Silver needle heat conduction itinerant detector and detection system

Abstract

The invention relates to the technical field of inspection instrument detection, and provides a silver needle heat conduction inspection instrument and a detection system.The detection system of the silver needle heat conduction inspection instrument provides comprehensive and accurate data for other modules through a data fusion module, so that an attitude calibration module can adjust the attitude of a silver needle according to an accurate instruction, and the detection accuracy of the silver needle heat conduction inspection instrument is improved. The temperature control module realizes accurate temperature compensation and tissue impedance adjustment based on real-time data, the path planning module flexibly plans a detection path by means of multi-source information, and all the modules cooperatively operate, so that the overall performance of the detection system is greatly improved.

Description

Technical Field

[0001] The present application relates to the technical field of patrol inspection instrument detection, and in particular to a silver needle thermal conductivity patrol inspection instrument and a detection system. Background Art

[0002] The existing silver needle thermal conductivity inspection instrument has shortcomings. The existing equipment collects a single type of tissue information, making it difficult to fully understand the tissue status. When adjusting the posture of the silver needle, it mostly relies on manual operation, lacks accurate parameter reference and real-time calibration feedback, and it is difficult to ensure the optimal posture of the silver needle. Moreover, the existing inspection instrument cannot accurately compensate for temperature and adjust tissue impedance according to changes in the detection environment, such as the impact of hose bending on heat conduction. At the same time, in terms of detection path planning, the traditional method is fixed path detection, and the detection order cannot be flexibly adjusted according to the real-time status of the tissue, thereby reducing detection efficiency and accuracy. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present application provides a silver needle thermal conductivity inspection instrument and a detection system.

[0004] In a first aspect, the present application provides a silver needle thermal conductivity inspection instrument detection system, including: a data fusion module, a posture calibration module, a temperature control module and a path planning module;

[0005] The data fusion module is used to obtain the temperature, contact pressure and tissue impedance of the target tissue through the sensor array, transmit it to the edge node to extract the dimensional features of temperature gradient, pressure distribution and impedance change rate, and fuse and analyze the dimensional features to generate a control signal;

[0006] The posture calibration module is used to receive the posture calibration instruction in the control signal, adjust the inclination angle, vibration frequency and contact pressure of the silver needle, and visually identify the deviation between the outline of the silver needle and the standard posture image to verify the effect of the posture calibration;

[0007] The temperature control module is used to receive the temperature control instruction in the control signal, and control the temperature compensation and tissue impedance compensation of the inspection instrument during the detection process, wherein the tissue impedance compensation includes determining whether to adjust the output current according to the impedance change rate;

[0008] The path planning module is used to detect whether the phase angle of tissue impedance is abnormal and the degree of abnormality, so as to dynamically coordinate the execution timing of posture calibration and temperature control, and at the same time determine the detection path, detect the target tissue through the inspection instrument based on the detection path, and generate status information.

[0009] As an optional implementation manner, the extraction logic of the dimensional feature of the impedance change rate includes:

[0010] Acquire the tissue impedance of the target tissue by using a micro impedance sensor and record the timestamp of the tissue impedance;

[0011] Building a sliding window, dividing the tissue impedance within each sliding window into a plurality of data segments;

[0012] The impedance change rate is calculated for each data segment by the central difference method;

[0013] The impedance change rate is subjected to wavelet transformation to form multi-scale dimensional characteristics of the impedance change rate.

[0014] As an optional implementation, the logic for adjusting the inclination angle, vibration frequency and contact pressure of the silver needle includes:

[0015] Parse the attitude calibration instructions and extract the target calibration parameters, which include the target tilt angle, target vibration frequency and target contact pressure;

[0016] Calculate the deviation between the current posture parameters and the target calibration parameters to obtain the calibration amount;

[0017] The silver needle's tilt angle, vibration frequency, and contact pressure are adjusted based on the calibration amount.

[0018] As an optional implementation, the logic for verifying the effect of the posture calibration includes:

[0019] Acquire a posture image of the working area of ​​the silver needle, and grayscale the posture image to obtain a grayscale posture image;

[0020] Extract the outline of the silver needle based on the grayscale posture image;

[0021] The outline of the silver needle in the grayscale posture image is compared with the standard posture image, the tilt angle deviation is calculated, and the vibration frequency deviation and contact pressure deviation are simultaneously determined to obtain the effect of posture calibration;

[0022] Feedback the effect of attitude calibration to update the attitude calibration instructions.

[0023] As an optional implementation, the temperature compensation logic includes:

[0024] Monitor the temperature of the silver needle and the hose in real time, and sense the bending angle of the hose to determine the loss of heat conduction efficiency;

[0025] Analyze the temperature control instructions, extract the target temperature of the silver needle, and determine whether there is a temperature deviation;

[0026] If there is a temperature deviation, the temperature compensation value is calculated based on the loss of heat conduction efficiency;

[0027] Convert the temperature compensation value into the adjustment amount of heating power.

[0028] As an optional implementation, the logic of tissue impedance compensation includes:

[0029] Obtain tissue impedance and impedance change rate of target tissue in real time;

[0030] Determining the output current according to the tissue impedance of the target tissue and the heating power;

[0031] The output current is adjusted based on the impedance change rate, and the temperature deviation is monitored to determine whether the output current should be re-determined.

[0032] As an optional implementation, the detection logic of whether the phase angle of tissue impedance is abnormal includes:

[0033] Calculate the phase angle of tissue impedance;

[0034] Calculate the change rate and absolute value deviation of the phase angle, configure the change threshold and deviation threshold, compare the change rate and absolute value deviation of the phase angle with the change threshold and deviation threshold respectively, and determine whether the phase angle is abnormal and the degree of abnormality;

[0035] When an abnormal phase angle of tissue impedance is detected, the execution timing of posture calibration and temperature control is determined according to the degree of abnormality.

[0036] As an optional implementation, the detection path determination logic includes:

[0037] Generate an initial detection path based on the target tissue;

[0038] Decompose the initial detection path into multiple detection points and assign a detection priority to each detection point;

[0039] The temperature, contact pressure and abnormal state of tissue impedance of the target tissue in each detection point are monitored in real time, and the execution order of the detection points is reordered based on the detection priority and abnormal state to determine the detection path.

