A smart meter waterproof and dustproof detection method and device

Abstract

The present application relates to the technical field of power metering equipment testing, and discloses a kind of smart meter waterproof dust detection method and equipment, comprising: the test environment of low-pass filter isolation unit in series is constructed, and the dielectric reference model of thermal response in dry state is established;Start spraying and control the power modulation sequence of electric meter execution, utilize thermal expansion and cold contraction to establish the alternating pressure difference inside and outside the shell;Synchronous acquisition leakage current vector, channel impedance spectrum and internal temperature data;Solve the resistive leakage current component, impedance spectrum resonance frequency drift and thermal response phase lag, and thus comprehensively determine the sealing performance of electric meter.The present application blocks power interference by isolation unit, simulates real working conditions by using the breathing effect caused by power modulation, and solves the problem that traditional methods are difficult to identify trace moisture intrusion by combining electrical and thermodynamic multi-dimensional feature analysis, realizing high sensitivity online monitoring of early sealing failure risk of smart meter.

Description

Technical Field

[0001] This invention relates to the field of power metering equipment testing technology, specifically to a method and equipment for testing the waterproof and dustproof properties of smart meters. Background Technology

[0002] As the core terminal for electricity billing, smart meters are widely installed in outdoor metering boxes or open environments, facing harsh weather conditions such as rain, high humidity condensation, and dust accumulation. The sealing performance of the meter casing directly affects the corrosion resistance, metering accuracy, and long-term operational safety of the internal electronic components. Therefore, verifying the enclosure protection rating (IP code) of smart meters according to relevant national or international standards is a crucial step in product type testing and quality supervision.

[0003] Existing waterproof and dustproof testing of smart meters is typically conducted in dedicated environmental test chambers. The testing process generally adopts an exposure-first, judgment-later approach: the meter is subjected to rain or dust for a specified time, then removed and left to stand for a period of time before being judged for passability through insulation resistance testing, power frequency withstand voltage testing, or direct visual inspection of the interior for water or dust accumulation. However, this traditional testing and evaluation system has revealed certain limitations in practical applications.

[0004] First, traditional insulation resistance and withstand voltage tests primarily target severe failure modes where the insulation material has completely failed or internal conductive short circuits have occurred. When moisture only penetrates in trace amounts or merely adheres to the inner wall of the insulating casing, without forming a continuous conductive path in the high and low voltage areas of the circuit board, the electrical insulation indicators of the meter often do not show a significant decrease, resulting in a passing test result. However, these trace amounts of moisture or humidity lurking inside can trigger electrochemical migration of PCB circuits or metal electrolytic corrosion during long-term operation, causing delayed quality incidents. Second, most existing rain tests are conducted under conditions where the meter is powered off or only in steady-state operation, failing to fully simulate the thermodynamic effects generated during actual load fluctuations. Under real-world conditions, changes in the power consumption of the core components inside the meter cause temperature fluctuations in the internal gas, resulting in a pressure difference between the inside and outside of the casing. This suction force generated by thermal expansion and contraction is often the main driving force for overcoming the surface tension of the sealing strip that causes external moisture to be drawn in. Static rain tests lacking dynamic thermal load excitation cannot accurately reproduce this crucial failure mechanism. In addition, while opening the cover for inspection is intuitive, it damages the factory seal of the meter, making it unsuitable for non-destructive batch sampling or full inspection scenarios, and it is difficult to quantify and assess the degradation trend of the sealing performance. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method and equipment for testing the waterproof and dustproof properties of smart meters. This solves the problem that existing technologies mainly rely on insulation resistance or withstand voltage tests to determine failure in smart meter waterproofing tests, making it difficult to identify internal trace moisture intrusion and early sealing performance degradation without disassembling the device.

[0006] To achieve the above objectives, the present invention provides a method and equipment for testing the waterproof and dustproof properties of smart meters.

[0007] The first aspect of this invention provides a method for testing the waterproof and dustproof properties of a smart meter, comprising the following steps:

[0008] An electrical isolation test environment was constructed, the meter under test was connected to the load side of the isolation unit, and a thermal response reference transfer function and dielectric reference impedance model under dry conditions were established to determine the thermodynamic and electrical reference characteristics of the meter under test under fault-free conditions.

[0009] The spray mechanism of the rain test chamber is activated, the power modulation sequence of the meter under test is controlled to establish an alternating pressure difference inside and outside the shell; during the spraying, the leakage current vector is collected synchronously using the vector monitoring unit, the channel impedance spectrum is collected using the impedance analysis unit, and the internal temperature data is read through the communication interface unit.

[0010] The leakage current vector is decomposed by phase-sensitive detection to obtain the resistive component. The resonant frequency drift of the channel impedance spectrum relative to the dielectric reference impedance model is calculated, and the phase hysteresis angle of the real-time thermal response relative to the thermal response reference transfer function is calculated.

[0011] The control terminal determines the sealing performance of the meter under test based on the resistive component, the resonant frequency drift, and the phase lag angle.

[0012] In the step of constructing the electrical isolation test environment, a low-pass filter circuit composed of a power inductor and a safety capacitor is used as the isolation unit. This isolation unit is connected in series between the power supply unit and the power input terminal of the meter under test. The cutoff frequency of the isolation unit is set to be higher than the power frequency and lower than the power line carrier communication start frequency of the meter under test. This allows the isolation unit to exhibit low impedance pass-through characteristics at the power frequency and high impedance blocking characteristics in the carrier frequency band, thereby blocking high-frequency noise and internal impedance interference from the power supply unit side to the load-side measurement.

[0013] In the step of establishing the thermal response reference transfer function and dielectric reference impedance model under dry conditions, the meter under test is controlled to perform low-frequency power modulation with sinusoidal variation, and the input power waveform and internal temperature waveform are recorded synchronously. The fundamental phase component is extracted by discrete Fourier transform and the phase difference between the two is calculated as the drying reference phase lag angle. At the same time, the meter under test is controlled to send a swept carrier signal, and the input impedance magnitude corresponding to each frequency point in the carrier frequency band is recorded to construct a drying reference impedance spectrum vector containing inherent resonance peak characteristics.

[0014] In the step of controlling the meter under test to execute the power modulation sequence and establishing an alternating pressure difference inside and outside the casing, the microcontroller unit of the meter under test is controlled to perform high-intensity calculations or periodically switch the operating frequency, so that the total input power is superimposed on the power bias amount with the dynamic driving power amplitude; the heat wave generated by the power fluctuation causes the temperature of the sealed gas inside the casing to rise and fall periodically, and according to Charles's Law, the internal air pressure fluctuates, forming a driving field with alternating positive and negative pressure differences inside and outside the casing.

