component connection status information. When the status information corresponds to an abnormal connection of an internal component, the corresponding abnormal position point is obtained, and an adaptive adjustment strategy is generated for the abnormal position point, and adaptive adjustment is performed according to the adaptive adjustment strategy, and the corresponding component connection status information after the adaptive adjustment is subjected to secondary analysis to obtain secondary status information, an adaptive adjustment result is generated according to the secondary status information, and the adaptive adjustment result is sent to the user interaction module; the adaptive adjustment is to set an adjustable connection structure, such as an elastic buckle, an adaptive locking device, etc. When a loose connection is detected, it is automatically adjusted by mechanical or electromagnetic means to restore the tightness of the connection.

[0030] The sensor working module is used to control the work of each sensor acquisition module, identify the working data to obtain the sensor acquisition data, process the sensor acquisition data to obtain the corresponding acquisition data electrical signal, and send the acquisition data electrical signal to the data storage module.

[0031] The user interaction module is used to receive and display data from each module, and obtain the user's operation settings to obtain manual operation instructions; it receives signal abnormality information and adaptive adjustment results, and generates corresponding display information and warning information.

[0032] The data storage module is used to store deformation data, stress data and working data, and is also used to collect data electrical signals, store signal abnormality information and adaptive adjustment results.

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

[0034] 1. The present invention obtains a deformation state value by analyzing deformation data, and obtains a stress state value by analyzing stress data, and obtains component connection state information by comprehensively analyzing the deformation state value and the stress state value, and then performs corresponding adaptive adjustment according to the connection state of the component, obtains the result after adaptive adjustment to obtain an adaptive adjustment result, and can monitor and analyze the connection of each internal component to obtain the corresponding connection state, which can facilitate users to immediately discover abnormalities and increase control.

[0035] 2. The present invention obtains the signal state by identifying the comprehensive parameters of the signal, generates the corresponding signal gain control instruction, executes the signal gain according to the signal gain control instruction, identifies the result of the gain execution, and generates the corresponding signal abnormality information when the signal gain is unresponsive. By judging the result of the signal gain and re-confirming the connection state, the accuracy of the abnormal connection of the monitoring element is increased. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present application.

[0037] Figure 1 It is a principle block diagram of the present invention;

[0038] Figure 2 It is a schematic diagram of the microwave sensor body of the present invention. DETAILED DESCRIPTION

[0039] 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.

[0040] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1-2 In an embodiment of the present invention, an embodiment of a wearable multimodal flexible microwave sensor includes: a data acquisition module, a connection status monitoring module, a signal gain control module, an adaptive adjustment module, a sensing working module, a user interaction module and a data storage module.

[0041] The data acquisition module obtains deformation data and stress data of each internal component by monitoring the internal components of the microwave sensor, obtains corresponding working data through the microwave sensor, and sends the deformation data, stress data and working data to the data storage module;

[0042] The deformation data of each component inside the microwave sensor during the stretching and torsion process is obtained through the strain sensor. The deformation data includes displacement, deformation direction and deformation mode.

[0043] By analyzing the stress data of the internal components of the microwave sensor when subjected to external forces, the stress data includes stress magnitude, stress distribution data and stress direction;

[0044] The microwave sensor collects the working data generated during operation, and the working data includes sensor collection data and signal comprehensive parameters.

[0045] The connection status monitoring module acquires deformation data and stress data, analyzes the deformation data to obtain a deformation status value, analyzes the stress data to obtain a stress status value, comprehensively analyzes the deformation status value and the stress status value to obtain component connection status information, and sends the component connection status information to the data storage module.

[0046] The specific analysis method for deformation data analysis is as follows:

[0047] The component position information, deformation direction and deformation mode are obtained by identifying the deformation data; a preset detection time point is obtained, the component position information of each internal component corresponding to each detection time point is obtained, the component position information corresponding to two adjacent detection time points is overlapped and compared to obtain the component displacement, a preset displacement upper limit value is obtained, the component displacement corresponding to each component is compared with the displacement upper limit value, and when the component displacement is greater than the displacement upper limit value, the component displacement and the displacement upper limit value are difference calculated to obtain the displacement abnormality.

