Cable channel hidden space detection method based on self-insulation mechanical arm and multi-physical field sensor

Abstract

The invention discloses a cable channel hidden space detection method based on a self-insulation mechanical arm and a multi-physical field sensor, and the method comprises the steps: carrying out the modeling of the mechanical arm; a cable multi-physical field sensor measurement result is obtained through the mechanical arm; cable defects are judged and positioned by analyzing a measurement result; and in combination with an analysis result, designing a cable outer sheath monitoring method. A motor and a metal part are not arranged at the part close to the sensor, and the mechanical arm is driven by a motor driving rope far away from the mechanical arm to be pulled, so that the error of the leakage current and the difference temperature measurement value is relatively small; in combination with change rules of multiple physical fields such as an electric field and a thermal field under the condition of cable damage, measurement results of a Hall current transformer and a thermocouple temperature sensor are fused according to a D-S method, and accurate judgment and positioning of cable damage are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of cable monitoring, and in particular to a method for detecting hidden spaces in cable channels based on a self-insulating mechanical arm and a multi-physical field sensor. Background Art

[0002] As power cables are increasingly used in urban power grids, reliable insulation performance is an important guarantee for the safe operation of cables and the entire system. During the operation of the cable, the introduction of various defects will cause the internal and external insulation to deteriorate or be damaged, reducing the overall performance. Take the cable sheath as an example. After the outer sheath is damaged, the metal sheath and the earth form a loop, causing the sheath leakage current to increase. The existence of leakage current not only accelerates the degradation of the sheath material, but its heat also affects the current carrying capacity of the cable. If the defects cannot be located and inspected in time, it is likely to cause the breakdown of the main insulation and cause an accident.

[0003] Existing methods for detecting cable damage in hidden spaces of cable channels mostly use single-type information criteria such as leakage current or temperature, ignoring the mutual correlation of uncertainties between leakage current and temperature caused by the coupling of multiple physical fields. In addition, most of them are mounted on metal robotic arms driven by motors, which causes interference to the measurement results.

[0004] Therefore, it is crucial to design a hidden space detection method for cable channels based on a self-insulating robotic arm and multi-physical field sensors. Summary of the invention

[0005] In view of the above problems in the prior art, the present invention is proposed.

[0006] Therefore, the object of the present invention is to provide a method for detecting hidden spaces in cable channels based on a self-insulating mechanical arm and a multi-physical field sensor.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a cable channel hidden space detection method based on a self-insulating mechanical arm and a multi-physical field sensor, comprising:

[0008] Modeling the robotic arm;

[0009] Acquire cable multi-physics sensor measurement results through the robotic arm;

[0010] By analyzing the measurement results, the cable defects can be judged and located; and,

[0011] Based on the analysis results, a method for monitoring the cable outer sheath is designed.

[0012] As a preferred solution of the cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor described in the present invention, the multi-physical field sensor includes a through-type current transformer and a stable sensor.

[0013] As a preferred solution of the cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor of the present invention, the mechanical arm is driven by a rope, and the multi-physical field sensor is mounted on the support platform of the mechanical arm; the modeling of the mechanical arm includes:

[0014] Modeling the sensor-carrying support platform and the flexible rope in the rope-driven manipulator;

[0015] Establish the lateral bending equation of the support platform and the equilibrium equation of the forces and moments of the system;

[0016] Construct a kinematic model of the robotic arm.

[0017] As a preferred scheme of the hidden space detection method of the cable channel based on the self-insulating mechanical arm and the multi-physical field sensor described in the present invention, wherein: the judgment and positioning of the cable defects by analyzing the measurement results is to analyze the changing laws of the multi-physical fields of the electric field and the thermal field when the cable is damaged, and propose a strategy for judging and positioning the cable defects based on the multi-source fusion results of the multi-physical measurement results of the electric field and the temperature field.

[0018] As a preferred solution of the cable channel hidden space detection method based on self-insulating robotic arm and multi-physical field sensor described in the present invention, wherein: the method of designing cable outer sheath monitoring in combination with analysis results is to combine cable detection scene, analyze the working principle and working process of multi-physical sensors, design a set of robots to detect the outer sheath of long-distance cables, and realize online monitoring of the cable operation status in the cable channel.

[0019] As a preferred solution of the cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor of the present invention, wherein: in modeling the mechanical arm, the mechanical arm structure includes a fixed platform, a moving platform, a flexible rope and a spring;

[0020] Wherein, the flexible rope is used to connect the fixed platform and the moving platform, and the spring is arranged between the moving platform and the fixed platform.