[0040] In a second aspect, the present application provides a silver needle thermal conductivity inspection instrument, including: an inspection instrument body, an operation panel, a fixing mechanism, a connecting plug, a hose, a connecting line, a silver needle and an adjusting mechanism;

[0041] The silver needle is connected to the inspection instrument body through a fixing mechanism, one end of the connecting plug is connected to the circuit in the inspection instrument body, and the other end is connected to the silver needle through a connecting line;

[0042] The adjusting mechanism is connected with the hose and is used for adjusting the bending angle of the hose. The operation panel is installed on the main body of the inspection instrument to display the status information of the detection system of the silver needle thermal conductivity inspection instrument.

[0043] Compared with the prior art, the beneficial effects of the present application are: the data fusion module provides comprehensive and accurate data for other modules, so that the posture calibration module can adjust the posture of the silver needle according to precise instructions, the temperature control module realizes precise temperature compensation and tissue impedance adjustment based on real-time data, and the path planning module flexibly plans the detection path with the help of multi-source information. The modules work together to greatly improve the overall performance of the detection system.

[0044] The data fusion module comprehensively acquires the temperature, contact pressure and tissue impedance data of the target tissue through the sensor array, and performs deep feature extraction and fusion analysis at the edge node to generate precise control signals. Compared with the existing technology, this multi-dimensional data collection and fusion analysis method can more comprehensively and accurately reflect the state of the target tissue, and provide a reliable basis for subsequent posture calibration, temperature control and path planning, greatly improving the adaptability of the detection system to complex tissue environments and the accuracy of detection.

[0045] The posture calibration module can accurately adjust the inclination angle, vibration frequency and contact pressure of the silver needle according to the posture calibration instructions in the control signal, and verify the calibration effect by visually identifying the deviation between the outline of the silver needle and the standard posture image. Compared with the traditional method of relying on manual experience or simple mechanical adjustment, this module realizes the automation and precision of posture adjustment, and has a real-time feedback mechanism, which can promptly detect and correct posture deviations, ensuring that the silver needle always maintains the best posture during the detection process, thereby improving the detection effect.

[0046] The temperature control module can accurately control the temperature compensation and tissue impedance compensation of the inspection instrument during the detection process according to the temperature control instructions in the control signal. It determines the heat conduction efficiency loss by real-time monitoring the temperature of the silver needle and the hose and sensing the bending angle of the hose, and performs temperature compensation accordingly. At the same time, it dynamically adjusts the output current according to the impedance change rate to achieve tissue impedance compensation. Compared with the existing technology, it significantly improves the accuracy of temperature control and ensures that the silver needle can stably output the appropriate temperature under various complex situations.

[0047] The path planning module can detect the phase angle anomalies and degree of anomalies of tissue impedance, dynamically coordinate the execution timing of posture calibration and temperature control, and determine the detection path according to the real-time status of the target tissue. This function enables the detection system to flexibly adjust the detection process according to the actual situation of the target tissue, give priority to abnormal areas, and improve detection efficiency and accuracy. Compared with the traditional fixed detection path method, it greatly enhances the adaptability of the detection system to different tissue conditions, and can obtain more comprehensive and in-depth information on the target tissue, providing stronger support for detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] 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. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0049] Figure 1 A system flow chart of a silver needle thermal conductivity inspection instrument detection system provided in an embodiment of the present application;

[0050] Figure 2 A logic diagram for extracting dimensional features of the impedance change rate of a silver needle thermal conductivity inspection system provided in an embodiment of the present application;

[0051] Figure 3 A logic diagram of tissue impedance compensation of a silver needle thermal conductivity inspection system provided in an embodiment of the present application;

[0052] Figure 4 A detection path determination logic diagram of a silver needle thermal conductivity inspection system provided in an embodiment of the present application;

[0053] Figure 5 This is a device structure diagram of a silver needle thermal conductivity inspection instrument provided in an embodiment of the present application.

[0054] Figure numerals: 1. Inspection instrument body; 2. Operation panel; 3. Fixing mechanism; 4. Connecting plug; 5. Hose; 6. Connecting wire; 7. Silver needle; 8. Adjusting mechanism. DETAILED DESCRIPTION

[0055] In order to make the objectives, technical solutions and advantages of the embodiments of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application are clearly and completely described below in conjunction with the drawings in the specification. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0056] Example 1

[0057] like Figure 1 As shown, a system flow chart of a silver needle thermal conductivity patrol meter detection system is provided for an embodiment of the present application. A silver needle thermal conductivity patrol meter detection system includes a data fusion module, a posture calibration module, a temperature control module, a path planning module and a self-check warning module.

[0058] The data fusion module is used to obtain the temperature, contact pressure and tissue impedance of the target tissue through the sensor array, transmit it to the edge node to extract the dimensional characteristics of temperature gradient, pressure distribution and impedance change rate, and fuse and analyze the dimensional characteristics to generate a control signal.

[0059] Specifically, Figure 2 As shown, the extraction logic of the dimensional features of the impedance change rate includes:

[0060] Acquire the tissue impedance of the target tissue through a micro impedance sensor and record the timestamp of the tissue impedance;

[0061] Building a sliding window, dividing the tissue impedance within each sliding window into a number of data segments;

[0062] The impedance change rate is calculated for each data segment by the central difference method;

[0063] The impedance change rate is subjected to wavelet transformation to form multi-scale dimensional characteristics of the impedance change rate.

[0064] Temperature information at different positions can reflect the heat conduction and metabolic activity inside the target tissue, which helps to determine the physiological state and treatment effect of the target tissue. Monitoring of contact pressure can ensure that the silver targets the target tissue with appropriate pressure to avoid excessive or insufficient pressure affecting detection and treatment. Tissue impedance is an important parameter reflecting the electrical properties of tissue. Combined with timestamps, it can analyze the changing trend of tissue impedance over time, providing richer information for subsequent feature extraction and analysis.

[0065] The temperature, contact pressure and tissue impedance of the target tissue are acquired through a sensor array, wherein temperature sensors are distributed inside the silver needle, at the needle tip, in the needle body and inside the hose near one end of the silver needle to comprehensively monitor temperature changes at different positions; contact pressure sensors are installed at the contact point between the silver needle and the target tissue to measure the contact pressure in real time; micro impedance sensors are used to acquire the tissue impedance of the target tissue and record the timestamp of the tissue impedance; through the arrangement of multi-position and multi-type sensors, the information on the temperature, contact pressure and tissue impedance of the target tissue can be acquired comprehensively and accurately, providing a rich and reliable data basis for subsequent feature extraction and fusion analysis.