[0015] In the step of obtaining the resistive component by phase-sensitive detection decomposition of the leakage current vector, the voltage phasor and the total leakage current phasor at the power frequency fundamental frequency are obtained; the voltage phasor is set as the reference zero phase, and the phase difference between the total leakage current phasor and the voltage phasor is calculated; the effective value of the total leakage current phasor is multiplied by the cosine of the phase difference to obtain the resistive leakage current component; the dynamic trend baseline of the resistive leakage current component is calculated using a moving average filtering algorithm, and the real-time resistive current change after detrending is calculated.

[0016] In the step of calculating the resonant frequency drift of the channel impedance spectrum relative to the dielectric reference impedance model, the real-time acquired channel impedance spectrum is subtracted from the dielectric reference impedance model to obtain the differential impedance spectrum; the peak point of the impedance magnitude representing parallel resonance is searched and identified to obtain the real-time resonant frequency at the current moment; the relative frequency shift of the real-time resonant frequency relative to the inherent resonant frequency under dry conditions is calculated; when the relative frequency shift is positive and exceeds the theoretical allowable temperature drift value, it is determined that the dielectric environment inside the shell has changed due to moisture infiltration.

[0017] In the step of calculating the phase lag angle of the real-time thermal response relative to the thermal response reference transfer function, dynamic power is used as the system excitation input and internal temperature is used as the system response output to construct a linear time-invariant thermodynamic system model; the power fundamental phase and temperature fundamental phase at the modulation frequency are extracted, and the difference between the two is calculated to obtain the real-time phase lag angle; the phase drift of the real-time phase lag angle relative to the drying reference phase lag angle is calculated.

[0018] In the step of determining the sealing performance of the meter under test based on the resistive component, the resonant frequency drift, and the phase lag angle, the resistive component, the resonant frequency drift, and the phase lag angle are mapped to normalized electrical risk index, dielectric risk index, and thermodynamic risk index, respectively. A weighted summation of the electrical risk index, dielectric risk index, and thermodynamic risk index is performed to calculate a comprehensive sealing failure index. If the electrical risk index exceeds a set value, it is directly determined to be a conductive water ingress failure. If the comprehensive sealing failure index exceeds a set threshold but the electrical risk index does not exceed the limit, it is determined to be an early sealing failure risk.

[0019] A second aspect of the present invention provides a waterproof and dustproof testing device for smart meters, comprising:

[0020] The rain test chamber includes a rotating platform for supporting the meter under test and a spray mechanism for applying environmental pressure; a power supply unit whose output is connected to the input of an isolation unit; the isolation unit is connected in series between the power supply unit and the power supply input of the meter under test; a vector monitoring unit is connected in series in the circuit between the isolation unit and the meter under test; an impedance analysis unit is connected in parallel to the power supply input of the meter under test and located on the load side of the isolation unit; a communication interface unit is connected between the data port of the meter under test and a control terminal; the control terminal establishes a communication connection with the above units via a bus to perform monitoring and judgment.

[0021] The isolation unit consists of a power inductor connected in series in the phase line loop and a safety capacitor connected in parallel between the phase line and the neutral line; the vector monitoring unit is a broadband power analyzer used to acquire voltage, current waveforms and phase angles; the impedance analysis unit uses a spectrum receiver or network analyzer to measure the input impedance spectrum within the carrier frequency band; and the communication interface unit is an opto-isolated transceiver used to connect the data port of the meter under test to the control terminal.

[0022] This invention provides a method and device for testing the waterproof and dustproof properties of smart meters. It has the following beneficial effects:

[0023] 1. This invention achieves a multi-dimensional evaluation of the sealing performance of electric meters by comprehensively analyzing resistive leakage current, channel impedance spectrum resonant frequency drift, and thermal response phase hysteresis angle. Compared with traditional methods that rely solely on insulation resistance or withstand voltage tests, this invention utilizes the physical characteristics of moisture intrusion leading to an increase in dielectric constant and changes in the thermal resistance-capacitance network. This enables the identification of early failure states where a small amount of moisture intrusion has occurred but has not yet caused an electrical short circuit, thereby improving the ability to identify latent sealing defects.

[0024] 2. This invention connects an isolation unit consisting of a power inductor and a safety capacitor in series between the power supply and the meter under test. By utilizing its high impedance characteristics in the carrier frequency band, it effectively blocks the interference of high-frequency noise and internal impedance on the load side impedance measurement. This design provides a low-noise electrical environment for high-precision dielectric response monitoring, ensuring that the impedance analysis unit can accurately distinguish the resonant frequency drift signal caused by subtle changes in humidity inside the casing.

[0025] 3. This invention uses the method of controlling the meter to execute a power modulation sequence, and uses the heat wave generated by dynamic power consumption to establish an alternating pressure difference driving field inside and outside the shell; the method uses the internal air pressure fluctuation formed by the principle of thermal expansion and contraction to overcome the surface tension of the liquid in the tiny leakage channel, and simulates the breathing effect in actual operation without damaging the shell structure, thereby improving the detection efficiency of tiny non-straight-through pores. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the structure of the smart meter waterproof and dustproof detection system according to an embodiment of the present invention;

[0027] Figure 2 This is a flowchart of the waterproof and dustproof testing method for smart meters according to an embodiment of the present invention;

[0028] Figure 3 This is a schematic diagram of the detection equipment of the present invention;

[0029] Figure 4 This is a schematic diagram of the internal structure of the detection device of the present invention.

[0030] Among them, 100 is the rain test chamber; 101 is the rotating table; 102 is the spraying mechanism; 200 is the communication interface unit; 300 is the power supply unit; 400 is the isolation unit; 500 is the vector monitoring unit; 600 is the impedance analysis unit; and 700 is the control terminal. Detailed Implementation

[0031] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] See attached document Figure 1 Appendix Figure 3 With appendix Figure 4The present invention provides a smart meter testing system based on thermal modulation transfer function and differential impedance spectrum, including a rain test chamber 100, a communication interface unit 200, a power supply unit 300, an isolation unit 400, a vector monitoring unit 500, an impedance analysis unit 600, and a control terminal 700.

[0033] The meter under test is fixedly mounted on a rotating platform 101 inside a rain test chamber 100. The rain test chamber 100 is equipped with a spray mechanism 102, which is configured to apply liquid pressure or a dust environment conforming to preset standards to the meter under test. During the test, the rotating platform 101 drives the meter under test to rotate at multiple angles.

[0034] The communication interface unit 200 is connected between the data port of the meter under test and the control terminal 700. It is configured as an opto-isolated transceiver and is used for command transmission and internal register data reading.

[0035] The power supply unit 300 is connected to the input terminal of the isolation unit 400 and is configured to provide the system with AC power that is controllable in voltage, frequency and phase, and to adjust the output power waveform in response to control commands.

[0036] An isolation unit 400 is connected in series between the power supply unit 300 and the power input terminal of the meter under test. The isolation unit 400 consists of a low-pass filter network composed of an inductor and a capacitor, with its cutoff frequency set below the power line carrier start frequency of the meter under test. Under power frequency conditions, the isolation unit 400 exhibits low-impedance shoot-through characteristics; within the carrier frequency band, the isolation unit 400 exhibits high-impedance blocking characteristics, used to isolate high-frequency noise from the power supply unit 300 side.

