Power distribution switch early fault detection method and device, computer equipment and medium

Abstract

The invention relates to the technical field of artificial intelligence, and discloses a power distribution switch early fault detection method and device, computer equipment and a medium, and the method comprises the steps: building an air-water initial simulation model; acquiring a crack parameter, a potential difference and a rainwater parameter of a to-be-detected power distribution switch, and setting parameters of the initial two-phase simulation model to obtain a target simulation model; detecting actual arc parameters of the power distribution switch; comparing the predicted arc parameter with the predicted arc parameter; and judging whether the distribution switch has an early fault or not according to a comparison result. The beneficial effects of the invention are that the method can timely recognize and process problems which may cause serious power faults through continuous monitoring and accurate analysis of the power distribution switch, and can implement more targeted maintenance measures through detailed analysis of crack expansion and discharge behaviors, thereby improving the maintenance efficiency. Therefore, the service life of the power distribution switch and related power equipment is prolonged.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to early fault detection of a power distribution switch. Background Art

[0002] Distribution switches have high mechanical strength, chemical stability, excellent insulation properties and strong corrosion resistance, and have been widely used in distribution networks. When the distribution switch is fired, the quartz in the material will transform from α-quartz to β-quartz during the cooling process, and the volume will decrease by 2%. This will cause strain and form many microcracks in the porcelain body. These microcracks will grow larger over time under the action of electrical and mechanical stress, and eventually lead to complete radial cracks. In the 10kV distribution network, commonly used distribution switches include pin-type distribution switches, suspended distribution switches, pillar distribution switches, cross-arm distribution switches, etc. Among them, the pin-type distribution switch lacks an iron cap, and the porcelain between the electrodes (wires and needles) is relatively thin. Therefore, rainwater can easily flow into the cracks on rainy days, reducing the insulation strength, resulting in drainage in the cracks. The narrow internal space of the crack allows the discharge to extinguish itself through the evaporation of water caused by heat, showing a self-clearing characteristic. This type of fault is referred to as early failure (PIIF) of the distribution switch in the present invention.

[0003] At present, the detection of early faults of distribution switches is mainly through manual inspection, which is time-consuming and labor-intensive, and there are also safety issues for the inspectors. Summary of the invention

[0004] Based on this, it is necessary to address the existing problem of early fault detection of distribution switches and propose an early fault detection method for distribution switches.

[0005] A method for detecting early faults of a power distribution switch, the method comprising:

[0006] Establish an initial air-water simulation model;

[0007] Acquire crack parameters, potential difference and rain parameters of the power distribution switch to be tested, and set parameters in the crack of the initial simulation model according to the crack parameters, set the potentials at the top and bottom of the initial simulation model according to the potential difference, and set the phase field variables of the initial two-phase simulation model according to the rain parameters to obtain a target simulation model;

[0008] Analyzing predicted arc parameters at the crack parameters and the potential difference according to the target simulation model;

[0009] detecting actual arc parameters of the power distribution switch;

[0010] comparing the predicted arc parameter with the predicted arc parameter;

[0011] It is determined whether an early failure occurs in the power distribution switch according to the comparison result.

[0012] Further, the step of analyzing the predicted arc parameters based on the crack parameters and the potential difference according to the target simulation model includes:

[0013] According to the target simulation model, analyzing a first relationship between arc voltage and current and a second relationship between arc conductance and arc resistance during arc burning at the crack;

[0014] The predicted arc parameters are obtained by calculating the arc energy dissipation data according to the first relationship and the second relationship.

[0015] Furthermore, the step of setting the phase field variables of the initial two-phase simulation model according to the rainwater parameters comprises:

[0016] The water-gas two-phase flow inside the fracture is simulated by the Cahn-Hilliard equation and the Navier-Stokes equation.

[0017] Furthermore, the step of simulating the water-gas two-phase flow inside the fracture by using the Cahn-Hilliard equation and the Navier-Stokes equation includes:

[0018] By introducing the phase field variable φ, different phase regions and transition regions between different phases are identified. The formula is:

[0019]

[0020] in, represents the partial derivative with respect to time t, which is used to describe the rate of change of φ with time; represents the convection term, u represents the velocity of the fluid (m / s), represents the gradient of φ, and the dot product represents the rate of change of φ in the velocity direction; represents the diffusion term, · Indicates divergence, used to describe The degree of divergence in space; coefficient represents the controlled diffusion rate, γ represents the mobility (m3·s / kg), λ represents the mixing energy density (N), ε represents the interface thickness parameter (m), and ψ represents the phase field auxiliary variable;

[0021] At the gas-liquid interface, the density ρ is smoothly varied across the two-phase interface. BD and viscosity μ BD Define it to mean:

[0022]