[0066] The introduction of edge nodes can realize local data processing, reduce data transmission delays, and improve the response speed of the detection system. At the same time, allocating part of the data processing tasks to the edge nodes can reduce the burden on the cloud server and reduce the cost and energy consumption of the detection system. The collected temperature, contact pressure and tissue impedance data are transmitted to the edge nodes, and the data obtained by the sensor array are sent to the edge nodes through wireless transmission technologies such as Bluetooth or ZigBee, which realizes real-time and efficient data transmission, reduces data transmission delays, and improves the response speed of the detection system. At the same time, the data processing capability of the edge nodes can perform preliminary preprocessing and analysis of the data, providing more efficient support for subsequent feature extraction and fusion analysis.

[0067] By constructing a sliding window and data segmentation, continuous tissue impedance data can be divided into multiple local data segments, which is convenient for analyzing the changes in tissue impedance in different time periods; the central difference method can more accurately calculate the rate of change of data points, and has higher accuracy and better noise resistance than forward difference or backward difference; and the wavelet transform can decompose the signal into different frequency scales and extract the characteristic information of the signal at different scales. By performing wavelet transform on the impedance change rate, multi-scale impedance change rate characteristics can be obtained, which more comprehensively reflects the changes in tissue impedance.

[0068] The dimensional features of temperature gradient, pressure distribution and impedance change rate are extracted at the edge node. This embodiment focuses on the dimensional feature extraction logic of impedance change rate: according to the actual application requirements and data characteristics, the appropriate sliding window size and step size are selected. For example, the sliding window size can be set to 100 data points and the step size can be set to 10 data points. The continuous data is divided into local data segments to facilitate local analysis of the data, thereby improving the accuracy and pertinence of feature extraction.

[0069] Furthermore, the calculation formula of the impedance change rate is as follows:

[0070] ;

[0071] In the formula, Indicates the first The impedance change rate of each data point is Indicates the first The tissue impedance of the data points, Indicates the first The tissue impedance of the data points, Indicates the time interval of the sliding window.

[0072] Accurate calculation of the impedance change rate can more clearly reflect the changing trend of tissue impedance and provide an important basis for subsequent analysis and judgment.

[0073] Select a suitable wavelet basis function, such as Daubechies wavelet, and perform wavelet decomposition on the impedance change rate. The number of decomposition layers is determined according to actual needs and is generally set to 3-5 layers, thereby obtaining multi-scale impedance change rate characteristics, which can analyze the changes in tissue impedance at different frequency scales and capture the physiological and pathological information of the tissue more comprehensively.

[0074] Accurately extracted dimensional features are the key to subsequent fusion analysis and control signal generation. If the feature extraction is inaccurate or incomplete, it will lead to inaccurate fusion analysis results, which will in turn affect the generation of control signals and reduce the performance and effectiveness of the system.

[0075] A single dimensional feature cannot fully reflect the physiological and pathological state of the target tissue. By fusing and analyzing features of multiple dimensions, we can comprehensively utilize the information of each feature to improve the accuracy of judgment on the state of the target tissue. Machine learning algorithms have powerful classification and analysis capabilities, and can automatically learn the relationship between features, providing a more accurate basis for the generation of regulatory signals.

[0076] At the edge node, the extracted dimensional features of temperature gradient, pressure distribution and impedance change rate are fused and analyzed, and the dimensional features are classified and analyzed through machine learning-based fusion methods, such as support vector machine (SVM) or neural network. This includes normalizing the extracted dimensional features and mapping the eigenvalues ​​to the interval [0,1] to avoid the impact of dimensional differences between different features on the fusion analysis results. A large amount of sample data is collected, including feature data of normal tissues and diseased tissues, and the machine learning model is trained. During the training process, the cross-validation method is used to select the optimal model parameters and improve the generalization ability of the model. Finally, the normalized dimensional features are input into the trained machine learning model for classification and analysis to obtain the state judgment result of the target tissue.

[0077] By fusing and analyzing features from multiple dimensions, we can comprehensively utilize the information of each feature and improve the accuracy of judging the state of the target tissue. The application of machine learning algorithms can automatically learn the relationship between features, reduce interference from human factors, and improve the intelligence level of the detection system. Accurate fusion analysis results are the basis for the generation of regulatory signals. If the fusion analysis results are inaccurate, it will lead to errors in the generation of regulatory signals, affecting the detection and treatment effects of the detection system.

[0078] The generation of regulatory signals is to guide the coordinated work of other modules of the detection system to ensure the accuracy and effectiveness of detection and treatment. The generation of regulatory signals based on the state judgment results of the target tissue can achieve adaptive adjustment of the detection system and improve the performance and effectiveness of the detection system.

[0079] Based on the results of the fusion analysis, a control signal is generated. The control signal includes information such as posture calibration, temperature control, and path priority. According to the state judgment result of the target tissue, the corresponding control strategy is determined and the corresponding control signal is generated.

[0080] According to the classification results of the machine learning model, a corresponding control strategy is formulated. For example, if the target tissue is judged to be a diseased tissue, it is necessary to adjust the posture of the silver needle, increase the temperature or give priority to detecting this area; the control strategy is converted into a specific control signal, and the control signal is encoded in binary coding to ensure the accurate transmission and analysis of the control signal; the encoded control signal is sent to other modules of the detection system, such as the posture calibration module, the temperature control module and the path planning module; by generating accurate control signals, other modules of the detection system can be guided to work together, realize adaptive adjustment of the detection system, and improve the accuracy and effectiveness of detection and treatment.

[0081] The posture calibration module is used to receive the posture calibration instructions in the control signal, adjust the inclination angle, vibration frequency and contact pressure of the silver needle, and verify the effect of the posture calibration by visually identifying the deviation between the outline of the silver needle and the standard posture image.

[0082] Specifically, the logic for adjusting the inclination angle, vibration frequency and contact pressure of the silver needle includes:

[0083] Parse the attitude calibration instructions and extract the target calibration parameters, which include the target tilt angle, target vibration frequency and target contact pressure;

[0084] Calculate the deviation between the current posture parameters and the target calibration parameters to obtain the calibration amount;

[0085] The silver needle's tilt angle, vibration frequency, and contact pressure are adjusted based on the calibration amount.

[0086] The posture calibration module needs to know clearly what state the silver needle should be adjusted to, so it is necessary to accurately extract the target calibration parameters from the control signal. These target calibration parameters are the basis for subsequent calibration operations; the received control signal is decoded, and through a pre-set communication protocol, parameters such as the target tilt angle, target vibration frequency and target contact pressure are parsed from the decoded signal and stored in the module's cache register, so that the required target calibration parameters can be quickly and accurately obtained from the complex control signal, providing a basis for subsequent calculation of deviations.