[0037] The vector monitoring unit 500 is connected in series in the loop between the isolation unit 400 and the meter under test, and is configured as a wideband power analyzer to synchronously acquire the voltage waveform, current waveform and phase angle parameters of the input terminal of the meter under test 1.

[0038] Impedance analysis unit 600 is connected in parallel to the power input terminal of the meter under test, located on the load side of isolation unit 400. Impedance analysis unit 600 is configured as a spectrum receiver or network analyzer to measure the channel input impedance spectrum and frequency response characteristics within the carrier frequency band.

[0039] The control terminal 700 establishes a communication connection with the above-mentioned units through an industrial bus to send timing synchronization trigger signals and to collect and process the monitoring data fed back by each unit.

[0040] See attached document Figure 2 This invention provides a method for testing the waterproof and dustproof properties of smart meters, comprising the following steps:

[0041] S10, Construct an electrical isolation test environment. Install the meter under test inside the rain test chamber 100 and connect it to the power supply unit 300 via the isolation unit 400. Connect the vector monitoring unit 500 and the impedance analysis unit 600, and establish a data link through the communication interface unit 200. The control terminal 700 sends time synchronization commands to each unit to unify the system clock domain.

[0042] S20, Establish a dry state reference model. Before starting the spray mechanism 102, control the power supply unit 300 to output a steady-state voltage and control the meter under test to execute a low-frequency power modulation sequence. The control terminal 700 synchronously records the phase relationship between the internal temperature and input power of the meter under test, generating a thermal response reference transfer function. At the same time, control the meter under test to send a swept-frequency carrier signal, and the impedance analysis unit 600 records the channel impedance spectrum, generating a dielectric reference impedance model.

[0043] S30, apply dynamic environmental pressure and multidimensional excitation. The spray mechanism 102 of the rain test chamber 100 is activated to apply cold shock and negative pressure suction effect to the meter under test. During this process, the meter under test is continuously controlled to perform low-frequency power modulation to maintain dynamic thermal flow field excitation. Simultaneously, the meter under test is controlled to periodically send swept frequency carrier signals to maintain electromagnetic field excitation.

[0044] S40 performs multi-physics characteristic monitoring. During S30, the vector monitoring unit 500 acquires the leakage current vector in real time and separates the resistive and capacitive components; the impedance analysis unit 600 acquires the channel impedance spectrum in real time and calculates the differential spectrum relative to the dielectric reference impedance model; the control terminal 700 reads the internal temperature data in real time and calculates the phase hysteresis angle relative to the thermal response reference transfer function.

[0045] S50 integrates and determines sealing performance. The control terminal 700 comprehensively analyzes the abrupt change characteristics of resistive leakage current, the resonant frequency drift characteristics of differential impedance spectrum, and the shift characteristics of thermal response phase hysteresis angle. If any characteristic parameter exceeds the preset safety threshold, the meter under test is determined to have failed sealing; if all characteristic parameters are within the safety threshold range, the meter under test is determined to have passed the test.

[0046] See attached document Figure 2 In step S10, an electrical isolation test environment is constructed and a data synchronization mechanism is established. This step addresses the bypassing and shunting problem of low-impedance loads on the grid side to high-frequency signals, as well as the time asynchrony problem of multi-source sensor data, through physical circuit construction and software timing calibration. Step S10 specifically includes the following sub-steps:

[0047] S101, construct the physical link for impedance isolation and signal transmission. Install the smart meter under test (SMUT) at the test station of the integrated rain test chamber, and connect the power supply terminal to the load-side output terminal of the isolation unit 400. The isolation unit 400 adopts an LC low-pass filter circuit topology, which includes a power inductor connected in series in the phase line loop and a safety capacitor connected in parallel between the phase line and the neutral line. The power inductor uses an iron-silicon-aluminum magnetic core or a high-flux magnetic core to ensure that magnetic saturation does not occur when the SMUT carries a full-load current (e.g., 60A or 100A), maintaining the linearity of the inductance value.

[0048] Based on the power line carrier communication protocol frequency band used by the smart meter, the cutoff frequency parameter of isolation unit 400 is selected. If the starting frequency of the carrier communication frequency band is... (e.g., on the order of kHz), then set the cutoff frequency. The following relationship must be satisfied:

[0049] ;

[0050] in This is the power frequency (50Hz or 60Hz). In specific implementation, the cutoff frequency... The preferred value range is 3kHz to 9kHz.

[0051] Through the above configuration, the isolation unit 400 achieves the following technical effects: On the one hand, it presents low impedance direct current at the power frequency, ensuring the power supply to the energy meter; on the other hand, in the carrier frequency band and above, it utilizes the high inductive reactance of the inductor to form a high impedance barrier. This high impedance barrier not only blocks conducted noise from the power supply side, but more importantly, it shields the extremely low internal impedance of the power supply side (usually less than 1 ohm), preventing it from shunting and masking the weak parasitic capacitance change signal inside the energy meter under test, thereby improving the measurement signal-to-noise ratio of the impedance analysis unit 600 connected in parallel to the load side.

[0052] S102, configure signal acquisition parameters and establish communication handshake. The control terminal 700 sends configuration commands to the vector monitoring unit 500 via the industrial bus to set the sampling rate, measurement bandwidth, and integration time parameters for the voltage and current channels. The sampling rate is set to be more than 5 times the highest harmonic frequency of the signal under test, typically set to 100 kS / s to 1 MS / s, to fully capture waveform details including the thermally modulated low-frequency envelope and transient changes in leakage current.

[0053] Simultaneously, the control terminal 700 establishes an application-layer connection with the smart meter through the communication interface unit 200. The control terminal 700 sends a specific register read command to the smart meter to verify the validity of the onboard temperature sensor data. The system sets the temperature data read refresh frequency. The frequency should be no lower than 2Hz to meet the sampling theorem requirements for the thermal modulation process (typically 0.01Hz to 0.05Hz) and avoid aliasing errors. For the handshake process and register address definition of the smart meter's communication protocol, those skilled in the art can refer to standard communication protocol specifications such as DL / T 645 or DLMS / COSEM, which are well-known technologies in the field and will not be elaborated further here.

[0054] S103 performs system-level clock synchronization and timing alignment. Given that the vector monitoring unit 500 outputs high-frequency waveform data at the microsecond level, while the smart meter's internal temperature sensor outputs low-frequency data including communication transmission delays, the control terminal 700 establishes the system's absolute time axis by sending a unified time base trigger signal. .