[0021] As a preferred solution of the cable channel hidden space detection method based on the self-insulating manipulator and multi-physical field sensor of the present invention, the local coordinate system pxyz and the global coordinate system OXYZ are established on the basis of the manipulator structure, and the following four parameters are defined in the established coordinate systems to represent the position and working state of the manipulator:

[0022] represents the angle between axis s and axis X (characterizing the direction of spring bending);

[0023] It represents the angle between the plane where the moving platform is located and the plane where the fixed platform is located (characterizing the amplitude of the spring bending);

[0024] h p : represents the h coordinate of the top center of the spring in the coordinate system Osh (characterizing the vertical height of the bending spring);

[0025] s p : Represents the s-coordinate of the center of the top of the spring in the coordinate system Osh (representing the lateral translation of the bending spring).

[0026] All rope tensions are converted into equivalent forces and equivalent moments applied to the top center of the spring, and the kinematic equations of the mechanism are established by combining the lateral bending equation of the spring and the force and moment equilibrium equations applied to the moving platform.

[0027] As a preferred solution of the cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor of the present invention, in which: in the process of judging and locating the cable defects by analyzing the measurement results, according to the change law of the electric-thermal-material multi-physical field under the condition of the cable outer sheath damage, the electric field thermal field coupling model of the cable damage is constructed, wherein the electric field model is expressed by Poisson's equation as follows:

[0028]

[0029] in, Indicates electric potential; represents the charge density; ε represents the dielectric constant.

[0030] The energy calculation formula for thermal radiation is:

[0031]

[0032] Among them, σ represents the surface emissivity of the object; δ represents the Stefan-Boltzmann constant; A1 represents the effective area; Q represents the heat source; T represents the cable temperature; T0 represents the ambient temperature, and then analyzes the complex physical field coupling relationship that affects the numerical discrete solution domain and the distribution of the electric field due to the increase of leakage current near the defect causing local heating, and the material deforming under the action of thermal stress;

[0033] Based on the electric field and thermal field coupling model of the damaged cable mentioned above and the DS criterion method, the fuzzy and uncertain information such as leakage current characteristics and temperature thermal field distribution is processed to obtain the judgment and positioning results of the cable damage with higher confidence.

[0034] As a preferred solution of the cable channel hidden space detection method based on self-insulating robotic arm and multi-physical field sensor described in the present invention, in which: in combining the analysis results, in the method of designing cable outer sheath monitoring, according to the cable detection index requirements, Hall current sensor and thermocouple temperature sensor are selected as electric field and thermal field detection instruments.

[0035] The beneficial effects of the present invention are as follows: by not setting up motors and metal parts near the sensor, the robot arm is driven by a motor-driven rope far away from the robot arm, so that the errors of leakage current and differential temperature measurements can be relatively small; combined with the changing laws of multiple physical fields such as electric field and thermal field when the cable is damaged, the measurement results of the Hall current transformer and the thermocouple temperature sensor are fused according to the DS method to achieve accurate judgment and positioning of cable damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0037] Figure 1 Schematic diagram of modeling a rope-driven robotic arm

[0038] Figure 2 Schematic diagram for force and moment balance analysis

[0039] Figure 3 Schematic diagram of the working principle of the current sensor

[0040] Figure 4 Flowchart for designing a self-insulating robotic arm and multiphysics sensors. DETAILED DESCRIPTION

[0041] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0042] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0043] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0044] Secondly, the present invention is described in detail with reference to the schematic diagram. When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0045] Embodiment 1 provides a method for detecting hidden spaces in cable channels based on a self-insulating mechanical arm and a multi-physical field sensor, comprising:

[0046] S1: Model the robotic arm;

[0047] The robotic arm is driven by ropes, and the multi-physics field sensor is mounted on a support platform of the robotic arm; the modeling of the robotic arm includes modeling the support platform and spring parts that carry the sensor in the rope-driven robotic arm; establishing the lateral bending equation of the support platform and the balance equation of the force and torque of the system; and constructing a kinematic model of the robotic arm.

[0048] In modeling the robotic arm, the robotic arm is an insulating robotic arm, and the robotic arm structure includes a fixed platform, a moving platform, a flexible rope and a spring; wherein the flexible rope is used to connect the fixed platform and the moving platform, and the spring is arranged between the moving platform and the fixed platform.