[0048] The material of each internal component is extracted from the cloud data repository, and the material of each internal component is identified to obtain anisotropic materials and isotropic materials; corresponding deformation influence values ​​are set for anisotropic materials and isotropic materials respectively, and the high-impact deformation directions corresponding to each type of material are obtained, and the deformation directions corresponding to each internal component are matched with the high-impact deformation directions to obtain the affected directions, and the number of affected directions corresponding to each internal component is counted and recorded as the affected direction value; for anisotropic materials, such as some metals and alloys, the deformation direction will significantly affect their physical and mechanical properties. For example, metals will form specific deformation textures during drawing or rolling. This anisotropy may cause internal components to be more susceptible to failure or damage in specific directions; for isotropic materials, the deformation direction has a relatively small effect on their performance, and excessive deformation or improper deformation direction will lead to internal defects.

[0049] Deformation modes include but are not limited to tensile deformation, compression deformation, bending deformation, and torsional deformation. The deformation process of each internal component corresponding to each deformation mode is obtained, and the duration of the deformation process is recorded to obtain the deformation duration. The deformation time is calculated by ratioing the deformation duration with the corresponding component displacement to obtain the deformation rate. The deformation rate is divided into multiple deformation rate intervals, each deformation rate interval corresponds to a rate influence value, and the deformation rate of each current internal component corresponding to each deformation mode is matched with multiple deformation rate intervals to obtain the corresponding rate influence value.

[0050] The displacement anomaly, the affected direction value and the velocity impact value are normalized and their values ​​are taken. The formula is used to The deformation state value XB is calculated; among them, WY, FX, and SL represent the displacement anomaly, the affected direction value, and the velocity influence value, respectively. It is expressed as the sum of the rate influence values ​​corresponding to n deformation modes of each internal component, where n is a positive integer; t1, t2, and t3 are all preset weight factors, with values ​​of 2.15, 1.74, and 2.12, respectively.

[0051] The stress data is analyzed in the following way:

[0052] By identifying the stress number, the stress magnitude, stress distribution data and stress direction are obtained; the pre-set stress upper limit value is obtained, and the current stress value corresponding to each internal component is obtained according to the stress magnitude, and the stress value corresponding to each internal component is compared with the stress upper limit value. When the stress value is greater than the stress upper limit value, the stress value of the corresponding internal component is marked as an abnormal stress value.

[0053] The stress distribution data is identified to obtain the stressed area of ​​each internal component, the ratio of the stressed area to the total area of ​​the corresponding internal component is calculated to obtain the stress area ratio value, and a preset area ratio threshold is obtained. When the stress area ratio value is less than the area ratio threshold, the area ratio threshold and the stress area ratio value are difference-calculated to obtain a difference, and the difference is marked as the stress area influence value; based on the same stress condition, the smaller the stressed area, the greater the damage to the stressed part of the corresponding internal component.

[0054] The stress direction of the stress on each internal component is obtained, one stress direction is set as the reference stress direction, the reference stress direction is overlapped and compared with the remaining stress directions to obtain the stress angle value, a pre-set standard angle interval is obtained, the stress angle values ​​corresponding to the remaining stress directions are matched with the standard angle interval corresponding to the reference stress direction, the stress angle values ​​exceeding the standard angle interval are marked as opposite influence angles, the number of opposite influence angles is counted to obtain the opposite influence angle value, and the number of stress directions in the standard angle interval corresponding to the reference stress direction is obtained, and the difference between the opposite influence angle value and the number of stress directions is calculated to obtain the angle direction difference; the smaller the angle direction difference is, the greater the influence of multi-dimensional stress on the internal component is, and the larger the value is, the stress value of a single direction on the internal component is.

