Digital image-based multi-dimensional cable arc-caused fire assessment method

Abstract

The invention relates to a digital image-based multi-dimensional cable arc-caused fire assessment method. The method comprises the following steps of: establishing synchronous acquisition of multi-dimensional physical information of an ignition process under live operation of a cable by matching a plurality of high-speed cameras with a plurality of smoke, gas and temperature sensors; establishing and calculating a three-dimensional model of the cable fire caused by the arc by using a multi-physical field coupling simulation means based on an FDS kernel and taking various typical fault arcs as fire heat sources; and according to the electric arc and cable flame images and the multi-dimensional physical information data, establishing a cable electric arc fire characteristic data set, and in combination with an analytic hierarchy process, evaluating and judging the cable fire danger degree under various types of fault electric arc conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of fault arc fires, and in particular to a multi-dimensional cable arc fire assessment method based on digital images. Background Art

[0002] In recent years, the economy and technology have developed rapidly, and the electrification level of the whole society has been increasing. As a necessary link in the laying of circuits, cables have become the most important part of the safe operation of the people's power grid. For reasons such as aesthetics or space saving, cables are often installed in hidden spaces, underground pipe galleries and other places that are not easy to be found during the laying process. The fires caused by them are often highly destructive and difficult to locate and extinguish, causing huge losses to people's lives and property.

[0003] Among the various factors that cause cable fires, fault arcs play a decisive role. The insulation of cables may be reduced due to improper laying, external forces, insulation corrosion, high-load operation, etc., which may directly or indirectly cause fault arcs. The high temperature generated by the arc will further promote the thermal decomposition of the cable to form a cable carbonization path, causing insulation failure or directly causing a fire. At the same time, the high temperature environment of the fire will be more conducive to the maintenance and expansion of the arc, which seriously threatens the safe operation of the power system.

[0004] There are multiple stages in the process of arc fault from its generation to fire in the cable operation, and each stage has different states. At present, most of the research on its initiation process is to detect and identify the voltage, current, smoke, temperature and other parameters alone, but there is a lack of multi-dimensional information research combining high-speed digital images of arc and flame and corresponding hazard assessment methods. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a multi-dimensional cable arc fire assessment method based on digital images, to achieve full-process synchronous collection of multi-dimensional information of arc faults when the cable is energized, to establish a cable arc fire feature data set, and to evaluate and identify the degree of cable fire hazard under various types of fault arc conditions in combination with the hierarchical analysis method.

[0006] To achieve the above object, the present invention adopts the following technical solution: a multi-dimensional cable arc-induced fire assessment method based on digital images, comprising the following steps:

[0007] Step 1: Establish a multi-dimensional information synchronous acquisition system for cable fires caused by fault arcs;

[0008] Step 2: Establish a three-dimensional model of cable fire caused by fault arc;

[0009] Step 3: Conduct cable fire risk assessment under arc fault conditions.

[0010] In a preferred embodiment, in step 1: the multi-dimensional information synchronous acquisition system for cable fires caused by fault arcs includes a cable fault arc fire experimental device, a host computer, a synchronous control module, a high-speed image acquisition module and a multi-dimensional information acquisition module; when the multi-dimensional information synchronous acquisition system for cable fires caused by fault arcs is running, the host computer issues a control instruction to control the fault arc generating device connected to the cable test piece to generate a continuous fault arc; the access load and working conditions of the fault arc can be adjusted and set according to actual needs; at the same time, a control instruction is sent to the synchronous control module to synchronously trigger the high-speed digital image acquisition module and the multi-dimensional information acquisition module, and the data is transmitted to the host computer using a high-speed data acquisition card, and waveform display and processing are performed.

[0011] In a preferred embodiment, the high-speed image acquisition module includes multiple high-speed cameras, and the acquired images include: images of the complete cable ignition process, dynamic images of the cable fault arc, images of the evolution of the cable carbonization path under arc light suppression, and images of arc bead splashing.

[0012] In a preferred embodiment, the multi-dimensional information acquisition module uses a pyrolysis particle detector to monitor pyrolysis ions and a thermal convection sensor to monitor temperature, and uses a smoke sensor to monitor smoke quality and changes in concentrations of different gas components.