[0049] In step S1, the self-insulating robot arm is modeled as Figure 1 As shown in Figure 1, the model mainly consists of four parts: a fixed platform, a moving platform, three flexible ropes with negligible mass and diameter, and a flexible support spring. One end of each driving rope is fixed to point P on the moving platform. i (i=1,2,3). The other end is fixed to the output end of the drive motor, and the rope passes through point B. i The moving platform is driven by three motors through three ropes. Figure 1 The global coordinate system is defined as OXYZ, with its origin O located at the center of the fixed platform; the local coordinate system is defined as pxyz, with its origin p located at the center of the moving platform. In the figure, a and b are the radii of the fixed platform and the moving platform respectively, the rope tension is ti, and the rope length between points Bi and Pi is l i , the unit vector of the tension direction of each rope is u i .

[0050] In the global coordinate system OXYZ, point B on the platform is determined i ( O b1, O b2, O The homogeneous coordinates of b3) can be expressed as:

[0051] O b1=(0,a,0,1) T

[0052]

[0053] In the local coordinate system pxyz, the point P on the moving platform is i ( p p1, p p2, p The homogeneous coordinates of p3) can be expressed as:

[0054] p p1=(0,b,0,1) T

[0055]

[0056] Assuming that the flexible spring can only bend in the same plane and the torsional strength of the spring is very large, it can be considered that the moving platform has no rotation about the axis z in the local coordinate system pxyz. In this case, the following four moving platform posture parameters are further defined as follows:

[0057] represents the angle between axis s and axis X (characterizing the direction of spring bending);

[0058] It represents the angle between the plane where the moving platform is located and the plane where the fixed platform is located (characterizing the amplitude of the spring bending);

[0059] h p : represents the h coordinate of the top center of the spring in the coordinate system Osh (characterizing the vertical height of the bending spring);

[0060] s p : Represents the s-coordinate of the center of the top of the spring in the coordinate system Osh (representing the lateral translation of the bending spring).

[0061] parameter and It is used to describe the posture of the moving platform in the global coordinate system OXYZ, and the parameters hp and sp are used to describe the position of the moving platform in the global coordinate system OXYZ. Due to the constraints of the lateral bending characteristic equation of the flexible spring, the parameter h p and pOnly one of them is independent. Therefore, only three of the above four parameters are independent. In order to avoid loss of generality, the parameter s p In other words, parameter s p Can be passed the given parameters and h p According to the defined pose parameters and Rodriguez rotation formula, the rotation matrix from the local coordinate system pxyz to the global coordinate system OXYZ can be obtained. O R P :

[0062]

[0063] in:

[0064]

[0065] Similarly, the homogeneous coordinate transformation matrix from the local coordinate system pxyz to the global coordinate system OXYZ can be expressed as:

[0066]

[0067] in: is the position vector of point p in the global coordinate system OXYZ.

[0068] When establishing the kinematic equation of the robotic arm, all rope tensions are converted into forces within the spring bending plane Osh, and all forces are converted into two mutually perpendicular forces F1 and F2 within this plane and a moment M perpendicular to the spring bending plane. Then, the kinematic equation of the robotic arm is established by combining the lateral bending equation of the spring and the force and moment balance equation applied to the moving platform.

[0069] like Figure 2 As shown in the figure, the flexible spring bends under the action of two forces F1 and F2 and a moment M. Assuming that the bionic flexible parallel joint mechanism under study bends within a small angle range, only linear bending curves are considered in this study. For any cross section of the spring, the linear equation for small bending can be expressed as:

[0070]

[0071] Where β represents the bending stiffness of the spring after compression. Based on the bending stiffness of the spring β0 and the length of the spring (initial length l0 and compressed length h p ), β can be expressed as:

[0072]

[0073] It should be noted that this study uses h pto approximate the length of the spring after compression. In fact, only when the spring does not bend at all (θ p =0), the length of the compressed spring is equal to h p If θ p ≠0, considering that the deformation angle is small in this study, h p It can approximate the length of the spring after compression. Therefore, the variable F2 can be approximated by Hooke's law as:

[0074] F2≈K(l0-h p )

[0075] Where K is the spring stiffness coefficient. Figure 2 In the system shown in , all the ropes must be able to generate tension to achieve the balance of the moving platform. The moving platform is regarded as a point mass with a mass of m located at the center of the moving platform. Therefore, the balance condition of the force and torque of the moving platform can be expressed as:

[0076]

[0077] Where: t i =t i u i ,u i =( O b i - O T p p p i ) / | O b i - O T p p p i |, and The above formulas can be used to preliminarily establish the kinematic equations of the insulating manipulator.