[0023] Among them, ρw represents the density of water (kg / m3), ρ air Indicates air density (kg / m3), μ w Indicates the viscosity of water (Pa·s), μ air Indicates air viscosity (Pa·s);

[0024] The two-phase flow Navier-Stokes equation and continuity equation are expressed as:

[0025]

[0026]

[0027] Where ρ represents the fluid density (kg / m3), μ represents the dynamic viscosity (Pa·s), and u represents the velocity (m / s). represents the velocity gradient, represents the tensor transpose of the velocity gradient, p represents the flow inlet pressure (Pa), I represents the unit vector, and F st represents the interfacial tension of the two-phase fluid (N / m), g (m / s2) represents the gravity vector, and the formula is Indicates the incompressibility of the fluid;

[0028] Convection and diffusion in the interface region will cause changes in the interface free energy, which will increase the interfacial tension F st Defined as:

[0029] Furthermore, before the step of analyzing the crack parameters and the potential difference according to the target simulation model to predict arc parameters, the method further includes:

[0030] Setting a breakdown threshold according to the potential difference and material parameters of the power distribution switch;

[0031] Obtaining the maximum electric field intensity in the crack region of the target simulation model;

[0032] Determining whether the maximum electric field strength is greater than the breakdown threshold;

[0033] If the maximum electric field strength is greater than the breakdown threshold, the step of analyzing the predicted arc parameters based on the crack parameters and the potential difference and the predicted air characteristics after discharge self-clearing according to the target simulation model is performed.

[0034] Further, the step of comparing the predicted arc parameter with the predicted arc parameter comprises:

[0035] Acquire a minimum threshold of arc existence duration according to the predicted arc parameter;

[0036] Determine the actual arc duration in the actual arc parameters;

[0037] If the actual existence duration is less than or equal to the minimum duration threshold, it is determined that the distribution switch has no early failure; if the actual existence duration is greater than the minimum duration threshold, it is determined that the distribution switch has an early failure.

[0038] Further, after the step of comparing the predicted arc parameter with the predicted arc parameter, the method further includes:

[0039] Detecting whether the distribution switch re-ignites within a set time after the arc discharge is extinguished;

[0040] If the re-ignition phenomenon occurs, it is determined that the distribution switch has an early failure.

[0041] A distribution switch early fault detection system, the system comprising:

[0042] Establishing module for establishing initial air-water simulation model;

[0043] An acquisition module, used to acquire crack parameters, potential difference and rain parameters of the power distribution switch to be detected, and to set parameters in the crack of the initial simulation model according to the crack parameters, to set the potentials at the top and bottom of the initial simulation model according to the potential difference, and to set the phase field variables of the initial two-phase simulation model according to the rain parameters, so as to obtain a target simulation model;

[0044] An analysis module, configured to analyze predicted arc parameters based on the crack parameters and the potential difference according to the target simulation model;

[0045] A detection module, used for detecting actual arc parameters of the power distribution switch;

[0046] A comparison module, configured to compare the predicted arc parameter with the predicted arc parameter;

[0047] The determination module is used to determine whether an early failure occurs in the power distribution switch according to the comparison result.

[0048] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the following steps:

[0049] Establish an initial air-water simulation model;

[0050] Acquire crack parameters, potential difference and rain parameters of the power distribution switch to be tested, and set parameters in the crack of the initial simulation model according to the crack parameters, set the potentials at the top and bottom of the initial simulation model according to the potential difference, and set the phase field variables of the initial two-phase simulation model according to the rain parameters to obtain a target simulation model;

[0051] Analyzing predicted arc parameters at the crack parameters and the potential difference according to the target simulation model;

[0052] detecting actual arc parameters of the power distribution switch;

[0053] comparing the predicted arc parameter with the predicted arc parameter;

[0054] It is determined whether an early failure occurs in the power distribution switch according to the comparison result.

[0055] A computer-readable storage medium stores a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0056] Establish an initial air-water simulation model;

[0057] Acquire crack parameters, potential difference and rain parameters of the power distribution switch to be tested, and set parameters in the crack of the initial simulation model according to the crack parameters, set the potentials at the top and bottom of the initial simulation model according to the potential difference, and set the phase field variables of the initial two-phase simulation model according to the rain parameters to obtain a target simulation model;

[0058] Analyzing predicted arc parameters at the crack parameters and the potential difference according to the target simulation model;

[0059] detecting actual arc parameters of the power distribution switch;

[0060] comparing the predicted arc parameter with the predicted arc parameter;

[0061] It is determined whether an early failure occurs in the power distribution switch according to the comparison result.