[0055] The control terminal 700 records the timestamp of sending the temperature read command. Timestamp of received temperature data return frame Calculate the communication transmission delay correction amount In one embodiment, assuming symmetrical uplink and downlink delays in the communication link, the correction is calculated as follows:

[0056] ;

[0057] During the data preprocessing stage, the control terminal 700 marks the logical time corresponding to the received temperature measurement value as... This time-shifting operation maps the lagging temperature data points back to their physical sampling time, ensuring that the synchronization error between these data points and the voltage and current data collected by the vector monitoring unit 500 on the time axis is controlled within milliseconds (e.g., less than 10ms). This alignment step eliminates phase deviations introduced by non-physical factors (communication delays), ensuring that the phase lag angle of the thermal response transfer function calculated in subsequent steps accurately reflects the thermal resistance-capacitance physical characteristics of the smart meter.

[0058] See attached document Figure 2 In step S20, a multi-dimensional benchmark model under dry conditions is established. This step aims to obtain the inherent physical characteristic parameters of the smart meter under test under the absence of environmental pressure interference, and to eliminate individual measurement errors caused by differences in device manufacturing tolerances, PCB layout, and ambient base temperature by establishing a reference system. Step S20 specifically includes the following sub-steps:

[0059] S201, Perform environmental initialization and thermal equilibrium verification. Maintain the integrated rain test chamber in a standard atmospheric environment and shut down the spray and dust control mechanisms. The control terminal 700 monitors the rate of change of the internal temperature sensor value of the smart meter. To prevent initial temperature drift from interfering with subsequent phase calculations, the system needs to confirm thermal stability. When the internal temperature change rate is lower than the preset steady-state judgment threshold (e.g., 0.1℃ / min), the smart meter under test is determined to have reached thermal equilibrium and meets the baseline acquisition conditions.

[0060] S202, Obtain the thermal response reference transfer function. This step aims to determine the thermal resistance-capacitance network characteristics of the smart meter under test, which consists of its own structural materials, sealed air layer, and circuit board. The control terminal 700 sends computing power scheduling instructions to the smart meter, controlling its microcontroller unit (MCU) to perform periodic floating-point operations or data transfer tasks, thereby generating controlled dynamic power consumption fluctuations within the smart meter.

[0061] Set input power According to the low-frequency sinusoidal pattern, its functional relationship can be expressed as:

[0062] ;

[0063] The definitions and value selection principles of each variable are as follows:

[0064] This serves as the average power baseline. Its value must ensure that the average internal temperature of the electricity meter is higher than a preset value for the external ambient temperature (e.g., a temperature rise greater than 15°C) to guarantee that a continuous negative pressure can be formed inside the casing relative to the outside during the subsequent spraying phase. It is typically set to 60% to 80% of the electricity meter's rated maximum power consumption.

[0065] This represents the power modulation amplitude. Its value needs to be large enough that the resulting temperature fluctuation exceeds the quantization resolution of the internal temperature sensor (e.g., greater than 0.5°C) while avoiding triggering the layout thermal protection. It is typically set to... 10% to 20%.

[0066] This is the thermal modulation frequency. This frequency is determined by the system's thermal time constant and must ensure that the heat wave can be effectively conducted to the casing surface. For conventional polycarbonate casing meters, the value ranges from 0.01Hz to 0.05Hz.

[0067] While applying power excitation, the vector monitoring unit 500 simultaneously acquires the actual input power data, and the control terminal 700 simultaneously reads the internal temperature data. Based on the principle of linear time-invariant (LTI) systems, the Discrete Fourier Transform (DFT) is used to extract the input power waveform and the internal temperature waveform at the fundamental frequency. The phase component at that point. Calculate the difference between the two, and denot it as the drying reference phase lag angle. Physically, It directly reflects the resistive-capacitive characteristics of the thermal path formed by the dry air medium and the dry PCB board. Compared to directly measuring absolute temperature, the phase hysteresis angle is less sensitive to the slow overall drift of ambient temperature, providing a more stable detection benchmark. For a typical well-sealed smart meter, The typical value range is usually between 30 degrees and 60 degrees.

[0068] S203, Establish a dielectric reference impedance model. This step uses the power line carrier communication frequency band to perform frequency sweep calibration on the high-frequency impedance characteristics of the power input port of the energy meter. Control the smart meter's carrier communication module to enter test transmission mode, within the preset frequency band. It transmits continuous wave signals at stepped frequencies. This frequency band covers the main operating frequency band of Power Line Communication (PLC), specifically set from 10kHz to 500kHz.

[0069] Impedance analysis unit 600, located on the load side of isolation unit 400, synchronously measures and records the input impedance magnitude at each frequency point within the frequency band, constructing a dry reference impedance spectrum vector. :

[0070] ;

[0071] in, to To scan frequency points, This represents the total number of frequency points. This reference impedance spectrum primarily reflects the parallel resonance characteristics of the safety capacitor, varistor, and EMI filter at the power input of the smart meter. Since the external power supply impedance has been isolated, the resonant peak frequency appearing in this impedance spectrum is... The dielectric environment of the electricity meter is inherently determined solely by the parameters of its internal components and the distributed parasitic parameters.

[0072] S204, Reference data verification and storage. The control terminal 700 verifies and stores the acquired data. and Perform a validity check. If... Exceeding the preset empirical statistical range (e.g., less than 10 degrees or greater than 80 degrees), or If the expected LC resonance peak is not detected, the connection is deemed abnormal or the initial state of the energy meter is faulty, and the test is terminated. After successful verification, the above parameters are stored as the reference characteristic parameter set of the smart meter under test, which will be used as the minuend in the differential operation in subsequent steps.

[0073] See attached document Figure 2 In step S30, dynamic environmental pressure and multidimensional excitation are applied. This step aims to establish an alternating pressure gradient inside and outside the smart meter casing through the coupling effect of external environmental stress and internal active heat source modulation. This dynamic excitation mechanism utilizes the principle of thermal expansion and contraction, transforming traditional static passive permeation detection into dynamic active aspiration detection. It aims to overcome the surface tension resistance of liquids in micro-leakage channels and improve the detection rate of micron-level cracks and sealing defects. Step S30 specifically includes the following sub-steps:

[0074] S301, Applying external environmental cold shock and medium coverage. The spray mechanism 102 of the integrated rain test chamber is activated, spraying water meeting preset temperature and flow rate standards onto the surface of the smart meter under test. Initially, due to the lower temperature of the external water flow compared to the smart meter's outer casing, a thermal shock effect occurs. This thermal shock causes the smart meter's casing material to contract instantaneously, while the enclosed gas inside the casing contracts in volume due to cooling via heat conduction. According to Charles's Law, under constant volume conditions, a decrease in internal gas temperature leads to a decrease in internal gas pressure, thereby establishing an initial static negative pressure difference between the inside and outside of the smart meter. Specific spray parameters, such as the oscillation pipe angle, spray nozzle diameter, and water flow rate, can be set by those skilled in the art according to the provisions of GB / T 4208 or IEC 60529 standards regarding IP protection level testing; these are well-known techniques in the field and will not be elaborated upon here.