[0013] In a preferred embodiment, in step 2: a multi-physics field coupling method based on the FDS kernel is used to describe the changes of temperature, heat release rate, smoke concentration, etc. in the fire scene over time; FDS adopts an approximate form of the Navier-Stroker fluid dynamics equation, and the FDS model consists of a mass conservation equation, a momentum conservation equation, and an energy conservation equation;

[0014] Mass Conservation Equation

[0015]

[0016] Where ρ is the arc plasma density, which is a function of temperature; t is time; U is the arc plasma velocity vector;

[0017] Component Conservation Equation

[0018]

[0019] Where, is the mass fraction of component i; is the diffusion coefficient of component i; is the mass of component i;

[0020] Momentum Conservation Equation

[0021]

[0022] Where p is the pressure; g is the acceleration due to gravity; f is the volume force per unit mass of the fluid; is the stress tensor;

[0023] Energy Conservation Equation

[0024]

[0025] Where H is thermal enthalpy; λ is thermal conductivity;

[0026] In the setting of the pyrolysis model, the pyrolysis reaction rate of the insulating sheath is solved based on the Arrhenius equation, which is expressed as

[0027]

[0028] Where, k is the pyrolysis reaction rate; A is the pre-exponential factor; E is the activation energy; R is the ideal gas constant; T is the thermodynamic temperature;

[0029] In the solution model setting, A and E need to be obtained through thermogravimetric experiment TGA test; this experiment uses a thermogravimetric analyzer to perform thermogravimetric analysis on the cable sheath material to obtain the TG curve of the material as the temperature increases; the TG data is analyzed using the FWO method to obtain the A and E values ​​of the insulating material at different pyrolysis stages.

[0030] In a preferred embodiment, in step 3: construct a fire risk evaluation index set S = {s1, s2, s3, s4, s5}, where S represents the cable fire risk level; s1, s2, s3, s4, s5 are divided into system factors, fault arc factors, image factors, cable factors and multi-sensor factors; use the hierarchical analysis method APH to establish an evaluation index system and determine the weights of the factors affecting the fire induced by the cable under the action of the fault arc, and then combine the expert scoring results with the weight vector to form the evidence source of DS evidence fusion, and use DS evidence fusion to determine the cable fire hazard level;

[0031] The fire risk assessment results are divided into four levels: low risk, first-level risk, second-level risk, and high risk; each indicator is divided into a range, and different risk scores (0-100) are assigned to indicators in different ranges; finally, the fire level score determined by DS evidence fusion is 0-100, and the results in the range of 0-30 are considered low risk, 30-50 are first-level risks, 50-80 are second-level risks, and 80 and above are high risks.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. Build a synchronous acquisition system for cable arc fault-caused fires based on multi-angle arc digital images and multi-type sensors. The system coordinates and controls the synchronous triggering of multiple high-speed cameras, and is equipped with pyroion detectors and smoke, gas and temperature sensors to achieve synchronous acquisition of multi-dimensional physical information during the generation of arc, flame and carbonization path when a cable arc fire occurs under different energized operating conditions.

[0034] 2. Construct a dynamic three-dimensional simulation model of arc-induced cable fire based on FDS. This model uses multi-physics field coupling simulation based on the FDS kernel, combined with chemical pyrolysis and combustion reactions, and uses a variety of typical fault arcs as fire heat sources to build and calculate the three-dimensional model of arc-induced cable fire.

[0035] 3. A method for determining the electrical fire hazard level based on multi-physical information is proposed. The features of arc and cable flame images and multiple types of sensor, voltage and current data are extracted, and the corresponding data set is established. Combined with DS theory and hierarchical analysis method, the degree of cable fire hazard under various types of fault arc conditions is quantitatively evaluated and identified. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a schematic diagram of the structure of a system for synchronously collecting multi-dimensional information on cable fires caused by fault arcs in a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0037] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0038] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0039] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application; as used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or their combinations.

[0040] A multi-dimensional cable arc fire assessment method based on digital images, reference Figure 1 , including the following steps:

[0041] (1) Multi-dimensional information synchronous acquisition system for cable fires caused by arc faults

[0042] Cable fire is a complex staged process from the appearance of fault arc to the final ignition, but the critical points between stages are unclear, involving a large number of physical and chemical reactions. It includes processes such as decomposition of insulating sheath, arc bead splashing, and carbonization path growth, which contain a large amount of characteristic information. The present invention builds a cable fault arc fire multi-dimensional information acquisition system to achieve the full process of multi-dimensional data synchronization of electrical fires caused by fault arcs under different working conditions. The system consists of a cable fault arc fire experimental device, a host computer, a synchronous control module, a high-speed image acquisition module, and a multi-dimensional information acquisition module.

[0043] The high-speed image acquisition module is composed of multiple high-speed cameras, which independently undertake different types of image acquisition, including: images of the complete cable ignition process, dynamic images of cable fault arcs, images of the evolution of cable carbonization paths under arc light suppression, and images of arc bead splashing. Among them, arc light suppression is achieved by combining high-frequency laser diode emitters with narrow-band filters.