[0062] Beneficial effects of the invention: Through continuous monitoring and precise analysis of the distribution switch, the invention can timely identify and deal with problems that may lead to serious power failures. Through detailed analysis of crack expansion and discharge behavior, more targeted maintenance measures can be implemented, thereby extending the service life of the distribution switch and related power equipment. The system's predictive maintenance model reduces unnecessary comprehensive inspection and maintenance costs, allowing resources to be more concentrated on key parts that may fail. This resource optimization not only reduces direct maintenance costs, but also helps reduce downtime costs caused by sudden failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.

[0064] in:

[0065] Figure 1 A diagram showing an application environment of a method for detecting early faults of a power distribution switch in an embodiment;

[0066] Figure 2 A flow chart of early fault detection of a power distribution switch in one embodiment;

[0067] Figure 3 A diagram showing simulation results of a method for detecting early faults of a power distribution switch in an embodiment;

[0068] Figure 4 A schematic diagram of voltage-electric field changes in a method for detecting early faults of a power distribution switch in an embodiment;

[0069] Figure 5 A schematic diagram of Parc-Rarc variation of a method for detecting early faults of a power distribution switch in an embodiment;

[0070] Figure 6 is a structural block diagram of a distribution switch early fault detection system in one embodiment;

[0071] Figure 7 FIG. 4 is a structural block diagram of a computer device in one embodiment. DETAILED DESCRIPTION

[0072] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0073] Figure 1 FIG. 1 is a diagram of an application environment for early fault detection of a power distribution switch in an embodiment. Figure 1The distribution switch early fault detection method is applied to the distribution switch early fault detection system. The distribution switch early fault detection system includes a terminal 110 and a server 120. The terminal 110 and the server 120 are connected through a network. The terminal 110 can be a desktop terminal or a mobile terminal. The mobile terminal can be at least one of a mobile phone, a tablet computer, a laptop computer, etc. The server 120 can be implemented as an independent server or a server cluster composed of multiple servers. The terminal 110 is used to obtain actual arc parameters, and the server 120 is used to establish a simulation model.

[0074] like Figure 2 As shown, in one embodiment, a method for detecting early faults of a power distribution switch is provided. The method can be applied to both a terminal and a server. This embodiment is illustrated by applying the method to a server. The method for detecting early faults of a power distribution switch specifically includes the following steps:

[0075] S1: Establish an initial air-water simulation model;

[0076] S2: Obtain crack parameters, potential difference and rain parameters of the power distribution switch to be detected, and set parameters in the crack of the initial simulation model according to the crack parameters, set the potentials at the top and bottom of the initial simulation model according to the potential difference, and set the phase field variables of the initial two-phase simulation model according to the rain parameters to obtain a target simulation model;

[0077] S3: analyzing the predicted arc parameters based on the crack parameters and the potential difference according to the target simulation model;

[0078] S4: Detecting actual arc parameters of the power distribution switch;

[0079] S5: comparing the predicted arc parameter with the predicted arc parameter;

[0080] S6: Determine whether the power distribution switch has an early failure according to the comparison result.

[0081] As described in step S1 above, due to adverse conditions such as overvoltage, mechanical stress and surface contamination, cracks may appear in the pin-type distribution switch. These cracks are highly concealed and difficult to observe with the naked eye. They are usually between 0.1 and 0.2 mm. Under dry weather conditions, the crack distribution switch can still maintain sufficient insulation capacity, and the normal power frequency voltage of the system will not cause discharge. However, under rainy conditions, rainwater will flow into the crack from top to bottom, gradually shortening the air gap. At a certain moment, the electric field strength reaches the breakdown threshold, triggering discharge. The water entering the crack evaporates and is discharged from the crack due to the thermal effect of the fault current, causing the arc to prolong and extinguish when the current passes through zero. A simulation model of water-gas two-phase displacement in the slit interface was constructed.

[0082] As described in step S2, the crack parameters, potential difference and rain parameters of the distribution switch to be detected are obtained, and the parameters in the crack of the initial simulation model are set according to the crack parameters, the potentials at the top and bottom of the initial simulation model are set according to the potential difference, and the phase field variables of the initial two-phase simulation model are set according to the rain parameters to obtain the target simulation model. That is, a proportional distribution switch model is established according to the corresponding distribution switch, the geometric shape, position, width, depth of the crack and the electrical characteristics of the insulator to ensure that the model reflects the physical and electrical characteristics of the actual crack distribution switch.

[0083] As described in the above step S3, the predicted arc parameters based on the crack parameters and the potential difference are analyzed according to the target simulation model. The specific calculation method is not limited, and the main purpose is to obtain the corresponding minimum time threshold of the arc existence duration.