[0075] S302 executes internal dynamic power modulation based on computing power scheduling. During continuous spraying, constant power heating is not used; instead, the smart meter continues to execute a low-frequency power modulation strategy. The control terminal 700 sends specific control commands to the smart meter through the communication interface unit 200 to change the operating state of its microcontroller unit (MCU) and peripherals. Specific implementation methods include: controlling the MCU to execute high-intensity matrix multiplication or empty loop instructions to increase CPU utilization, periodically switching the MCU's main frequency (e.g., switching between 4MHz and 32MHz), periodically turning the power amplifier (PA) of the onboard power line carrier communication module on and off, and controlling the backlight's on / off state.

[0076] Through software-defined control of the aforementioned hardware load, the total input power of the smart meter is controlled. Over time Fluctuation according to a preset function:

[0077] ;

[0078] The definitions and value ranges of each parameter are as follows:

[0079] This is the power bias. Its value is preferably set to 50% to 70% of the rated maximum power of the smart meter. The purpose of setting this bias is to establish a higher base temperature field, ensuring that the surface temperature of the internal PCB board and key components of the smart meter is still higher than the ambient dew point temperature during modulation troughs, thus preventing misjudgments caused by a decrease in insulation resistance due to physical condensation.

[0080] This is the dynamic driving power amplitude. Its value is preferably set to 20% to 40% of the rated maximum power of the smart meter. This amplitude directly determines the expansion and contraction of the internal gas; the larger the amplitude, the stronger the pressure difference driving force.

[0081] This is the modulation frequency. The selection of this frequency needs to be related to the thermal time constant of the smart meter. This matching ensures that internal temperature fluctuations have detectable phase characteristics. If the frequency is too high, the internal air temperature will not follow power changes; if the frequency is too low, the system approaches quasi-static, and the phase difference will approach zero. For a typical polycarbonate-cased smart meter, It usually lasts for 10 to 30 minutes, therefore The preferred setting is 0.0005Hz to 0.005Hz (i.e., a period of several minutes to thirty-five minutes).

[0082] S303 establishes a thermally and aerodynamically coupled alternating pressure difference driving field. Through power modulation via S302, the heating element inside the smart meter generates periodic heat waves. These heat waves act on the enclosed gas inside the casing through air convection and solid-state conduction, causing the internal gas temperature to rise. This fluctuates accordingly. Within the shell volume Under the premise of being basically constant, according to the ideal gas law, the internal gas pressure It will fluctuate periodically with temperature.

[0083] At this time, the pressure difference between the inside and outside of the smart meter It manifests as:

[0084] ;

[0085] in It is the sum of the external atmospheric pressure and the spray water pressure.

[0086] Due to the periodic variation of input power, It will alternate between positive and negative pressure differentials.

[0087] The core principle of this invention lies in overcoming capillary action using alternating pressure differences. When tiny leakage channels exist (such as microcracks or gaps in sealing rings), the liquid is hindered by surface tension within the channels. A constant static negative pressure is often insufficient to overcome this surface tension. However, under the action of the alternating pressure difference field generated in this step: during the power increase phase, the internal gas expands, generating an outward thrust that causes the liquid stagnant at the channel opening to move outward; during the power decrease phase, the internal gas contracts, generating an inward suction force. This reciprocating mechanical stress not only disrupts the surface tension balance of the liquid but also, through the pumping effect of thermal expansion and contraction, gradually draws external moisture into the shell, thereby improving the detection sensitivity of hidden sealing defects.

[0088] See attached document Figure 2 In step S40, dynamic vector separation monitoring of leakage current is performed. This step is a monitoring process executed in parallel with the application of dynamic environmental pressure and thermal modulation excitation in step S30. Its core objective is to solve the technical problem that in rainy or high-humidity environments, a water film forming on the surface of the smart meter casing introduces a large parasitic capacitive current, thus masking the weak resistive fault leakage current. This invention utilizes the principle of insulation dielectric loss angle to separate the resistive component characterizing insulation failure from the total leakage current through vector decomposition technology. Step S40 specifically includes the following sub-steps:

[0089] S401 acquires instantaneous voltage and leakage current waveforms in real time. The vector monitoring unit 500 synchronously acquires the instantaneous voltage signal at the smart meter input terminal at a high-frequency sampling rate (preferably 100kS / s to 250kS / s). and the instantaneous leakage current signal in the circuit .

[0090] Leakage current signal here The acquisition method is as follows: A zero-sequence current transformer (ZCT) made of a high-permeability permalloy core is simultaneously connected to the outside of the phase line (L) and neutral line (N) of the smart meter. Under ideal insulation conditions, the vector sum of the current flowing into the L line and the current flowing out of the N line is zero; when leakage occurs, the transformer induces a non-zero differential mode current signal.

[0091] To prevent high-frequency harmonics of the load current from interfering with leakage measurements, the vector monitoring unit 500 is equipped with an analog front-end anti-aliasing filter. The cutoff frequency of this filter is set to 2kHz to 5kHz, and its passband must completely cover the 50Hz or 60Hz power frequency fundamental signal to ensure the linearity of the phase measurement.

[0092] S402, performs vector decomposition based on phase-sensitive detection. This step separates signals based on the following physical model: The sprayed water film on the surface of the smart meter casing is separated from the internal charged conductor by an insulating shell, forming a parallel-plate capacitor model. The resulting leakage current is mainly displacement current, which leads the voltage by 90 degrees in phase (exhibiting pure capacitiveness). When moisture enters the casing through sealing defects, the water droplets mix with dust or ionic contaminants on the circuit board to form a conductive electrolyte, creating a resistive path between the charged part and ground. The resulting leakage current is in phase with the voltage (exhibiting pure resistivity).

[0093] The vector monitoring unit 500 collects discrete voltage data sequences. and leakage current data sequence Perform a Fast Fourier Transform (FFT) to extract the voltage phasor at the fundamental frequency of the power grid. With current phasor Set voltage phasor The reference phase is 0 degrees. Calculate the phase difference between the total leakage current vector and the voltage vector. It is stipulated that when the current leads the voltage... Positive value, lagging time The value is negative. Based on this phase difference, the total leakage current amplitude is... Decomposed into resistive leakage current components and capacitive leakage current component The calculation formula is as follows:

[0094] ;

[0095] ;

[0096] in:

[0097] This is the measured effective value of the total leakage current;

[0098] Let be the phase angle of the current vector relative to the voltage vector. In the case of ideal insulation and the presence of an external water film, Approaching 90 degrees, at this time Approaching zero; when water ingress causes a decrease in insulation, Shifting towards 0 degrees Significantly increased.

[0099] The resistive leakage current component is a direct parameter for determining seal failure.