[0044] In the process from the generation of the fault arc to the triggering of the cable fire, the first stage is the pyrolysis stage: the cable insulation layer is decomposed by heat, releasing a large amount of pyrolytic ions. As the temperature continues to rise, the insulation layer begins to carbonize, and after reaching the ignition point, it begins to smolder, and finally the cable burns and causes a fire. Under the action of the high-temperature arc, the insulation layer pyrolyzes and burns, producing pyrolytic ions, smoke, and various gases such as CO, CO2, etc., accompanied by rapidly changing light and heat phenomena, forming multiple types of collectible features. The multi-dimensional information acquisition module in this system uses a pyrolytic particle detector to monitor pyrolytic ions and a thermal convection sensor to monitor temperature, and a smoke sensor to monitor the smoke quality and changes in the concentration of different gas components.

[0045] When the system is running, the host computer issues a control command to control the arc fault generator connected to the cable test piece to generate a continuous arc fault. The access load and working conditions of the arc fault can be adjusted and set according to actual needs. At the same time, the control command is sent to the synchronous control module to synchronously trigger the high-speed digital image acquisition module and the multi-dimensional information acquisition module, and the high-speed data acquisition card is used to transmit data to the host computer, and the waveform is displayed and processed.

[0046] (2) 3D model of cable fire caused by arc fault

[0047] The arc heat source of the cable fault arc in the evolution process will cause the cable insulation sheath to pyrolyze, and a large number of pyrolysis reactions will affect the calculation of the fire. The present invention considers the pyrolysis reaction and the fault arc heat source, takes the physical information collected in the experiment as input, and establishes a three-dimensional cable fire simulation model.

[0048] The common method used in the market for fire simulation is to use the multi-physics field coupling method based on the FDS kernel to describe the changes of temperature, heat release rate, smoke concentration, etc. in the fire scene over time. FDS uses the approximate form of the Navier-Stroker fluid dynamics equation. The FDS model consists of mass (component) conservation equations, momentum conservation equations, and energy conservation equations.

[0049] Mass Conservation Equation

[0050]

[0051] Where ρ is the arc plasma density, which is a function of temperature; t is time; and U is the arc plasma velocity vector.

[0052] Component Conservation Equation

[0053]

[0054] Where, is the mass fraction of component i; is the diffusion coefficient of component i; is the mass of component i.

[0055] Momentum Conservation Equation

[0056]

[0057] Where p is the pressure, g is the acceleration due to gravity, f is the volume force per unit mass of fluid, and is the stress tensor.

[0058] Energy Conservation Equation

[0059]

[0060] Where H is the thermal enthalpy and λ is the thermal conductivity.

[0061] In the setting of the pyrolysis model, the pyrolysis reaction rate of the insulating sheath is solved based on the Arrhenius equation, which is expressed as

[0062]

[0063] Where k is the pyrolysis reaction rate; A is the pre-exponential factor; E is the activation energy; R is the ideal gas constant; and T is the thermodynamic temperature.

[0064] In the solution model setting, A and E need to be obtained through thermogravimetric experiment (TGA) test. This experiment uses a thermogravimetric analyzer to perform thermogravimetric analysis on the cable sheath material to obtain the TG curve of the material as the temperature increases. By analyzing the TG data using the FWO method, the A and E values ​​of the insulation material at different pyrolysis stages can be obtained.

[0065] (3) Cable fire risk assessment method under arc fault conditions

[0066] Power cable fire risk warning is a multi-parameter and multi-factor hazard identification and risk assessment process. The present invention collects various fire-causing signals and images under different system states through multi-channel sensors and multiple high-speed cameras, and combines signal processing technology to construct a fire risk assessment index set. As shown in Table 1, the factors affecting power cable fire risk are divided into five primary factors, namely system factors, fault arc factors, cable combustion factors, and multi-sensor factors. The primary factors are further subdivided into 18 secondary factors.

[0067] Table 1

[0068]

[0069] The constructed fire risk evaluation index set is S = {s1, s2, s3, s4, s5}, where S represents the cable fire risk level; s1, s2, s3, s4, s5 are divided into system factors, fault arc factors, image factors, cable factors and multi-sensor factors. The analytic hierarchy process (APH) is used to establish an evaluation index system and determine the weights of the factors affecting the fire induced by the cable under the action of the fault arc. Then, the expert scoring results are combined with the weight vector to form the evidence source of DS evidence fusion, and DS evidence fusion is used to determine the cable fire hazard level.

[0070] In order to further classify the fire warning signals so that relevant personnel can take appropriate measures to avoid or respond to the occurrence of fires, the fire risk assessment results are divided into four levels: low risk, first-level risk, second-level risk, and high risk. In order to quantify the results of fire warning, each indicator is divided into ranges, and different risk scores (0-100) are assigned to indicators in different ranges. Finally, the fire level score determined by DS evidence fusion is 0-100, and the results in the range of 0-30 are considered low risk, 30-50 are first-level risks, 50-80 are second-level risks, and 80 and above are high risks.