[0084] As described in the above steps S4-S6, the actual arc parameters of the distribution switch are detected and the predicted arc parameters are compared with the predicted arc parameters, and whether the distribution switch has an early failure is determined based on the comparison result. Through continuous monitoring and precise analysis of the distribution switch, problems that may cause serious power failures can be identified and handled in a timely manner. Through detailed analysis of crack expansion and discharge behavior, more targeted maintenance measures can be implemented, thereby extending the service life of the distribution switch and related power equipment. The system's predictive maintenance model reduces unnecessary comprehensive inspection and maintenance costs, allowing resources to be more concentrated on key parts that may fail. This resource optimization not only reduces direct maintenance costs, but also helps reduce downtime costs caused by sudden failures.

[0085] In one embodiment, the step S3 of analyzing the predicted arc parameters based on the crack parameters and the potential difference according to the target simulation model comprises:

[0086] S301: Analyzing, according to the target simulation model, a first relationship between arc voltage and current during arc burning at the crack and a second relationship between the arc voltage and current and arc conductance and arc resistance;

[0087] S302: Obtain the predicted arc parameters based on the arc energy dissipation data calculated according to the first relationship and the second relationship.

[0088] As described in the above steps S301-S302, in the simulation, the phase field method is combined with the Navier-Stokes equations to construct a water-gas two-phase displacement simulation model in the slit interface.

[0089] The phase field method introduces the phase field variable φ to identify different phase regions and transition regions between different phases. The Cahn-Hilliard equation (Cahn-Hilliard equation is a nonlinear differential equation used to describe multiphase systems, which can be used to simulate phase change processes in multiphase systems) is a convection-diffusion equation used to control the evolution of interface profiles. This equation shows that the change in the phase field variable φ over time is balanced with the change under the influence of convection and diffusion:

[0090]

[0091]

[0092] in, is the partial derivative symbol, u represents the velocity of the fluid (m / s), and γ represents the mobility (m 3 ·s / kg), λ represents the mixing energy density (N), ε is the interface thickness parameter (m), ψ represents the phase field auxiliary variable, Is an operation symbol.

[0093] Then at the gas-liquid interface, the density ρ that varies smoothly across the two-phase interface is expressed as BD (kg / m 3 ) and viscosity μ BD (Pa·s) is defined as:

[0094]

[0095] The Navier-Stokes equations are used to describe the mass and momentum transfer characteristics of incompressible fluids. Considering the influence of interfacial tension, the two-phase flow Navier-Stokes equations and continuity equations can be expressed as:

[0096]

[0097]

[0098] Where ρ represents the density (kg / m 3 ), μ represents dynamic viscosity (Pa·s), u represents velocity (m / s), p represents inlet pressure (Pa), I represents unit vector, F st represents the interfacial tension of the two-phase fluid (N / m), and g represents the gravity vector.

[0099] In the phase field method, convection and diffusion in the interface region will cause changes in the interface free energy, which can be used to calculate the interfacial tension F. st Defined as:

[0100]

[0101] At the same time, the size of the distribution switch is much smaller than the wavelength of the 50Hz power frequency electromagnetic wave. The electrostatic field theory can be used to analyze the electric field inside the crack of the distribution switch. The electric field E and the displacement field D are obtained through the potential:

[0102]

[0103]

[0104] Where ε0 is the dielectric constant of free space, ε r represents the relative dielectric constant, ρ Q represents the space charge density.

[0105] In the simulation, the bottom plane of the model is set to ground and the potential of the top plane is set to 8165×sin(100πt). The results are as follows: Figure 4 As shown in the figure. As time goes by, water gradually flows into the crack from top to bottom under the action of gravity and surface tension. Due to the different roughness of different areas on the crack surface, the lengths of different water flow paths are also different. This causes the water-air interface to not move horizontally downward, as shown at 25ms, 45ms, etc. But overall, the water-air interface will move steadily downward, and the length of the air gap will gradually decrease. In addition, under the influence of the power frequency voltage, the distribution of the electric field in the crack will also change over time.

[0106] exist Figure 4 The high electric field intensity area is mainly located near the water-air interface. Starting from 0ms, the maximum electric field intensity at each moment when water flows into the crack is recorded at intervals of 0.1ms. The curve is as follows: Figure 4 shown.

[0107] It should be noted that under the action of power frequency voltage, if the positions of the two electrodes and the properties of the dielectric between them remain unchanged, the maximum electric field strength between the electrodes will change with the voltage in each half cycle, showing a trend of first increasing and then decreasing. Therefore, if the maximum electric field strength exceeds the dielectric breakdown strength, the discharge will occur before the voltage reaches the peak value. Otherwise, the electric field strength will decrease as the voltage decreases, and the discharge will not occur.

[0108] However, for crack distribution switches operating on rainy days, the length of the air gap will be shortened by the water flowing into the crack. This means that the properties of the dielectric between the two electrodes are also changing over time, and the peak value of the maximum electric field strength may occur during the rising or falling phase of the voltage within half a power frequency cycle, such as Figure 4 Therefore, as water flows into the cracks, discharge will occur not only during the voltage rising phase, but also during the voltage falling phase after the voltage reaches the peak.