[0100] S403, Dynamic Baseline Removal and Feature Extraction. During prolonged dynamic testing, even without water ingress, resistive leakage current... The thermal modulation applied in step S30 may also cause temperature changes in the insulating material, leading to slight fluctuations in dielectric constant and insulation resistance (thermal drift). To accurately capture the abrupt changes caused by water ingress, this slowly changing background baseline needs to be eliminated.

[0101] The system uses a moving average filtering algorithm to calculate Dynamic trend baseline And calculate the real-time resistive current change after detrending. :

[0102] ;

[0103] in:

[0104] This represents the number of sampling points and width of the sliding window. The corresponding time length is... It needs to be set to be greater than the thermal power modulation period. More than 1.5 times (e.g.) (minutes) to ensure that the baseline follows thermally induced drift, but not rapid step signals caused by water ingress.

[0105] This is the purely resistive abrupt change component after differentiation.

[0106] The system has a preset safety threshold for leak detection. This threshold is determined based on safety standards (such as IEC 62052-31) and the insulation class of the electricity meter. It is typically set... The current is 0.5mA to 3mA. If... Exceeding at any time If so, it is determined that a liquid medium intrusion event has occurred.

[0107] See attached document Figure 2 In step S40, a channel differential impedance spectroscopy scan is performed synchronously. This step aims to utilize the high dielectric constant of water molecules to detect trace amounts of gaseous water molecule permeation or discrete condensation that has not yet formed a continuous conductive circuit by monitoring the impedance resonant point drift of the high-frequency signal path. This step uses the safety capacitor and filter circuit at the power input terminal of the smart meter as a highly sensitive dielectric sensor, compensating for the limitation of step S40 in detecting only resistive continuity faults, and enabling earlier detection of signs of sealing failure. Step S40 specifically includes the following sub-steps:

[0108] S404, perform real-time impedance frequency sweep of the carrier band. During the application of dynamic environmental pressure in step S30, the impedance analysis unit 600 continuously monitors the load side of the impedance isolation decoupling unit. The control terminal 700 controls the power line carrier communication (PLC) of the smart meter to enter the test mode via commands, or uses the external impedance analysis unit 600 as an excitation source to perform periodic frequency sweeps within a preset carrier communication frequency band (e.g., 10kHz to 500kHz).

[0109] To ensure sufficient frequency resolution to capture the shift of the narrowband resonant peak, a sweep step frequency is set. The frequency band is no greater than 1 kHz (preferably 100 Hz to 500 Hz). The impedance analysis unit 600 samples and calculates the input impedance magnitude within this frequency band in real time, generating a real-time impedance spectrum vector. Since the impedance isolation decoupling unit has blocked the low-impedance loop on the grid side, this real-time impedance spectrum mainly reflects the parallel resonance characteristics of the EMI filter capacitor, varistor, and parasitic capacitance inside the casing at the power input port of the smart meter.

[0110] S405 calculates the differential impedance spectrum and extracts resonance characteristics. Control terminal 700 acquires the real-time impedance spectrum vector. Then, the drying reference impedance spectrum vector obtained in step S20 is retrieved from the storage unit. Perform a spectral subtraction operation to obtain the differential impedance spectrum. :

[0111] ;

[0112] Differential calculations eliminate the influence of cable impedance and static background impedance, highlighting dynamic changes. Control terminal 700 pairs or original spectrum An extremum search is performed to identify the peak point of the impedance magnitude characterizing parallel resonance. The system records the natural resonant frequency under dry reference conditions. and the real-time resonant frequency at the current moment. .

[0113] S406, Frequency drift determination based on abrupt changes in dielectric constant. This step is based on the physical model of the frequency response of an LC resonant circuit. The equivalent resonant frequency at the smart meter input terminal. From equivalent inductance With equivalent capacitance The decision is made such that the following relationship is satisfied:

[0114] ;

[0115] Among them, equivalent capacitance Due to the inherent filter capacitors of the circuit board With the distributed stray capacitance inside the casing Parallel connection. Distributed stray capacitance. The size is related to the relative permittivity of the medium inside the shell. Proportional.

[0116] The detection principle of this invention lies in the relative permittivity of dry air. The relative permittivity of liquid water Even minute amounts of water vapor intrusion or the formation of non-conductive micro-condensation on the PCB surface can lead to [damage / consumption] due to the dipole polarization effect of water molecules. Significantly increased, which in turn caused Increase. According to the above formula, when... When the resonant frequency increases, It will inevitably shift towards lower frequencies.

[0117] The system calculates the relative frequency shift of the resonant frequency. :

[0118] ;

[0119] To distinguish between component temperature drift caused by thermal modulation (step S30) and large dielectric constant drift caused by actual water ingress, the system introduces dynamic judgment logic based on temperature compensation. The control terminal 700 determines the internal temperature change based on the data obtained in step S40. Calculate the theoretical allowable temperature drift value :

[0120] ;

[0121] in, The temperature coefficient of the input capacitor for the electricity meter (usually a known constant, such as ±200ppm / ℃), This is the engineering tolerance margin (e.g., 0.5%).

[0122] The judgment logic is as follows: if a relative frequency shift is detected... It is a positive value (i.e., the frequency decreases), and its absolute value significantly exceeds the theoretical allowable temperature drift value (i.e., If the frequency shift is within a certain range, it indicates an abnormal change in the dielectric environment inside the casing, suggesting the intrusion of water molecules. Conversely, if the frequency shift is within a certain range... Fluctuations within a certain range are considered normal thermally induced frequency shifts. This logic effectively avoids misjudgments caused by heating cycles, ensuring that the test results are only sensitive to substances with high dielectric constants (water).

[0123] See attached document Figure 2In step S40, a thermal response phase transfer function analysis is performed in parallel. This step utilizes the principle of thermal diffusion, treating the smart meter as a linear time-invariant (LTI) thermodynamic system. By monitoring the phase delay change between the input power waveform and the internal temperature response waveform, changes in the thermal properties of the medium inside the casing are identified. Unlike traditional humidity sensor detection, this method leverages the significant physical differences in thermal conductivity and specific heat capacity between water and air, enabling the detection of water ingress events through the drift of global thermal resistance-capacitance characteristics even without direct sensor contact with water. Step S40 specifically includes the following sub-steps:

[0124] S407, Construct a thermodynamic input-output model and extract the fundamental component. The system will then apply the dynamic power from step S30. The temperature collected by the internal sensors of the smart meter will be used as the system's excitation input. As the system response output, the control terminal 700 performs Digital Quadrature Correlation (DQC) or Discrete Fourier Transform (DFT) on the synchronously acquired power and temperature sequences to accurately extract the values ​​at the modulation frequency. The fundamental amplitude and phase information at the location.

[0125] Specifically, setting The modulation frequency is [value], and the sampling period is [value]. The control terminal 700 calculates the fundamental phase of the power signal. Phase with the fundamental frequency of the temperature signal To eliminate noise interference, the integration time needs to cover at least three complete modulation cycles.