[0087] Only by clearly understanding the difference between the current silver needle posture and the target posture can we determine the direction and amplitude of adjustment, i.e. the calibration amount. The posture sensor installed on the fixed mechanism can obtain the current silver needle's inclination angle and vibration frequency in real time, and the pressure sensor at the contact point between the fixed mechanism and the silver needle can obtain the current contact pressure. These real-time data are compared with the target calibration parameters in the cache register, and the deviation value is obtained by subtraction, i.e. the calibration amount. For example, if the target inclination angle is 30 degrees and the current actual inclination angle is 25 degrees, the calibration amount of the inclination angle is 5 degrees, which clearly quantifies the gap between the current posture and the target posture and provides an accurate numerical basis for adjusting the silver needle posture.

[0088] The silver needle is actually adjusted according to the calibration amount to achieve the target posture and contact pressure to meet the treatment needs. The spatial position and tilt angle of the silver needle are adjusted by the electric telescopic rod of the adjustment mechanism until the angle value fed back by the posture sensor is close to the target tilt angle; the vibration frequency of the silver needle is monitored based on the posture sensor. If abnormal vibration is detected, the vibration is suppressed by the damper of the adjustment mechanism to ensure the stability of the silver needle; the contact pressure between the silver needle and the body surface is dynamically adjusted through the flexible piezoresistive film of the fixing mechanism until the value fed back by the pressure sensor is close to the target contact pressure, so that the posture and contact pressure of the silver needle can be accurately adjusted according to the calibration amount to improve the accuracy of the treatment.

[0089] Specifically, the logic for verifying the effect of posture calibration includes:

[0090] Acquire a posture image of the working area of ​​the silver needle, and grayscale the posture image to obtain a grayscale posture image;

[0091] Extract the outline of the silver needle based on the grayscale posture image;

[0092] The outline of the silver needle in the grayscale posture image is compared with the standard posture image, the tilt angle deviation is calculated, and the vibration frequency deviation and contact pressure deviation are simultaneously determined to obtain the effect of posture calibration;

[0093] Feedback the effect of attitude calibration to update the attitude calibration instructions.

[0094] Color images contain too much information, which increases the complexity of image processing. Grayscale processing can simplify image information, highlight the contour features of the silver needle, and facilitate subsequent processing. The industrial camera is aimed at the working area of ​​the silver needle, and the color image of the working area of ​​the silver needle is obtained at a set frame rate (for example, 30 frames per second). The color image is converted into a grayscale image through the function in the image processing library (such as OpenCV), reducing the amount of image data, thereby obtaining a grayscale posture image that is more suitable for contour extraction and improving image processing efficiency.

[0095] Only by extracting the outline of the silver needle can it be compared with the standard posture image to determine the effect of the posture calibration. Through edge detection-based algorithms, such as the Canny edge detection algorithm, the Canny edge detection algorithm calculates the gradient strength and gradient direction of the pixels in the grayscale posture image, identifies the edge pixels of the silver needle, and then forms the outline of the silver needle. The edge pixels of the silver needle are optimized through morphological processing methods to remove noise and discontinuous edges to obtain a clearer outline of the silver needle, thereby accurately extracting the outline of the silver needle and providing accurate data for subsequent comparison and analysis.

[0096] By comparing with the standard posture image, the deviation after posture calibration is quantified to determine whether the posture calibration has achieved the expected effect. The tilt angle deviation is calculated through the geometric features of the silver needle's contour (such as the center of mass position and the direction of the long axis). For example, the angle between the long axis of the current silver needle's contour and the long axis of the silver needle's contour in the standard posture image is calculated to obtain the tilt angle deviation. According to the degree of vibration blur of the silver needle in the grayscale posture image, combined with the Fourier transform algorithm, the frequency components in the grayscale posture image are analyzed and compared with the frequency characteristics under the standard posture to determine the vibration frequency deviation. By analyzing the deformation of the silver needle and tissue contact area in the grayscale posture image, the contact pressure deviation is estimated, so as to comprehensively and accurately evaluate the effect of posture calibration and provide a basis for whether further calibration is needed in the future.

[0097] According to the effect of posture calibration, the posture calibration instruction is adjusted in time to ensure that the posture of the silver needle always meets the treatment requirements. The information of calibration effects such as the calculated tilt angle deviation, vibration frequency deviation and contact pressure deviation is sent back to the data fusion module through the communication interface. The data fusion module regenerates more accurate posture calibration instructions based on these feedback information and other monitoring data, and sends them to the posture calibration module, thereby realizing closed-loop control of posture calibration, continuously optimizing the posture of the silver needle and improving the treatment effect.

[0098] The tilt angle deviation is obtained by the angle between the long axis of the outline of the silver needle in the grayscale posture image and the long axis of the outline of the silver needle in the standard posture image. The calculation formula of the tilt angle deviation is as follows:

[0099] ;

[0100] In the formula, Indicates the tilt angle deviation, The vector coordinates representing the long axis of the outline of the silver needle in the standard pose image, The vector coordinates representing the long axis of the outline of the silver needle in the grayscale pose image.

[0101] The temperature control module is used to receive the temperature control instructions in the control signal, and control the temperature compensation and tissue impedance compensation of the silver needle thermal conductivity inspection instrument during the detection process, wherein the tissue impedance compensation includes determining whether to adjust the output current according to the impedance change rate.

[0102] Specifically, the temperature compensation logic includes:

[0103] Monitor the temperature of the silver needle and the hose in real time, and sense the bending angle of the hose to determine the loss of heat conduction efficiency;

[0104] Analyze the temperature control instructions, extract the target temperature of the silver needle, and determine whether there is a temperature deviation;

[0105] If there is a temperature deviation, the temperature compensation value is calculated based on the loss of heat conduction efficiency;

[0106] Convert the temperature compensation value into the adjustment amount of heating power.

[0107] The temperature of the silver needle and the hose and the bending angle of the hose will affect the heat conduction efficiency, and thus affect the heating effect of the silver needle on the target tissue. Only by mastering this information in real time can accurate temperature compensation be performed. Temperature sensors are installed inside the silver needle, at the needle tip, the needle body, and at the end of the hose near the silver needle. An angle sensor is installed in the adjustment mechanism of the hose to measure the bending angle of the hose in real time. The heat conduction efficiency loss at the current bending angle is calculated through the pre-stored relationship between the heat conduction efficiency and the bending angle. For example, , represents the heat conduction efficiency loss, represents the proportionality coefficient, Indicates the bending angle of the hose, thereby obtaining the key parameters affecting the heat conduction efficiency in real time, providing a basis for accurately calculating the temperature compensation value.