[0109] According to the initial arc conditions obtained from electric field simulation and discharge initiation analysis, the relationship between arc voltage and current during arc burning and its influence on arc conductance and arc resistance are analyzed.

[0110] During the arc burning process, the arc voltage and current provide energy for the arc. Part of the energy is dissipated into the surrounding environment through convection, conduction and radiation, while the remaining energy is used to maintain the plasma state of the arc. This process can be expressed by the following heat balance equation:

[0111]

[0112] Where d is the derivative symbol, Q S Indicates arc energy, P loss represents the dissipated power, u and i represent the arc voltage and current respectively. Let g represent the arc conductance, then the equation can be transformed into:

[0113]

[0114]

[0115] If the order Then we get the classic black box arc model:

[0116]

[0117] ln is a logarithmic function, the time constant τ and the dissipated power P loss It can be expressed in different forms according to different assumptions. For example, Mayr, Schwarz, Cybernetic, etc. These models have achieved good results in arc simulation. Taking the Cybernic arc model as an example, P arc and R arc The schematic diagram of the changing trend is as follows Figure 5 shown.

[0118] As the power supplied to the arc by Parc decreases, the energy Q required to maintain the arc burning S This results in a decrease in arc temperature and diameter, resulting in an arc resistance R arc Increases rapidly. When P arc When it decreases to its minimum value, R arc It will reach its maximum value at a faster speed. This is the main reason for the "zero shoulder" in the arc current waveform.

[0119] After the air gap in the crack breaks down, the current will flow through the water area and the arc area. Since the arc length is less than 2cm, the resistance is low during the intense burning process. The conductivity of rainwater ranges from tens of Ω·m to hundreds of Ω·m. Combined with the calculation formula of resistance R water =ρw ·L w / S w , it can be inferred that when the air gap in the crack is just broken through, R water Much larger than R arc .

[0120] According to the above analysis, when the power input to the crack decreases, R arc However, the thermal effect of the current causes the rainwater in the cracks to heat up and evaporate, thus shortening the length of the water area L w At the same time, due to the limitation of the crack wall, the cross-sectional area S of the water area w This will result in R water Therefore, before the power is reduced to a certain level, the resistance change between the wire and the iron foot is mainly caused by R water The decrease of the dominant, which means that R water +R arc Will follow P arc 's decrease but first decreases and then increases.

[0121] According to the arc energy dissipation data calculated during the arc process, the characteristics of arc energy dissipation and high-temperature air after discharge self-clearing are analyzed.

[0122] For an arc under open space conditions, the energy dissipated by convection and radiation will cause thermal ionization of the air around the arc. The ionized air will be converted into part of the arc plasma, which is visually manifested as an increase in the arc column diameter. This phenomenon makes it easy for the arc to reignite after the current passes zero due to the presence of residual high-temperature air. However, the size of the air region within the crack is limited, and most of the energy dissipated by the arc is absorbed by the crack surface. Compared with the arc in the open space, the arc in the crack has less residual high-temperature air after the current passes zero, making it difficult to reignite.

[0123] In addition, as mentioned above, the water flowing into the crack will evaporate under the influence of the thermal effect of the current. The energy required for this evaporation process is W lat It can be calculated using the following equation:

[0124] W lat =ρ0V[c(T2-T1)+r]

[0125] Where ρ0=998kg·m 3 Represents the density of water, V(m 3 ) represents the volume of water, c = 4.18 kJ / (kg·K) is the specific heat capacity of water, T2 = 373 K represents the boiling point of water under standard atmospheric pressure, T1 = 293 K represents the initial temperature of water, and r = 2256 kJ / kg represents the latent heat of evaporation of water.

[0126] In one embodiment, the step S2 of setting the phase field variables of the initial two-phase simulation model according to the rainwater parameters comprises:

[0127] S201: The water-gas two-phase flow inside the fracture is simulated using the Cahn-Hilliard equation and the Navier-Stokes equation.