[0126] S408, calculate the phase lag angle of the real-time thermal response transfer function. Based on system identification theory, calculate the real-time phase lag angle under the current humid and hot environment. :

[0127] ;

[0128] in, This characterizes the time delay characteristic of heat generated from the onboard heat source, passing through the PCB board and the internal air layer to reach the temperature sensor location. This physical quantity is determined by the thermal resistance inside the smart meter. With heat capacity The time constant of the heat network The decision is made such that the following relationship is satisfied:

[0129] ;

[0130] This formula shows that the phase lag angle is directly related to the thermal resistance and capacitance parameters inside the system.

[0131] S409, Differential phase decision based on thermophysical property differences. The drying reference phase hysteresis angle stored in system call step S20. Calculate the phase drift. :

[0132] ;

[0133] The logic behind this judgment is based on the following thermophysical mechanism: dry air is a poor conductor of heat (thermal conductivity of about 0.026 W / m·K) and has a small heat capacity; while liquid water is a better conductor of heat (thermal conductivity of about 0.6 W / m·K, which is more than 20 times that of air) and has a very large specific heat capacity.

[0134] When a seal failure leads to moisture intrusion, the air medium inside the casing is partially replaced by water vapor or liquid water, resulting in increased thermal resistance. Significantly reduced (increased thermal conductivity), while heat capacity Increased heat absorption capacity. This changes the system's thermal time constant. This leads to a shift in the phase lag angle. Furthermore, if trace amounts of moisture undergo a phase transition (evaporation and condensation) during periodic thermal fluctuations, the absorption and release of latent heat will introduce additional nonlinear phase delay.

[0135] The system has a phase drift threshold set. This threshold is determined based on the statistical distribution of a large number of electricity meters of the same model, and is typically set between 3 and 8 degrees. If detected... If this state persists for more than a preset confirmation window (e.g., 3 modulation cycles), it is determined that there is a change in the thermal medium environment inside the smart meter caused by water ingress, and a seal failure alarm signal is output. This method has a unique advantage in detecting situations where internal insulation materials absorb moisture due to water ingress (changing thermal conductivity), and can supplement the blind spots in electrical parameter detection.

[0136] See attached document Figure 2 In step S50, a multi-physics feature fusion judgment is performed. This step aims to address the problem of false alarms or missed alarms caused by a single detection dimension in complex dynamic environments (such as high humidity, variable temperature, and electromagnetic interference environments). Based on the principle of heterogeneous redundancy, this step maps the insulation damage characteristics of the electrical dimension, the microscopic penetration characteristics of the dielectric dimension, and the macroscopic water accumulation characteristics of the thermodynamic dimension to a unified dimensionless metric space, and constructs a comprehensive quantitative index reflecting the sealing integrity of the smart meter through weighted fusion. Step S50 specifically includes the following sub-steps:

[0137] S501, Characteristic parameter normalization processing. Control terminal 700 receives the real-time resistive current fluctuations calculated from the three sub-processes in step S40. Relative drift of impedance resonant frequency and thermal response phase shift .

[0138] Because these three physical quantities have different dimensions (milliamperes, percentages, and degrees, respectively) and vastly different numerical magnitudes, the system first maps them to a standardized risk space of [0, +∞) to achieve data fusion. The normalization calculation formula and processing logic are as follows:

[0139] Electrical Risk Normalization Index :

[0140] ;

[0141] in The leakage detection safety threshold (e.g., 1mA) is set in step S40.

[0142] Dielectric risk normalization index :

[0143] To eliminate non-faulty temperature drift interference, a dead-zone filtering mechanism is introduced in the calculation of this index:

[0144] ;

[0145] in, This is the theoretical allowable temperature drift value at the current temperature calculated in step S40; The preset severe moisture frequency shift reference value (usually set to 2% to 5% of the resonant frequency) is used to define the reference state when the risk level is 1.0.

[0146] Thermodynamic risk normalization index :

[0147] ;

[0148] in The phase drift threshold set in step S40.

[0149] S502, Calculate the multidimensional seal failure comprehensive index. The system uses a weighted linear fusion algorithm to calculate the current seal failure comprehensive index. .

[0150] ;

[0151] in, , , Let be the weighting coefficient, satisfying .

[0152] In this embodiment, the values ​​of each weighting coefficient and their technical basis are as follows:

[0153] (Electrical weight) is set to 0.5 to 0.6. Technical basis: Resistive leakage current means that water molecules have connected to the charged circuit, constituting substantial insulation failure and safety hazard. It belongs to the highest priority in the judgment weight, so it is assigned the maximum value.

[0154] The dielectric weight is set to 0.25 to 0.3. Technical basis: Impedance spectrum drift is extremely sensitive to trace amounts of non-conductive water vapor, which can detect early penetration risks before a short circuit has formed, thus playing an early warning role. Therefore, a medium weight is assigned.

[0155] (Thermodynamic weight) is set to 0.1 to 0.2. Technical basis: Changes in thermal response usually require a large mass of water accumulation (change in heat capacity) to be manifested, and the response speed is relatively slow (minutes). It is mainly used to help confirm the existence of macroscopic water accumulation, so it is given a small weight.

[0156] S503 performs hierarchical judgment and fault type identification. The control terminal 700 will calculate the... Combined with the preset comprehensive judgment threshold (Typically set to 0.8 to 1.0) for comparison, and combined with the case of exceeding the limit in a single dimension, the following hierarchical judgment logic is executed:

[0157] Level 1 Judgment (Electrical Safety Priority Logic): Regardless of the comprehensive index Whether it exceeds the limit depends only on the electrical dimension. The system immediately identifies it as a "serious seal failure (conductive water ingress)". This logic ensures that in the event of a direct water leakage short circuit risk, the system will not miss the diagnosis due to low values ​​of other auxiliary indicators.

[0158] Level 2 Judgment (Comprehensive Trend Warning): If However, the comprehensive index The system identified this as an "early seal failure risk." Although no obvious leakage current was detected at this point, multidimensional characteristics indicated that the internal physical environment had undergone abnormal changes.

[0159] Level 3 Judgment (Fault Physical Morphology Classification): When a failure or warning is detected, the system identifies the fault morphology based on the distribution characteristics of the normalized index.

[0160] Vapor phase permeation type: characterized by Significantly higher than other indicators, while and The reading is low. This indicates that water vapor has entered through the micropores, changing the dielectric constant, but has not yet condensed into conductive water droplets.

[0161] Fluid retention type: characterized by The temperature continues to rise. This indicates that there is one-way liquid permeation and retention at the bottom of the shell, leading to an increase in overall heat capacity.

[0162] S504, Generate Test Conclusion and Termination Control. When any of the above failure judgments is triggered, the control terminal 700 immediately records the timestamp of the failure moment, the corresponding spray pressure parameters, and three-dimensional feature data. The system automatically sends a stop command to the integrated rain test chamber, shuts down the spray mechanism 102, and cuts off the test power supply to the smart meter. Finally, the system marks the sealing performance evaluation result of the smart meter as "unqualified" and writes the specific failure mode (such as "conductive leakage" or "medium moisture") into the test report.