[0108] Clarifying the target temperature and determining the difference between the current temperature and the target temperature are the prerequisites for temperature compensation. The temperature control command is decoded, the target temperature of the silver needle is extracted, and the temperature of the silver needle monitored in real time is compared with the target temperature. If the difference between the two is greater than the set threshold (such as 0.5°C), it is determined that there is a temperature deviation, thereby determining whether temperature compensation is needed, as well as the direction and approximate amplitude of the compensation.

[0109] According to the loss of heat conduction efficiency and temperature deviation, the temperature value that needs additional compensation is calculated to ensure that the silver needle reaches the target temperature. The temperature compensation value is calculated according to the loss of heat conduction efficiency, such as , represents the target temperature of the silver needle, It indicates the temperature compensation value, so as to accurately calculate the temperature compensation value and provide a quantitative basis for adjusting the heating power.

[0110] Temperature control is ultimately achieved by adjusting the heating power, so the temperature compensation value must be converted into the corresponding heating power adjustment amount. The temperature compensation value is converted into the corresponding heating power adjustment amount according to the calculation formula of the heating power adjustment amount, thereby converting the temperature compensation demand into an actually operable heating power adjustment amount to achieve precise control of the silver needle temperature.

[0111] Furthermore, the calculation formula of the adjustment amount of heating power is as follows:

[0112] ;

[0113] In the formula, Indicates the adjustment amount of heating power, Represents the resistance of the silver needle.

[0114] Specifically, Figure 3 As shown, the logic of tissue impedance compensation includes:

[0115] Obtain tissue impedance and impedance change rate of target tissue in real time;

[0116] Determining the output current according to the tissue impedance of the target tissue and the heating power;

[0117] The output current is adjusted based on the impedance change rate, and the temperature deviation is monitored to determine whether the output current should be re-determined.

[0118] Tissue impedance and its rate of change are important bases for judging whether the output current needs to be adjusted and determining the output current size. The tissue impedance data of the target tissue is acquired in real time through the micro impedance sensor at the tip of the silver needle. The impedance change rate is calculated through a sliding window algorithm, such as the central difference method. The impedance change rate is calculated within each sliding window, so as to grasp the dynamic changes of tissue impedance in real time and provide data support for tissue impedance compensation.

[0119] In order to make the silver target produce a suitable thermal effect on the tissue, the output current needs to be determined according to the tissue impedance and the desired heating power. Combined with the relationship between the tissue impedance and the heating power of the target tissue, the formula ,in Represents the output current, Indicates the heating power, Represents tissue impedance to calculate the output current. In practical applications, taking into account factors such as the contact resistance between the silver needle and the target tissue, the formula is adapted and modified to obtain a more accurate output current calculation formula, so that the output current can be reasonably determined according to tissue characteristics and heating requirements to ensure the treatment effect.

[0120] The impedance change rate reflects the change in tissue state. When the impedance change rate is abnormal, the output current needs to be adjusted to maintain the appropriate treatment effect. At the same time, monitoring the temperature deviation can further confirm whether the output current needs to be re-determined. The threshold of the impedance change rate is set. When the calculated impedance change rate is greater than the threshold of the impedance change rate, the output current that needs to be adjusted is determined. At the same time, the temperature of the silver needle is monitored in real time. If a temperature deviation occurs, consider re-determining the output current. The way to adjust the output current is to increase or decrease the output current in a certain proportion according to the size and direction of the impedance change rate, thereby realizing dynamic adjustment of the output current to adapt to changes in tissue state and improve the stability and effectiveness of treatment.

[0121] The path planning module is used to detect whether the phase angle of tissue impedance is abnormal and the degree of abnormality, so as to dynamically coordinate the execution timing of posture calibration and temperature control, and determine the detection path at the same time. Based on the detection path, the target tissue is detected through a silver needle thermal conductivity inspection instrument and status information is generated.

[0122] Specifically, the detection logic of the phase angle abnormality of tissue impedance includes:

[0123] Calculate the phase angle of tissue impedance;

[0124] Calculate the change rate and absolute value deviation of the phase angle, configure the change threshold and deviation threshold, compare the change rate and absolute value deviation of the phase angle with the change threshold and deviation threshold respectively, and determine whether the phase angle is abnormal and the degree of abnormality;

[0125] When an abnormal phase angle of tissue impedance is detected, the execution timing of posture calibration and temperature control is determined according to the degree of abnormality.

[0126] The phase angle of tissue impedance can reflect the electrical characteristics and physiological state changes of the tissue. Calculating the phase angle is the basis for judging whether it is abnormal. An output current of a specific frequency is injected into the target tissue through a silver needle, and the voltage at both ends of the target tissue is measured. The acquired voltage and current data are sampled synchronously, and the time domain data is converted into frequency domain data through the fast Fourier transform algorithm. For the tissue impedance data at a specific frequency, its phase angle is calculated through complex operations, so as to accurately obtain the phase angle of tissue impedance and provide key data for subsequent abnormality judgment.

[0127] Furthermore, the calculation formula of the phase angle is as follows:

[0128] ;

[0129] In the formula, represents the phase angle of tissue impedance, represents the imaginary part of tissue impedance, Represents the real part of tissue impedance.

[0130] It is difficult to judge the change of tissue state only by the phase angle itself. By calculating the rate of change and absolute value deviation of the phase angle and comparing them with the corresponding threshold, it is possible to more accurately judge whether the phase angle is abnormal and the degree of abnormality. The rate of change of the phase angle is calculated by the sliding window algorithm. The ratio of the first-order difference of the phase angle to the time interval is calculated in each sliding window to obtain the rate of change of the phase angle. The absolute value deviation between the current phase angle and the normal reference phase angle is calculated, and the appropriate change threshold and deviation threshold are configured according to the actual situation. The calculated rate of change and absolute value deviation of the phase angle are compared with the change threshold and deviation threshold respectively. When the rate of change of the phase angle is greater than the change threshold or the absolute value deviation is greater than the deviation threshold, the phase angle is judged to be abnormal. The degree of abnormality is determined according to the degree of exceeding the corresponding threshold. For example, if it exceeds the threshold by 1-2 times, it is considered to be mildly abnormal, if it exceeds the threshold by 2-5 times, it is considered to be moderately abnormal, and if it exceeds the threshold by more than 5 times, it is considered to be severely abnormal. In this way, the abnormality and degree of the phase angle of tissue impedance can be accurately judged, providing a basis for subsequent decision-making.