[0128] In one embodiment, the step S201 of simulating the water-gas two-phase flow inside the fracture by using the Cahn-Hilliard equation and the Navier-Stokes equation includes:

[0129] By introducing the phase field variable φ, different phase regions and transition regions between different phases are identified. The formula is:

[0130]

[0131] in, represents the partial derivative with respect to time t, which is used to describe the rate of change of φ with time; represents the convection term, u represents the velocity of the fluid (m / s), represents the gradient of φ, and the dot product represents the rate of change of φ in the velocity direction; represents the diffusion term, · Indicates divergence, used to describe The degree of divergence in space; coefficient represents the controlled diffusion rate, γ represents the mobility (m3·s / kg), λ represents the mixing energy density (N), ε represents the interface thickness parameter (m), and ψ represents the phase field auxiliary variable;

[0132] At the gas-liquid interface, the density ρ is smoothly varied across the two-phase interface. BD and viscosity μ BD Define it to mean:

[0133]

[0134] Among them, ρ w represents the density of water (kg / m3), ρ air Indicates air density (kg / m3), μ w Indicates the viscosity of water (Pa·s), μ air Indicates air viscosity (Pa·s);

[0135] The two-phase flow Navier-Stokes equation and continuity equation are expressed as:

[0136]

[0137]

[0138] Where ρ represents the fluid density (kg / m3), μ represents the dynamic viscosity (Pa·s), and u represents the velocity (m / s). represents the velocity gradient, represents the tensor transpose of the velocity gradient, p represents the flow inlet pressure (Pa), I represents the unit vector, and F st represents the interfacial tension of the two-phase fluid (N / m), g (m / s2) represents the gravity vector, and the formula is Indicates the incompressibility of the fluid;

[0139] Convection and diffusion in the interface region will cause changes in the interface free energy, which will increase the interfacial tension F st Defined as:

[0140]

[0141] In one embodiment, before the step S3 of analyzing the crack parameters and the potential difference according to the target simulation model to predict arc parameters, the method further includes:

[0142] S301: Setting a breakdown threshold according to the potential difference and material parameters of the power distribution switch;

[0143] S302: Obtaining the maximum electric field intensity in the crack region in the target simulation model;

[0144] S303: Determine whether the maximum electric field strength is greater than the breakdown threshold;

[0145] S304: If the maximum electric field strength is greater than the breakdown threshold, executing the step of analyzing the predicted arc parameters based on the crack parameters and the potential difference and the predicted air characteristics after discharge self-clearing according to the target simulation model.

[0146] As described in the above steps S301-S304, the breakdown threshold E of the dielectric is set. X , and compare the maximum electric field strength E in the crack area max Whether it exceeds the threshold E x , at any time, if E max More than E x , it is predicted that the discharge will occur before the voltage reaches the peak value; if E max Cannot exceed E x , the electric field strength will decrease as the voltage decreases, and discharge will not occur. Therefore, if the maximum electric field strength is greater than the breakdown threshold, the step of analyzing the predicted arc parameters based on the crack parameters and the potential difference and the predicted air characteristics after discharge self-clearing according to the target simulation model is performed, otherwise, no arc phenomenon will occur and no subsequent detection is required.

[0147] In one embodiment, the step S5 of comparing the predicted arc parameter with the predicted arc parameter comprises:

[0148] S501: Obtaining a minimum threshold of arc duration according to the predicted arc parameters;

[0149] S502: Determine the actual arc duration in the actual arc parameters;

[0150] S503: If the actual existence duration is less than or equal to the minimum duration threshold, it is determined that the distribution switch has no early failure; if the actual existence duration is greater than the minimum duration threshold, it is determined that the distribution switch has an early failure.

[0151] As described in the above steps S501-S503, when an arc is detected in the crack of the distribution switch and the duration is less than the minimum time threshold t min When the arc is triggered and extinguished due to the high local electric field intensity, there is a self-processing process, and it is determined that no early fault has occurred because this degree of fault is allowed.

[0152] In one embodiment, after the step S5 of comparing the predicted arc parameter with the predicted arc parameter, the method further comprises:

[0153] S601: Detecting whether the distribution switch re-ignites within a set time after the arc discharge is extinguished;

[0154] S602: If the reignition phenomenon occurs, it is determined that the power distribution switch has an early failure.

[0155] As described in the above steps S601-S602, if air is left after the arc burns and the arc can be reignited within a short time after discharge, it indicates that there is a continuous high electric field strength and unstable dielectric conditions inside the crack, that is, the distribution switch is aging, so it is considered an early fault. When the water in the crack evaporates due to the thermal effect of the current, and the calculated water evaporation energy exceeds the threshold value W min-lat When , it is judged that the moisture in the crack is reduced, and according to the inverse proportional relationship between the dielectric resistance and the moisture storage, it is judged that the dielectric resistance in the crack is increased.

[0156] Beneficial effects of the invention: Through continuous monitoring and precise analysis of the distribution switch, the invention can timely identify and deal with problems that may lead to serious power failures. Through detailed analysis of crack expansion and discharge behavior, more targeted maintenance measures can be implemented, thereby extending the service life of the distribution switch and related power equipment. The system's predictive maintenance model reduces unnecessary comprehensive inspection and maintenance costs, allowing resources to be more concentrated on key parts that may fail. This resource optimization not only reduces direct maintenance costs, but also helps reduce downtime costs caused by sudden failures.