[0055] The abnormal stress value, stress area influence value and angle direction difference are normalized and their values ​​are taken. The formula is used The stress state value YL is calculated; among them, ycz, ylm, and jdc represent the abnormal stress value, stress area influence value, and angle direction difference, respectively; b1, b2, and b3 are all preset weight factors, and their values ​​are 2.405, 3.704, and 2.235, respectively.

[0056] The deformation state value and stress state value are comprehensively analyzed, and the specific analysis method is as follows:

[0057] Two circles are constructed with the deformation state value and the stress state value as the radius. The centers of the two circles are on the same center line and the two circles are parallel. The centers of the two circles are connected to obtain a straight line perpendicular to the two circles. The length of the straight line is a fixed constant. A frustum is constructed with the two circles and the straight line. The volume of the frustum is calculated and the value of the volume is marked as the comprehensive state value. When the comprehensive state value is greater than the preset threshold, the corresponding component connection state information is generated as an internal component connection abnormality.

[0058] The signal gain control module acquires working data and performs signal status analysis to obtain corresponding signal gain control instructions; identifies the working data to obtain signal comprehensive parameters, and identifies the signal comprehensive parameters to obtain signal status. When the signal status corresponds to a weak signal, a corresponding signal gain control instruction is generated, and signal gain is executed according to the signal gain control instruction. The result of the gain execution is identified, and when the signal gain has no response, corresponding signal abnormality information is generated, and the signal abnormality information is sent to the user interaction module.

[0059] The adaptive adjustment module performs corresponding adaptive adjustments according to the connection status of the component; it is used to obtain component connection status information and identify the component connection status information. When the status information corresponds to an abnormal connection of an internal component, the corresponding abnormal position point is obtained, and an adaptive adjustment strategy is generated for the abnormal position point, and adaptive adjustment is performed according to the adaptive adjustment strategy, and the corresponding component connection status information after the adaptive adjustment is secondary analyzed to obtain secondary status information, an adaptive adjustment result is generated according to the secondary status information, and the adaptive adjustment result is sent to the user interaction module; the adaptive adjustment is to set an adjustable connection structure, such as an elastic buckle, an adaptive locking device, etc. When a loose connection is detected, it is automatically adjusted by mechanical or electromagnetic means to restore the tightness of the connection.

[0060] The sensor working module controls the work of each sensor acquisition module, identifies the working data to obtain the sensor acquisition data, processes the sensor acquisition data to obtain the corresponding acquisition data electrical signal, and sends the acquisition data electrical signal to the data storage module.

[0061] The user interaction module receives and displays data from each module, and obtains the user's operation settings to obtain manual operation instructions; it receives signal abnormality information and adaptive adjustment results, and generates corresponding display information and warning information.

[0062] The data storage module is used to store deformation data, stress data and working data, and is also used to collect data electrical signals, store signal abnormality information and adaptive adjustment results.

[0063] A wearable multimodal flexible microwave sensor also includes a microwave sensor body; the microwave sensor body includes: a flexible substrate material, a microwave sensing unit multimodal sensing module, a signal processing unit, a power supply and communication unit, and a protective layer.

[0064] The flexible substrate material is installed to carry each module and provide flexibility for the sensor. The flexible substrate material includes but is not limited to polymer films, fabrics, and nanofiber materials.

[0065] The microwave sensing unit receives and transmits microwave signals and detects relevant information of the target object according to the changes in the microwave signals.

[0066] The multimodal sensing module obtains various physical data through pressure sensors, temperature sensors, and humidity sensors, and converts the physical data into electrical signals for processing.

[0067] The signal processing unit receives the electrical signals from the sensing unit and the multimodal sensing module, and performs amplification and transmission on the electrical signals.

[0068] The power supply and communication module provides power to the sensor and transmits the information processed by each module to external devices.

[0069] The protective layer protects the modules of the sensor; it protects the internal structure and components of the sensor from interference and damage from the external environment. The materials of the protective layer include but are not limited to polymer materials, inorganic materials, and composite materials, and have functions such as waterproof, dustproof, and corrosion-resistant.