Claims

1. A method for testing the waterproof and dustproof properties of a smart meter, characterized in that, include: An electrical isolation test environment is constructed. The meter under test is connected to the load side of the isolation unit (400). Under dry conditions, the meter under test is controlled to perform low-frequency power modulation. The input power waveform and the internal temperature waveform are recorded synchronously and their phase difference is calculated as the drying reference phase hysteresis angle to establish the thermal response reference transfer function. And control the meter under test to send a frequency sweep signal, record the input impedance modulus within the carrier frequency band, so as to construct a dielectric reference impedance model; Start the spray mechanism (102) of the rain test chamber (100), and control the microcontroller unit of the meter under test to perform high-intensity operation or periodically switch the working frequency to make the total input power fluctuate periodically. Use the heat wave generated by the power fluctuation to make the gas pressure inside the shell change periodically, thereby establishing an alternating pressure difference between the inside and outside of the shell. During spraying, the leakage current vector is synchronously acquired using the vector monitoring unit (500), the channel impedance spectrum is acquired using the impedance analysis unit (600), and the internal temperature data is read through the communication interface unit (200). The leakage current vector is decomposed by phase-sensitive detection to obtain the resistive leakage current component and its change is extracted. The resonant frequency drift of the channel impedance spectrum relative to the dielectric reference impedance model is calculated, and the phase drift of the real-time thermal response relative to the thermal response reference transfer function is calculated. The control terminal (700) maps the resistive leakage current change, the resonant frequency drift and the phase drift to electrical risk index, dielectric risk index and thermodynamic risk index respectively, and obtains a comprehensive sealing failure index by weighted summation of each risk index. The control terminal (700) combines the over-limit situation of the electrical risk index with the comprehensive sealing failure index to classify and determine the sealing performance of the meter under test.

2. The method for testing the waterproof and dustproof properties of a smart meter according to claim 1, characterized in that, The steps for constructing the electrical isolation test environment include: A low-pass filter circuit composed of a power inductor and a safety capacitor is used as an isolation unit (400), and the isolation unit (400) is connected in series between the power supply unit (300) and the power supply input terminal of the meter under test. The cutoff frequency of the isolation unit (400) is set to be higher than the power frequency and lower than the power line carrier communication start frequency of the meter under test. The isolation unit (400) exhibits low impedance pass-through characteristics at the power frequency and high impedance blocking characteristics at the carrier frequency band.

3. The method for testing the waterproof and dustproof properties of a smart meter according to claim 1, characterized in that, The process of causing periodic fluctuations in the total input power specifically involves: The total input power is superimposed with the dynamic drive power amplitude on the power bias; The establishment of an alternating pressure difference inside and outside the shell is specifically achieved by the heat wave causing the temperature of the enclosed gas inside the shell to rise and fall periodically, which causes fluctuations in the internal air pressure according to Charles's Law, thus creating a driving field that alternates between positive and negative pressure differences inside and outside the shell.

4. The method for testing the waterproof and dustproof properties of a smart meter according to claim 1, characterized in that, The steps of performing phase-sensitive detection decomposition on the leakage current vector to obtain the resistive leakage current component and extracting its variation include: Obtain the voltage phasor and total leakage current phasor at the fundamental power frequency; Set the voltage phasor to a reference zero phase and calculate the phase difference between the total leakage current phasor and the voltage phasor; The resistive leakage current component is obtained by multiplying the effective value of the total leakage current phasor by the cosine of the phase difference. The dynamic trend baseline of the resistive leakage current component is calculated using a moving average filtering algorithm, and the real-time resistive current change after detrending is calculated.

5. The method for testing the waterproof and dustproof properties of a smart meter according to claim 1, characterized in that, The step of calculating the resonant frequency shift of the channel impedance spectrum relative to the dielectric reference impedance model includes: The differential impedance spectrum is obtained by performing a spectral subtraction operation between the real-time acquired channel impedance spectrum and the dielectric reference impedance model. Search and identify the peak point of the impedance magnitude that characterizes parallel resonance, and obtain the real-time resonant frequency at the current moment; Calculate the relative frequency shift of the real-time resonant frequency with respect to the inherent resonant frequency under dry conditions; When the relative frequency shift is positive and exceeds the theoretical allowable temperature drift value, it is determined that the dielectric environment inside the casing has changed due to moisture infiltration.

6. The method for testing the waterproof and dustproof properties of a smart meter according to claim 1, characterized in that, The step of calculating the phase shift of the real-time thermal response relative to the thermal response reference transfer function includes: A linear time-invariant thermodynamic system model is constructed by using dynamic power as the system excitation input and internal temperature as the system response output. Extract the power fundamental phase and temperature fundamental phase at the modulation frequency, and calculate the difference between them to obtain the real-time phase hysteresis angle; Calculate the phase drift of the real-time phase lag angle relative to the dry reference phase lag angle.

7. The method for testing the waterproof and dustproof properties of a smart meter according to claim 1, characterized in that, The method of classifying and determining the sealing performance of the meter under test by combining the exceeding of the electrical risk index with the comprehensive sealing failure index specifically includes: If the electrical risk index exceeds the set value, it is directly determined to be a conductive water ingress failure. If the comprehensive seal failure index exceeds the set threshold and the electrical risk index does not exceed the limit, it is determined to be an early seal failure risk.

8. A waterproof and dustproof testing device for smart meters, characterized in that, A method for testing the waterproof and dustproof properties of a smart meter according to any one of claims 1 to 7 includes: Rain test chamber (100), which is equipped with a rotating table (101) for carrying the meter under test and a spray mechanism (102) for applying environmental pressure. The power supply unit (300) has its output connected to the input of the isolation unit (400); The isolation unit (400) is connected in series between the power supply unit (300) and the power supply input terminal of the meter under test; The vector monitoring unit (500) is connected in series in the circuit between the isolation unit (400) and the meter under test; Impedance analysis unit (600) is connected in parallel to the power supply input terminal of the meter under test and is located on the load side of the isolation unit (400); A communication interface unit (200) is connected between the data port of the meter under test and the control terminal (700); The control terminal (700) establishes a communication connection with the above-mentioned units via a bus to perform monitoring and judgment.

9. The smart meter waterproof and dustproof testing device according to claim 8, characterized in that, The isolation unit (400) consists of a power inductor connected in series in the phase line loop and a safety capacitor connected in parallel between the phase line and the neutral line; The vector monitoring unit (500) is a wideband power analyzer used to acquire voltage, current waveforms and phase angles; The impedance analysis unit (600) employs a spectrum receiver or network analyzer to measure the input impedance spectrum within the carrier frequency band. The communication interface unit (200) is an opto-isolated transceiver used to connect the data port of the meter under test to the control terminal (700).

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