[0157] Reference Figure 6 The present invention also provides a distribution switch early fault detection distribution switch early fault detection system, the system comprising:

[0158] Establishing module 902, for establishing an air-water initial simulation model;

[0159] An acquisition module 904 is used to acquire crack parameters, potential difference and rain parameters of the power distribution switch to be detected, and to set parameters in the crack of the initial simulation model according to the crack parameters, to set the potentials at the top and bottom of the initial simulation model according to the potential difference, and to set the phase field variables of the initial two-phase simulation model according to the rain parameters, so as to obtain a target simulation model;

[0160] An analysis module 906 is used to analyze the predicted arc parameters based on the crack parameters and the potential difference according to the target simulation model;

[0161] A detection module 908, configured to detect actual arc parameters of the power distribution switch;

[0162] A comparison module 910, configured to compare the predicted arc parameter with the predicted arc parameter;

[0163] The determination module 912 is used to determine whether the power distribution switch has an early failure according to the comparison result.

[0164] It should be noted that other modules of the distribution switch early fault detection system of the present invention and the functions of each module correspond one-to-one with the distribution switch early fault detection method, and will not be repeated here.

[0165] Figure 7 FIG. 1 shows an internal structure diagram of a computer device in an embodiment. The computer device may be a terminal or a server. Figure 7As shown, the computer device includes a processor, a memory and a network interface connected via a system bus. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program. When the computer program is executed by the processor, the processor may implement the early fault detection method for the distribution switch. The internal memory may also store a computer program. When the computer program is executed by the processor, the processor may implement the early fault detection method for the distribution switch. Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0166] In one embodiment, a computer device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the following steps:

[0167] Establish an initial air-water simulation model;

[0168] Acquire crack parameters, potential difference and rain parameters of the power distribution switch to be tested, and set parameters in the crack of the initial simulation model according to the crack parameters, set the potentials at the top and bottom of the initial simulation model according to the potential difference, and set the phase field variables of the initial two-phase simulation model according to the rain parameters to obtain a target simulation model;

[0169] Analyzing predicted arc parameters at the crack parameters and the potential difference according to the target simulation model;

[0170] detecting actual arc parameters of the power distribution switch;

[0171] comparing the predicted arc parameter with the predicted arc parameter;

[0172] It is determined whether an early failure occurs in the power distribution switch according to the comparison result.

[0173] Through continuous monitoring and precise analysis of distribution switches, the present invention can promptly identify and address problems that may lead to serious power failures. Through detailed analysis of crack expansion and discharge behavior, more targeted maintenance measures can be implemented, thereby extending the service life of distribution switches and related power equipment.

[0174] In one embodiment, a computer-readable storage medium is provided, storing a computer program, wherein when the computer program is executed by a processor, the processor performs the following steps:

[0175] Establish an initial air-water simulation model;

[0176] Acquire crack parameters, potential difference and rain parameters of the power distribution switch to be tested, and set parameters in the crack of the initial simulation model according to the crack parameters, set the potentials at the top and bottom of the initial simulation model according to the potential difference, and set the phase field variables of the initial two-phase simulation model according to the rain parameters to obtain a target simulation model;

[0177] Analyzing predicted arc parameters at the crack parameters and the potential difference according to the target simulation model;

[0178] detecting actual arc parameters of the power distribution switch;

[0179] comparing the predicted arc parameter with the predicted arc parameter;

[0180] It is determined whether an early failure occurs in the power distribution switch according to the comparison result.

[0181] Through continuous monitoring and precise analysis of distribution switches, the present invention can promptly identify and address problems that may lead to serious power failures. Through detailed analysis of crack expansion and discharge behavior, more targeted maintenance measures can be implemented, thereby extending the service life of distribution switches and related power equipment.

[0182] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0183] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0184] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for detecting early faults of a power distribution switch, characterized in that: The method comprises: Establish an initial air-water simulation model; Acquire crack parameters, potential difference and rain parameters of the power distribution switch to be tested, and set parameters in the crack of the initial simulation model according to the crack parameters, set the potentials at the top and bottom of the initial simulation model according to the potential difference, and set the phase field variables of the initial two-phase simulation model according to the rain parameters to obtain a target simulation model; Analyzing predicted arc parameters at the crack parameters and the potential difference according to the target simulation model; detecting actual arc parameters of the power distribution switch; comparing the predicted arc parameter with the predicted arc parameter; It is determined whether an early failure occurs in the power distribution switch according to the comparison result.

2. The method for early fault detection of a power distribution switch according to claim 1, characterized in that: The step of analyzing the predicted arc parameters based on the crack parameters and the potential difference according to the target simulation model comprises: According to the target simulation model, analyzing a first relationship between arc voltage and current and a second relationship between arc conductance and arc resistance during arc burning at the crack; The predicted arc parameters are obtained by calculating the arc energy dissipation data according to the first relationship and the second relationship.