[0070] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A wearable multimodal flexible microwave sensor, comprising a data acquisition module, a sensing working module, a user interaction module and a data storage module, characterized in that: Also includes: A connection state monitoring module is used to obtain deformation data and stress data, analyze the deformation data to obtain a deformation state value, analyze the stress data to obtain a stress state value, comprehensively analyze the deformation state value and the stress state value to obtain component connection state information, and send the component connection state information to the data storage module; A signal gain control module is used to obtain working data and perform signal state analysis to obtain corresponding signal gain control instructions; The adaptive adjustment module performs corresponding adaptive adjustment according to the connection status of the component, obtains the result after the adaptive adjustment to obtain the adaptive adjustment result, and sends the adaptive result to the user interaction module.

2. A wearable multimodal flexible microwave sensor according to claim 1, characterized in that: The data acquisition module obtains deformation data and stress data of each internal component by monitoring the internal components of the microwave sensor, obtains corresponding working data through the microwave sensor, and sends the deformation data, stress data and working data to the data storage module; The deformation data of each component inside the microwave sensor during the stretching and torsion process is obtained through the strain sensor. The deformation data includes displacement, deformation direction and deformation mode. The stress data of the components inside the microwave sensor when subjected to external force is analyzed. The stress data includes stress magnitude, stress distribution data and stress direction. The microwave sensor collects the working data generated during operation, and the working data includes sensor collection data and signal comprehensive parameters.

3. A wearable multimodal flexible microwave sensor according to claim 1, characterized in that: The specific analysis method of the deformation data analysis is as follows: By identifying the deformation data, the component position information, deformation direction and deformation mode are obtained; a preset detection time point is obtained, the component position information of each internal component corresponding to each detection time point is obtained, the component position information corresponding to two adjacent detection time points is overlapped and compared to obtain the component displacement, a preset displacement upper limit value is obtained, the component displacement corresponding to each component is compared with the displacement upper limit value, and when the component displacement is greater than the displacement upper limit value, the component displacement and the displacement upper limit value are calculated by difference to obtain the displacement abnormality; The material of each internal component is extracted from the cloud data repository, and the material of each internal component is identified to obtain anisotropic material and isotropic material; corresponding deformation influence values ​​are set for the anisotropic material and the isotropic material, respectively, and the high-impact deformation direction corresponding to each material is obtained, and the deformation direction corresponding to each internal component is matched with the high-impact deformation direction to obtain the affected direction, and the number of affected directions corresponding to each internal component is counted and recorded as the affected direction value; The deformation modes include tensile deformation, compression deformation, bending deformation and torsion deformation. The deformation process of each internal component corresponding to each deformation mode is obtained, the duration of the deformation process is recorded to obtain the deformation duration, the deformation duration is calculated by ratio with the corresponding component displacement to obtain the deformation rate, the deformation rate is divided into multiple deformation rate intervals, each deformation rate interval corresponds to a rate influence value, and the deformation rate of each current internal component corresponding to each deformation mode is matched with multiple deformation rate intervals to obtain the corresponding rate influence value; The deformation state value is obtained by comprehensively calculating the displacement anomaly, the affected direction value and the velocity influence value.

4. A wearable multimodal flexible microwave sensor according to claim 1, characterized in that: The stress data is analyzed in the following specific way: By identifying the stress number, the stress magnitude, stress distribution data and stress direction are obtained; a preset stress upper limit value is obtained, and the current stress value corresponding to each internal component is obtained according to the stress magnitude, and the stress value corresponding to each internal component is compared with the stress upper limit value. When the stress value is greater than the stress upper limit value, the stress value of the corresponding internal component is marked as an abnormal stress value; The stress distribution data is identified to obtain the stressed area of ​​each internal component, the ratio of the stressed area to the total area of ​​the corresponding internal component is calculated to obtain the stress area ratio value, and a preset area ratio threshold is obtained. When the stress area ratio value is less than the area ratio threshold, the area ratio threshold and the stress area ratio value are calculated to obtain a difference value, and the difference value is marked as the stress area influence value; Obtain the stress direction of the stress on each internal component, set one stress direction as the reference stress direction, overlap and compare the reference stress direction with the remaining stress directions to obtain a stress angle value, obtain a preset standard angle interval, match the stress angle values ​​corresponding to the remaining stress directions with the standard angle interval corresponding to the reference stress direction, mark the stress angle values ​​exceeding the standard angle interval as opposite influence angles, count the number of opposite influence angles to obtain the opposite influence angle value, obtain the number of stress directions within the standard angle interval corresponding to the reference stress direction, and perform difference calculation between the opposite influence angle value and the number of stress directions to obtain an angle direction difference; The stress state value is obtained by comprehensively calculating the abnormal stress value, stress area influence value and angle direction difference.