[0078] S2: Obtain the measurement results of the cable multi-physical field sensor through the robot arm, and judge and locate the cable defects by analyzing the measurement results;

[0079] The multi-physical field sensor includes a through-type current transformer and a stable sensor. The judgment and positioning of cable defects by analyzing the measurement results is to analyze the change law of the electric field and thermal field multi-physical fields when the cable is damaged, and propose a strategy for judging and positioning the cable defects based on the multi-source fusion results of the electric field and temperature field multi-physical measurement results.

[0080] When there are defects such as the outer sheath of the cable being broken, the metal sheath being corroded, or even the outer sheath being carbonized due to the discharge of the bracket, the physical fields such as the temperature field and the electric field constrain each other and change together. After obtaining the change law of the electric-thermal-material multi-physical field under the damaged outer sheath of a typical metal bracket structure, the fixed-point area sensing detection technology based on the local leakage current and differential temperature of the damaged outer sheath of the cable can identify and locate the defects, and propose a local detection strategy for the damaged outer sheath. First, the electric field distribution at the damaged part of the cable is analyzed, which can be described by the Poisson equation:

[0081]

[0082] in, Indicates electric potential; represents the charge density; ε represents the dielectric constant. The relationship between the relevant variables is summarized as follows:

[0083]

[0084] Where D is the electric displacement vector; γ is the conductivity; and J is the current density. The continuity equations at different interfaces are:

[0085]

[0086] Among them, ρ s represents the surface charge density on the medium boundary; n represents the normal unit vector on the interface. Since the power cable lines laid in pipes, tunnels, and cable trenches can be considered infinite compared to their diameters, for the heat conduction problem of solid media (cable body, soil), the heat conduction differential equation is as follows:

[0087]

[0088] in, Indicates solid density; C p represents the specific heat capacity under normal pressure; Q represents the heat source; k represents the thermal conductivity; and T represents the temperature of the heat source. The energy calculation formula for thermal radiation is:

[0089]

[0090] Among them, σ represents the surface emissivity of the object; δ represents the Stefan-Boltzmann constant; A1 represents the effective area, T represents the heat source temperature, and T0 represents the ambient temperature.

[0091] When solving the temperature field distribution through the temperature control equation, the heat source term needs to be known. The heat source calculation is related to the conductivity, which is a function of temperature. The specific coupling relationship is:

[0092]

[0093] Where a and b are temperature correlation coefficients.

[0094] At the same time, the increase in leakage current near the defect causes local heating, and the material deforms under the action of thermal stress, which in turn affects the numerical discrete solution domain and the distribution of the electric field. The specific expression of thermal strain is:

[0095]

[0096] In the formula, is the thermal strain; α is the thermal expansion coefficient. In summary, it can be seen from the Poisson equation that when the charge distribution in the insulation layer is uneven, an electric field gradient may be formed, which will lead to the generation of leakage current. After the leakage current is generated, it will cause local heating, change the temperature field, and then lead to thermal aging of the material, affecting the change of cable conductivity and electric field distortion. This complex coupling relationship leads to the one-sidedness of the pattern recognition of the cable insulation state based on a single type of information. The leakage current of the cable outer sheath and the differential temperature information have an uncertain correlation. Data fusion can reduce the information loss of a single detection method and improve the performance of intelligent detection systems with multiple detection methods.

[0097] The DS criterion method can objectively process fuzzy and uncertain information such as leakage current characteristics and temperature thermal field distribution, and obtain a more confident judgment result by fusing the independent judgments of multiple incompatible evidence bodies on the identification framework sub-propositions. The specific identification steps based on DS multi-source fusion are as follows:

[0098] (1) Construct the identification framework θ. If the n typical insulation modes of the cable outer sheath are denoted as A1, A2, …, A n , then its identification framework is θ={A1,A2,…,A n The cable outer sheath includes scratches and damages, so the identification framework is θ = {A1, A2}, where A1 is the scratch defect mode and A2 is the damage defect mode.