3. The method for early fault detection of a power distribution switch according to claim 1, characterized in that: The step of setting the phase field variables of the initial two-phase simulation model according to the rainwater parameters comprises: The water-gas two-phase flow inside the fracture is simulated by the Cahn-Hilliard equation and the Navier-Stokes equation.

4. The method for early fault detection of a power distribution switch according to claim 3, characterized in that: The step of simulating the water-gas two-phase flow inside the fracture by using the Cahn-Hilliard equation and the Navier-Stokes equation includes: By introducing the phase field variable φ, different phase regions and transition regions between different phases are identified. The formula is: in, represents the partial derivative with respect to time t, which is used to describe the rate of change of φ with time; represents the convection term, u represents the velocity of the fluid (m / s), represents the gradient of φ, and the dot product represents the rate of change of φ in the velocity direction; represents the diffusion term, Represents divergence, used to describe The degree of divergence in space; coefficient represents the controlled diffusion rate, γ represents the mobility (m3·s / kg), λ represents the mixing energy density (N), ε represents the interface thickness parameter (m), and ψ represents the phase field auxiliary variable; At the gas-liquid interface, the density ρ is smoothly varied across the two-phase interface. BD and viscosity μ BD Define it to mean: Among them, ρ w represents the density of water (kg / m3), ρ air Indicates air density (kg / m3), μ w Indicates the viscosity of water (Pa·s), μ air Indicates air viscosity (Pa·s); The two-phase flow Navier-Stokes equation and continuity equation are expressed as: Where ρ represents the fluid density (kg / m3), μ represents the dynamic viscosity (Pa·s), and u represents the velocity (m / s). represents the velocity gradient, represents the tensor transpose of the velocity gradient, p represents the flow inlet pressure (Pa), I represents the unit vector, and F st represents the interfacial tension of the two-phase fluid (N / m), g (m / s2) represents the gravity vector, and the formula is Indicates the incompressibility of the fluid; Convection and diffusion in the interface region will cause changes in the interface free energy, which will increase the interfacial tension F st Defined as:

5. The method for early fault detection of a power distribution switch according to claim 1, characterized in that: Before the step of analyzing the predicted arc parameters of the crack parameters and the potential difference according to the target simulation model, the method further includes: Setting a breakdown threshold according to the potential difference and material parameters of the power distribution switch; Obtaining the maximum electric field intensity in the crack region of the target simulation model; Determining whether the maximum electric field strength is greater than the breakdown threshold; If the maximum electric field strength is greater than the breakdown threshold, the step of analyzing the predicted arc parameters based on the crack parameters and the potential difference and the predicted air characteristics after discharge self-clearing according to the target simulation model is performed.

6. The method for early fault detection of a power distribution switch according to claim 1, characterized in that: The step of comparing the predicted arc parameter with the predicted arc parameter comprises: Acquire a minimum threshold of arc existence duration according to the predicted arc parameter; Determine the actual arc duration in the actual arc parameters; If the actual existence duration is less than or equal to the minimum duration threshold, it is determined that the distribution switch has no early failure; if the actual existence duration is greater than the minimum duration threshold, it is determined that the distribution switch has an early failure.

7. The method for early fault detection of a power distribution switch according to claim 1, characterized in that: After the step of comparing the predicted arc parameter with the predicted arc parameter, the method further comprises: Detecting whether the distribution switch re-ignites within a set time after the arc discharge is extinguished; If the re-ignition phenomenon occurs, it is determined that the distribution switch has an early failure.

8. A distribution switch early fault detection system, characterized in that: The system comprises: Establishing module for establishing initial air-water simulation model; An acquisition module, used to acquire crack parameters, potential difference and rain parameters of the power distribution switch to be detected, and to set parameters in the crack of the initial simulation model according to the crack parameters, to set the potentials at the top and bottom of the initial simulation model according to the potential difference, and to set the phase field variables of the initial two-phase simulation model according to the rain parameters, so as to obtain a target simulation model; An analysis module, configured to analyze predicted arc parameters based on the crack parameters and the potential difference according to the target simulation model; A detection module, used for detecting actual arc parameters of the power distribution switch; A comparison module, configured to compare the predicted arc parameter with the predicted arc parameter; The determination module is used to determine whether an early failure occurs in the power distribution switch according to the comparison result.

9. A computer-readable storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a processor, the processor executes the steps of the early fault detection method for a distribution switch according to any one of claims 1 to 7.

10. A computer device, characterized in that: The device comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for early fault detection of a distribution switch according to any one of claims 1 to 7.

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