5. A wearable multimodal flexible microwave sensor according to claims 3 and 4, characterized in that: The deformation state value and the stress state value are comprehensively analyzed, and the specific analysis method is as follows: Two circles are constructed with the deformation state value and the stress state value as the radius. The centers of the two circles are on the same center line and the two circles are parallel. The centers of the two circles are connected to obtain a straight line perpendicular to the two circles. The length of the straight line is a fixed constant. A frustum is constructed with the two circles and the straight line. The volume of the frustum is calculated and the value of the volume is marked as the comprehensive state value. When the comprehensive state value is greater than the preset threshold, the corresponding component connection state information is generated as an internal component connection abnormality.

6. A wearable multimodal flexible microwave sensor according to claim 1, characterized in that: The method for acquiring working data and performing signal state analysis to obtain corresponding signal gain control instructions is specifically: The working data is identified to obtain the signal comprehensive parameters, and the signal comprehensive parameters are identified to obtain the signal state. When the signal state corresponds to a weak signal, a corresponding signal gain control instruction is generated, and the signal gain is executed according to the signal gain control instruction. The result of the gain execution is identified, and when the signal gain has no response, the corresponding signal abnormality information is generated, and the signal abnormality information is sent to the user interaction module.

7. A wearable multimodal flexible microwave sensor according to claim 1, characterized in that: The specific working process of the adaptive adjustment module is as follows: obtaining component connection status information and identifying the component connection status information; when the status information corresponds to an abnormal internal component connection, obtaining the corresponding abnormal position point, generating an adaptive adjustment strategy for the abnormal position point, and adaptively adjusting according to the adaptive adjustment strategy; performing secondary analysis on the component connection status information corresponding to the adaptive adjustment to obtain secondary status information; generating an adaptive adjustment result according to the secondary status information; and sending the adaptive adjustment result to the user interaction module.

8. The wearable multimodal flexible microwave sensor according to claim 1, characterized in that: The sensor working module is used to control the work of each sensor acquisition module, identify the working data to obtain the sensor acquisition data, process the sensor acquisition data to obtain the corresponding acquisition data electrical signal, and send the acquisition data electrical signal to the data storage module.

9. The wearable multimodal flexible microwave sensor according to claim 1, characterized in that: The user interaction module is used to receive and display data from each module, and obtain the user's operation settings to obtain manual operation instructions; by receiving signal abnormality information and adaptive adjustment results, and generating corresponding display information and warning information.

10. The wearable multimodal flexible microwave sensor according to claim 1, characterized in that: It also includes a microwave sensor body; the microwave sensor includes a flexible base material, a microwave sensing unit multi-modal sensing module, a signal processing unit, a power supply and communication unit and a protective layer; The flexible substrate material is used to install and support each module, providing flexibility for the sensor; The microwave sensing unit is used to receive and transmit microwave signals, and detect relevant information of the target object according to changes in the microwave signals; The multimodal sensing module obtains various physical data through pressure sensors, temperature sensors, and humidity sensors, and converts the various physical data into electrical signals for processing; The signal processing unit is used to receive the electrical signals from the sensing unit and the multi-modal sensing module, and to amplify and transmit the electrical signals; The power supply and communication module provides power to the sensor and transmits the information processed by each module to an external device; The protective layer is used to protect each module of the sensor; It protects the internal structure and components of the sensor from interference and damage from the external environment.

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