[0099] (2) Select evidence. Use leakage current features for identification as evidence 1, and use temperature difference features for identification as evidence 2. Decompose the changes of leakage current and temperature difference over time into wavelet packets, and use the node energy of wavelet packet decomposition as its feature vectors e1 and e2.

[0100] (3) Determine the basic reliability assignment of each evidence body. Use part of the data as the training set and use the leakage current feature vector e1 of the training set to train the neural network of evidence body 1. Use the remaining data as the test set to test the neural network and obtain the recognition rate S1 (A) of each defect mode of evidence body 1. j ); Similarly, the recognition rate S2(A j ).

[0101] (4) The two pieces of evidence are weighted and fused to obtain the weighted confidence assignment m(A) for each typical pattern after the weighted fusion of the two pieces of evidence. j) Bel(A j ) and Pl(A j) , and based on the decision rules, obtain the final decision result.

[0102] S3: Based on the analysis results, design a method for monitoring the cable outer sheath.

[0103] The combined analysis results are used to design a method for monitoring the outer sheath of a cable. The method combines the cable detection scenario, analyzes the working principle and working process of multiple physical sensors, designs a set of robots to detect the outer sheath of long-distance cables, and realizes online monitoring of the operating status of cables in cable channels.

[0104] In combining the analysis results and designing the cable outer sheath monitoring method, according to the cable detection index requirements, Hall current sensors and thermocouple temperature sensors are selected as electric field and thermal field detection instruments.

[0105] According to the above leakage current and differential temperature measurement requirements, the Hall current sensor is first selected as the leakage current sensor. The principle is as follows Figure 3 As shown, a current-carrying conductor will generate a magnetic field in the surrounding space, which can be gathered by the magnetic core; an air gap is opened at a certain section of the magnetic core, and the primary current is converted into a uniform magnetic field in the air gap; the Hall integrated chip is installed in the air gap so that its surface is perpendicular to the air gap magnetic field, and the Hall effect can be used to convert the air gap magnetic field into a Hall electromotive force, and the Hall electromotive force is modulated and output as a measurable voltage signal.

[0106] From the electric field analysis of the damaged cable in S2, it can be obtained that leakage current will be generated at the damaged part of the cable. Therefore, two Hall current sensors are arranged at the beginning and end of the cable respectively. When the cable is damaged, leakage current will be generated, making the results of the two current sensors before and after the cable different. Combined with the T-type equivalent circuit of the cable metal sheath and outer sheath and the equivalent impedance of the outer sheath between the metal sheath and the cable bracket, it can be used as one of the multi-source criteria for judging and locating cable damage.

[0107] At the same time, a thermocouple temperature sensor is used to measure the cable temperature difference. The working principle of the thermocouple is mainly based on the thermoelectric effect, that is, when two different types of metals or semiconductors are connected, a small voltage will be generated in the closed circuit due to the temperature difference. This voltage is called thermoelectric potential. By measuring the size of the thermoelectric potential, the temperature of the object being measured can be inferred.

[0108] In summary, two groups of Hall current sensors and thermocouple sensors are simultaneously mounted on the moving platform of the insulating robotic arm. The robotic arm controls the sensors to be arranged at the head and end of the cable. According to the current and temperature differences measured by the head and end sensors, it is determined whether the leakage current and temperature difference thresholds set in advance are exceeded, so as to judge and locate the damaged part of the cable.

[0109] Importantly, it should be noted that the construction and arrangement of the present application shown in a plurality of different exemplary embodiments are only exemplary. Although only a few embodiments are described in detail in this disclosure, it should be readily understood by those who refer to this disclosure that many modifications are possible (e.g., the size, scale, structure, shape and proportion of various elements, as well as parameter values ​​(e.g., temperature, pressure, etc.), mounting arrangements, use of materials, color, directional changes, etc.) without substantially departing from the novel teachings and advantages of the subject matter described in the application. For example, the element shown as integrally formed can be composed of multiple parts or elements, the position of the element can be inverted or otherwise changed, and the nature or number or position of the discrete element can be changed or changed. Therefore, all such modifications are intended to be included in the scope of the present invention. The order or sequence of any process or method steps can be changed or reordered according to alternative embodiments. In the claims, any "device plus function" clause is intended to cover the structure described herein that performs the function, and is not only structurally equivalent but also equivalent structure. Without departing from the scope of the present invention, other replacements, modifications, changes and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiments. Therefore, the invention is not limited to a specific embodiment, but extends to numerous modifications still falling within the scope of the appended claims.