[0131] Different degrees of phase angle abnormality have different effects on treatment. It is necessary to reasonably arrange the execution sequence of posture calibration and temperature control according to the degree of abnormality to improve the treatment effect. When there is no abnormality in the phase angle, posture calibration is performed first, then temperature control, and finally detection is performed according to the detection path; when there is an abnormality in the phase angle, the execution sequence is determined according to the degree of abnormality. When it is a mild abnormality, posture calibration and temperature control are started simultaneously, and then detection is performed according to the detection path; when it is a moderate abnormality, temperature control is started first, and posture calibration is performed after temperature control is stable, and then detection is performed according to the detection path; when it is a severe abnormality, temperature control is started immediately, and the changes in the phase angle are closely monitored during the temperature control process, and posture calibration is performed appropriately according to the changes in the phase angle; according to the changes in tissue state, the execution sequence of posture calibration and temperature control is flexibly adjusted to improve the pertinence and effectiveness of treatment.

[0132] Specifically, Figure 4 As shown, the logic for determining the detection path includes:

[0133] Generate an initial detection path based on the target tissue;

[0134] Decompose the initial detection path into several detection points and assign a detection priority to each detection point;

[0135] The temperature, contact pressure and abnormal state of tissue impedance of the target tissue in each detection point are monitored in real time, and the execution order of the detection points is reordered based on the detection priority and abnormal state to determine the detection path.

[0136] Provide a preliminary plan for the subsequent detection process of the inspection instrument to ensure full coverage of the target tissue and obtain complete detection data. According to the shape, size and location of the lesion area of ​​the target tissue, an initial detection path is generated based on the grid division method. The target tissue is divided into several small grid units, and each grid unit is tested in turn in a certain order (such as from left to right or from top to bottom). Determine the movement path of the silver needle, thereby obtaining a systematic and comprehensive initial detection path, providing a basic framework for subsequent detection operations and ensuring comprehensive detection of the target tissue.

[0137] In order to facilitate more detailed planning of the detection process, the detection order is reasonably arranged according to the importance of different detection points, key areas are detected first, and the detection efficiency and pertinence are improved. Detection points are set at a certain interval (such as 1 mm) along the initial detection path. For detection points close to known lesion areas and areas with large changes in tissue characteristics and areas at risk (such as near important blood vessels and nerves), higher detection priorities are assigned. For detection points far away from lesion areas or areas with relatively uniform tissues, lower detection priorities are assigned. The priority can be represented by digital codes, such as levels 1-5, where level 1 is the highest priority, thereby clarifying the importance of each detection point, making the detection process more focused, and giving priority to obtaining data from key areas, which helps to quickly locate problems and evaluate treatment effects.

[0138] The state of the target tissue will change during the detection process. Real-time monitoring of abnormal states and re-planning of paths based on detection priorities can detect and process abnormal areas more promptly and accurately, thereby improving the accuracy and effectiveness of detection. At each detection point, the sensor array is used to obtain data on the temperature, contact pressure, and tissue impedance of the target tissue in real time, and a temperature threshold (such as 45°C, a temperature exceeding this temperature is considered local overheating) and an impedance change rate threshold (such as a change of more than 10% per second is considered an impedance mutation) are set. When the temperature at a detection point is detected to be greater than the temperature threshold, the detection point is skipped and marked as "needs to be reviewed". When the impedance change rate is detected to be greater than the impedance change rate threshold, the detection density of the detection point is increased, such as at this detection point. Additional detection sub-points are added near the detection points; the execution order of the detection points is recalculated through a dynamic programming algorithm according to the detection priority and abnormal status. For example, for detection points with high detection priority and abnormal status, they are advanced to the front of the detection order, while for detection points with low detection priority and no abnormalities, they are appropriately postponed. In this way, the detection path can be dynamically adjusted according to the real-time status of the target tissue, abnormal areas can be detected first, the detection efficiency and the ability to detect lesions can be improved, and timely responses can be made to abnormal situations; the final status information includes the current position, posture, temperature of the silver needle, and the working status of each module, which are sent to the self-check warning module in a specific data frame format to provide it with comprehensive equipment operation status information.

[0139] The self-check and early warning module is used to receive status information, display the thermal map of pressure distribution in real time through the operation panel, and self-check the inspection instrument during each detection process to determine whether there is an abnormality and perform abnormality classification, display and sound and light prompts on the operation panel, and send hardware reset instructions to the data fusion module at the same time.

[0140] The self-check and early warning module needs to determine whether there is an abnormality based on the operating status of each part of the detection system, so it needs to receive status information sent by other modules such as the path planning module. These status information covers the current position, posture, temperature of the silver needle and the working status of each module, which is the basic data for subsequent operations; a special communication interface circuit is set in the self-check and early warning module to establish a communication connection with the path planning module and other related modules, and parse the received status information according to the preset data frame format, extract useful status parameters, and store them in the cache register in the self-check and early warning module, so that it can stably and accurately receive status information from other modules, provide comprehensive data support for subsequent self-check and abnormality judgment, and ensure real-time grasp of the operating status of the detection system.

[0141] The thermodynamic map of pressure distribution can intuitively display the distribution of contact pressure between the silver needle and the target tissue, helping the operator to quickly understand whether the pressure is uniform and whether there is a problem of excessive or insufficient local pressure, so as to make timely adjustments to ensure the treatment effect and patient safety. Through the display screen on the operation panel and the image processing algorithm, the received contact pressure data is converted into a thermodynamic map. First, it is divided into different levels according to the range of pressure values, and each level corresponds to a color; then, areas of different colors are drawn in the form of pixels on the display screen to form a thermodynamic map of pressure distribution. At the same time, a color scale and related annotations are added to the thermodynamic map to facilitate operators to read pressure values. The pressure distribution is presented in an intuitive and visual way, allowing operators to quickly and accurately obtain pressure information and improve the convenience and accuracy of operation.