Claims

1. A multi-dimensional cable arc fire assessment method based on digital images, characterized in that: The following steps are involved: Step 1: Establish a multi-dimensional information synchronous acquisition system for cable fires caused by fault arcs; Step 2: Establish a three-dimensional model of cable fire caused by fault arc; Step 3: Conduct cable fire risk assessment under arc fault conditions.

2. A multi-dimensional cable arc fire assessment method based on digital images according to claim 1, characterized in that: In the step 1, the multi-dimensional information synchronous acquisition system for cable fires caused by fault arcs includes a cable fault arc fire experimental device, a host computer, a synchronous control module, a high-speed image acquisition module and a multi-dimensional information acquisition module; when the multi-dimensional information synchronous acquisition system for cable fires caused by fault arcs is in operation, the host computer issues a control instruction to control the fault arc generating device connected to the cable test piece to generate a continuous fault arc; the access load and working conditions of the fault arc can be adjusted and set according to actual needs; at the same time, the control instruction is sent to the synchronous control module to synchronously trigger the high-speed digital image acquisition module and the multi-dimensional information acquisition module, and the high-speed data acquisition card is used to transmit data to the host computer, and the waveform is displayed and processed.

3. The multi-dimensional cable arc fire assessment method based on digital images according to claim 2 is characterized in that: The high-speed image acquisition module includes multiple high-speed cameras, and the acquired images include: images of the complete cable ignition process, dynamic images of cable fault arcs, images of cable carbonization path evolution under arc light suppression, and images of arc bead splashing.

4. The multi-dimensional cable arc fire assessment method based on digital images according to claim 2 is characterized in that: The multi-dimensional information acquisition module uses a pyrolysis particle detector to monitor pyrolysis ions and a thermal convection sensor to monitor temperature, and uses a smoke sensor to monitor smoke quality and changes in concentrations of different gas components.

5. The multi-dimensional cable arc fire assessment method based on digital images according to claim 1 is characterized in that: In the step 2: a multi-physics field coupling method based on the FDS kernel is used to describe the changes of temperature, heat release rate, smoke concentration, etc. in the fire scene over time; FDS adopts an approximate form of the Navier-Stroker fluid dynamics equation, and the FDS model consists of a mass conservation equation, a momentum conservation equation, and an energy conservation equation; Mass Conservation Equation Where ρ is the arc plasma density, which is a function of temperature; t is time; U is the arc plasma velocity vector; Component Conservation Equation In the formula, ω i is the mass fraction of component i; D i is the diffusion coefficient of component i; m i is the mass of component i; Momentum Conservation Equation Where p is pressure; g is gravitational acceleration; f is the volume force per unit mass of fluid; τ is the stress tensor; Energy Conservation Equation Where H is thermal enthalpy; λ is thermal conductivity; In the setting of the pyrolysis model, the pyrolysis reaction rate of the insulating sheath is solved based on the Arrhenius equation, which is expressed as Where, k is the pyrolysis reaction rate; A is the pre-exponential factor; E is the activation energy; R is the ideal gas constant; T is the thermodynamic temperature; In the solution model setting, A and E need to be obtained through thermogravimetric experiment TGA test; this experiment uses a thermogravimetric analyzer to perform thermogravimetric analysis on the cable sheath material to obtain the TG curve of the material as the temperature increases; the TG data is analyzed using the FWO method to obtain the A and E values ​​of the insulating material at different pyrolysis stages.

6. The multi-dimensional cable arc fire assessment method based on digital images according to claim 1 is characterized in that: In the step 3: construct a fire risk assessment index set S = {s1, s2, s3, s4, s5}, where S represents the cable fire risk level; s1, s2, s3, s4, s5 are divided into system factors, fault arc factors, image factors, cable factors and multi-sensor factors; The analytic hierarchy process (APH) was used to establish an evaluation index system and determine the weights of the factors affecting the fire induced by the cable under the action of the fault arc. The expert scoring results were combined with the weight vector to form the evidence source of DS evidence fusion, and the DS evidence fusion was used to determine the cable fire hazard level. The fire risk assessment results are divided into four levels: low risk, first-level risk, second-level risk, and high risk; each indicator is divided into a range, and different risk scores (0-100) are assigned to indicators in different ranges; finally, the fire level score determined by DS evidence fusion is 0-100, and the results in the range of 0-30 are considered low risk, 30-50 are first-level risks, 50-80 are second-level risks, and 80 and above are high risks.

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