[0110] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention) may not be described.

[0111] It will be appreciated that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but will be a routine task of design, fabrication, and production for those of ordinary skill having the benefit of this disclosure without undue experimentation.

[0112] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A cable channel hidden space detection method based on a self-insulating mechanical arm and a multi-physical field sensor, characterized in that: include, Modeling the robotic arm; Acquire cable multi-physics sensor measurement results through the robotic arm; By analyzing the measurement results, the cable defects can be judged and located; and, Based on the analysis results, a method for monitoring the cable outer sheath is designed.

2. The cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor as claimed in claim 1 is characterized in that: The multi-physics field sensor includes a through-hole current transformer and a stabilization sensor.

3. The cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor as claimed in claim 1 or 2, characterized in that: The robotic arm is driven by ropes, and the multi-physical field sensor is mounted on a support platform of the robotic arm; The modeling of the robotic arm includes: Modeling the sensor-carrying support platform and spring in the rope-driven robotic arm; Establish the lateral bending equation of the support platform and the equilibrium equation of the forces and moments of the system; Construct a kinematic model of the robotic arm.

4. The cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor as claimed in claim 3 is characterized in that: The method of judging and locating cable defects by analyzing the measurement results is to analyze the changing laws of the electric field and thermal field multi-physical fields when the cable is damaged, and propose a strategy for judging and locating the cable defects based on the multi-source fusion results of the electric field and temperature field multi-physical measurement results.

5. The cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor as claimed in claim 4 is characterized in that: The combined analysis results are used to design a method for monitoring the outer sheath of a cable. The method combines the cable detection scenario, analyzes the working principle and working process of multiple physical sensors, designs a set of robots to detect the outer sheath of long-distance cables, and realizes online monitoring of the operating status of cables in cable channels.

6. The cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor as claimed in claim 4 or 5, characterized in that: In modeling the robot arm, the robot arm structure includes a fixed platform, a moving platform, a flexible rope, and a spring; Wherein, the flexible rope is used to connect the fixed platform and the moving platform, and the spring is arranged between the moving platform and the fixed platform.

7. The cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor as claimed in claim 6 is characterized by: Based on the structure of the robot arm, the local coordinate system pxyz and the global coordinate system OXYZ are established respectively. The following four parameters are defined in the established coordinate systems to represent the position and working status of the robot arm: represents the angle between axis s and axis X (characterizing the direction of spring bending); It represents the angle between the plane where the moving platform is located and the plane where the fixed platform is located (characterizing the amplitude of the spring bending); h p : represents the h coordinate of the top center of the spring in the coordinate system Osh (characterizing the vertical height of the bending spring); s p : Represents the s-coordinate of the center of the top of the spring in the coordinate system Osh (representing the lateral translation of the bending spring). All rope tensions are converted into equivalent forces and equivalent moments applied to the top center of the spring, and the kinematic equations of the mechanism are established by combining the lateral bending equation of the spring and the force and moment equilibrium equations applied to the moving platform.

8. The cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor as claimed in claim 7 is characterized by: In order to judge and locate the cable defects by analyzing the measurement results, an electric field and thermal field coupling model of the cable damage site is constructed according to the change law of the electric-thermal-material multi-physical field when the cable outer sheath is damaged. The electric field model is expressed by Poisson's equation as follows: in, represents electric potential; ρc represents charge density; ε represents dielectric constant. The energy calculation formula for thermal radiation is: Among them, σ represents the surface emissivity of the object; δ represents the Stefan-Boltzmann constant; A1 represents the effective area; Q represents the heat source; T represents the cable temperature; T0 represents the ambient temperature, and then analyzes the complex physical field coupling relationship that affects the numerical discrete solution domain and the distribution of the electric field due to the increase of leakage current near the defect causing local heating, and the material deforming under the action of thermal stress; Based on the electric field and thermal field coupling model of the damaged cable mentioned above and the DS criterion method, the fuzzy and uncertain information such as leakage current characteristics and temperature thermal field distribution is processed to obtain the judgment and positioning results of the cable damage with higher confidence.

9. The cable channel hidden space detection method based on the self-insulating mechanical arm and the multi-physical field sensor as claimed in claim 8, characterized in that: In combining the analysis results and designing the cable outer sheath monitoring method, according to the cable detection index requirements, Hall current sensors and thermocouple temperature sensors are selected as electric field and thermal field detection instruments.

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