[0142] Regular self-inspection of the inspection instrument can promptly detect equipment hardware failures and software operation anomalies, ensure the stability and reliability of the inspection instrument during the detection process, and avoid equipment failures affecting the treatment effect or causing harm to the patient; in terms of hardware self-inspection, the key hardware parts of the inspection instrument such as the power supply circuit, sensor circuit and communication circuit are inspected. For example, by injecting a specific detection signal into the power supply circuit, monitor whether the output voltage is within the normal range; calibrate the sensor array to check whether the measurement accuracy of the sensor meets the requirements; use communication diagnostic tools to test the connectivity of the communication link and the accuracy of data transmission; in terms of software self-inspection, determine whether there are any abnormalities in the output results of the data fusion module, attitude calibration module, temperature control module and path planning module, so as to comprehensively detect the hardware and software status of the inspection instrument, promptly discover potential failures and anomalies, ensure the normal operation of the equipment, and improve the stability and reliability of the system.

[0143] Analyzing and judging the self-test results, determining whether there are abnormal conditions, and classifying the abnormalities will help operators quickly understand the nature and severity of the problem and take appropriate solutions; establishing an abnormality judgment strategy, for example, when the power supply output voltage is lower than the set lower limit, it is judged as a power supply fault abnormality; when the sensor measurement data exceeds a reasonable range and the duration exceeds a certain threshold, it is judged as a sensor fault abnormality; according to the nature and impact of the abnormality, the abnormality is divided into different categories, such as severe abnormality, general abnormality and minor abnormality. Severe abnormalities include power supply short circuit and failure of key sensors, which will cause the equipment to fail to work properly or cause danger to patients; general abnormalities include partial communication data loss and non-critical sensor accuracy reduction, which will affect the accuracy of the test results, but the equipment can continue to operate; minor abnormalities include software interface display abnormalities, which have little impact on the core functions of the equipment; thus, it is possible to accurately judge whether there are abnormalities and reasonably classify the abnormalities, provide clear guidance for subsequent abnormal prompts and processing, and improve the efficiency of troubleshooting and resolution.

[0144] Promptly send abnormal prompts to operators so that they can quickly understand the abnormal situation of the equipment and take corresponding countermeasures to avoid further deterioration of the problem; on the operation panel, display abnormal information by changing the display color and flashing icons. For example, for serious abnormalities, the background color of the operation panel will be changed to red, and a striking "fault" icon will flash; for general abnormalities, the relevant abnormal information will be highlighted in yellow font, and equipped with an audible and visual alarm device. When an abnormality is detected, a loud alarm will sound and a warning light will flash; the frequency and volume of the alarm can be adjusted according to the severity of the abnormality. For example, in serious abnormalities, the alarm frequency will be higher and the volume will be louder; thus, abnormal information is conveyed to operators in an intuitive and strong way, ensuring that operators can notice the abnormal situation of the equipment in time and improving the safety and reliability of the equipment.

[0145] When a serious abnormality is detected and the normal operation of the equipment cannot be quickly restored by conventional means, a hardware reset instruction is sent to the data fusion module to try to solve the problem by resetting the hardware system to avoid the equipment being in a faulty state for a long time and affecting the treatment process; a special hardware reset signal transmission line is established between the self-test warning module and the data fusion module. When it is determined that there is a serious abnormality that requires a hardware reset, the self-test warning module sends a specific hardware reset signal to the data fusion module through the control circuit. The signal is a low-level pulse that lasts for several milliseconds. After receiving the signal, the data fusion module triggers the internal hardware reset circuit to reset the hardware of the entire detection system, thereby providing an effective means to solve serious abnormalities. Through hardware reset, the equipment can be restored to normal operation, reducing equipment downtime and ensuring the continuity of treatment.

[0146] Example 2

[0147] like Figure 5 As shown, a device structure diagram of a silver needle thermal conductivity inspection instrument is provided in an embodiment of the present application, and the device includes an inspection instrument body 1, an operation panel 2, a fixing mechanism 3, a connecting plug 4, a hose 5, a connecting line 6, a silver needle 7 and an adjustment mechanism 8.

[0148] The silver needle 7 is connected to the inspection instrument body 1 through a fixing mechanism 3. The fixing mechanism 3 ensures that the silver needle 7 is firmly installed and provides a basis for electrical connection for the silver needle 7. One end of the connecting plug 4 is connected to the circuit in the inspection instrument body 1, and the other end is connected to the silver needle 7 through a connecting line 6, thereby realizing the transmission of electrical energy from the inspection instrument body 1 to the silver needle 7, so that the silver needle 7 can generate heat for treatment.

[0149] The adjusting mechanism 8 is connected to the hose 5 and is used to adjust the bending angle of the hose 5. The connecting wire 6 is wrapped inside the hose 5, which can not only protect the connecting wire 6 from external interference, but also flexibly change its shape under the action of the adjusting mechanism 8 to adapt to different treatment scenarios, ensuring that the silver needle 7 can accurately reach the target tissue for treatment, while ensuring the stability of power transmission.

[0150] The operation panel 2 is installed on the inspection instrument body 1 and is connected to the control circuit in the inspection instrument body 1. The operator inputs various instructions through the operation panel 2, such as temperature setting and detection mode selection, and the operation panel 2 transmits these instructions to the control circuit in the inspection instrument body 1, thereby controlling the operation of the entire detection system. At the same time, the operation panel 2 receives feedback information from various modules of the detection system, such as the temperature of the silver needle 7, tissue impedance, thermal map of pressure distribution, abnormal prompts and other information, and displays it to the operator.

[0151] One of the operating methods of the silver needle thermal conductivity inspection instrument and detection system includes: when the inspection instrument starts working, the data fusion module first activates the sensor array, the temperature sensors are distributed inside the silver needle 7, the needle tip, the needle body and the inside of the hose 5 close to one end of the silver needle 7, the contact pressure sensor is located at the contact part between the fixing mechanism 3 and the silver needle 7, and the impedance sensor is at the tip of the silver needle 7. These sensors begin to obtain the temperature, contact pressure and tissue impedance data of the target tissue in real time, and generate control signals after relevant processing by the data fusion module.

[0152] The posture calibration module receives the control signal from the data fusion module, parses the posture calibration instruction, extracts the target calibration parameters therein, including the target inclination angle, target vibration frequency and target contact pressure, and adjusts the inclination angle, vibration frequency and contact pressure of the silver needle 7 through some device structures of the inspection instrument according to the target calibration parameters.

[0153] The temperature control module receives the control signal from the data fusion module, parses the temperature control instruction, including the target temperature of the silver needle 7, and monitors the temperature of the silver needle 7 and the hose 5 in real time. It senses the bending angle of the hose 5 through the angle sensor installed in the adjustment mechanism 8, and determines the loss of heat conduction efficiency to perform temperature compensation and tissue impedance compensation operations; the path planning module generates a detection path by detecting the phase angle anomaly of the tissue impedance and determining the execution timing, and sends it to the inspection instrument body 1 to perform the detection operation.

[0154] The self-check warning module receives status information sent from the path planning module and other modules, including the current position, posture, temperature of the silver needle 7 and the working status of each module, and displays the thermal map of the pressure distribution in real time through the operation panel 2, converts the pressure data into an intuitive thermal map form and presents it to the operator. At the same time, the inspection instrument is self-checked regularly, including hardware self-check and software self-check, so as to issue abnormal prompts through the operation panel 2.

[0155] Since the principle of solving the problem by the device in the embodiment of the present application is similar to that of the system described above in the embodiment of the present application, the implementation of the device refers to the implementation of the system, and the repeated parts will not be repeated.

Claims

1. A silver needle thermal conductivity inspection instrument detection system, characterized in that: include: Data fusion module, attitude calibration module, temperature control module and path planning module; The data fusion module is used to obtain the temperature, contact pressure and tissue impedance of the target tissue through the sensor array, transmit it to the edge node to extract the dimensional features of temperature gradient, pressure distribution and impedance change rate, and fuse and analyze the dimensional features to generate a control signal; The posture calibration module is used to receive the posture calibration instruction in the control signal, adjust the inclination angle, vibration frequency and contact pressure of the silver needle, and visually identify the deviation between the outline of the silver needle and the standard posture image to verify the effect of the posture calibration; The temperature control module is used to receive the temperature control instruction in the control signal, and control the temperature compensation and tissue impedance compensation of the inspection instrument during the detection process, wherein the tissue impedance compensation includes determining whether to adjust the output current according to the impedance change rate; The path planning module is used to detect whether the phase angle of tissue impedance is abnormal and the degree of abnormality, so as to dynamically coordinate the execution timing of posture calibration and temperature control, and at the same time determine the detection path, detect the target tissue through the inspection instrument based on the detection path, and generate status information.

2. A silver needle thermal conductivity inspection instrument detection system as claimed in claim 1, characterized in that: The extraction logic of the dimensional feature of the impedance change rate includes: Acquire the tissue impedance of the target tissue through a micro impedance sensor and record the timestamp of the tissue impedance; Building a sliding window, dividing the tissue impedance within each sliding window into a plurality of data segments; The impedance change rate is calculated for each data segment by the central difference method; The impedance change rate is subjected to wavelet transformation to form multi-scale dimensional characteristics of the impedance change rate.

3. A silver needle thermal conductivity inspection instrument detection system as claimed in claim 2, characterized in that: The logic of adjusting the inclination angle, vibration frequency and contact pressure of the silver needle includes: Parse the attitude calibration instructions and extract the target calibration parameters, which include the target tilt angle, target vibration frequency and target contact pressure; Calculate the deviation between the current posture parameters and the target calibration parameters to obtain the calibration amount; The silver needle's tilt angle, vibration frequency, and contact pressure are adjusted based on the calibration amount.

4. A silver needle thermal conductivity inspection instrument detection system as claimed in claim 3, characterized in that: The logic of verifying the effect of posture calibration includes: Acquire a posture image of the working area of ​​the silver needle, and grayscale the posture image to obtain a grayscale posture image; Extract the outline of the silver needle based on the grayscale posture image; The outline of the silver needle in the grayscale posture image is compared with the standard posture image, the tilt angle deviation is calculated, and the vibration frequency deviation and contact pressure deviation are simultaneously determined to obtain the effect of posture calibration; Feedback the effect of attitude calibration to update the attitude calibration instructions.

5. A silver needle thermal conductivity inspection instrument detection system as claimed in claim 4, characterized in that: The temperature compensation logic includes: Monitor the temperature of the silver needle and the hose in real time, and sense the bending angle of the hose to determine the loss of heat conduction efficiency; Analyze the temperature control instructions, extract the target temperature of the silver needle, and determine whether there is a temperature deviation; If there is a temperature deviation, the temperature compensation value is calculated based on the loss of heat conduction efficiency; Convert the temperature compensation value into the adjustment amount of heating power.

6. A silver needle thermal conductivity inspection instrument detection system as claimed in claim 5, characterized in that: The logic of tissue impedance compensation includes: Obtain tissue impedance and impedance change rate of target tissue in real time; Determining the output current according to the tissue impedance of the target tissue and the heating power; The output current is adjusted based on the impedance change rate, and the temperature deviation is monitored to determine whether the output current should be re-determined.

7. A silver needle thermal conductivity inspection instrument detection system as claimed in claim 6, characterized in that: The detection logic of whether the phase angle of the tissue impedance is abnormal includes: Calculate the phase angle of tissue impedance; Calculate the change rate and absolute value deviation of the phase angle, configure the change threshold and deviation threshold, compare the change rate and absolute value deviation of the phase angle with the change threshold and deviation threshold respectively, and determine whether the phase angle is abnormal and the degree of abnormality; When an abnormal phase angle of tissue impedance is detected, the execution timing of posture calibration and temperature control is determined according to the degree of abnormality.

8. A silver needle thermal conductivity inspection instrument detection system as claimed in claim 7, characterized in that: The determination logic of the detection path includes: Generate an initial detection path based on the target tissue; Decompose the initial detection path into multiple detection points and assign a detection priority to each detection point; The temperature, contact pressure and abnormal state of tissue impedance of the target tissue in each detection point are monitored in real time, and the execution order of the detection points is reordered based on the detection priority and abnormal state to determine the detection path.

9. A silver needle thermal conductivity inspection instrument, equipped with a silver needle thermal conductivity inspection instrument detection system according to any one of claims 1 to 8, characterized in that: include: Inspection instrument body, operation panel, fixing mechanism, connecting plug, hose, connecting wire, silver needle and adjusting mechanism; The silver needle is connected to the inspection instrument body through a fixing mechanism, one end of the connecting plug is connected to the circuit in the inspection instrument body, and the other end is connected to the silver needle through a connecting line; The adjusting mechanism is connected with the hose and is used for adjusting the bending angle of the hose. The operating panel is installed on the main body of the inspection instrument and is used for displaying the status information of the detection system of the silver needle thermal conductivity inspection instrument.

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