An automatic range switching method and system for electrical measuring instruments

Abstract

The application discloses an automatic range switching method and system for an electric measuring instrument, and relates to the technical field of electronic measurement, which comprises the following steps: a range control module analyzes a range instruction and calculates a relay control time sequence of a target range gear; and an execution driving module drives a multi-channel relay group to switch to the target range gear according to the relay control time sequence. The application configures the multi-channel relay group composed of a high-precision relay channel, a power relay channel and a high-voltage relay channel through the execution driving module. The heterogeneous hardware design concept of using special-purpose relays for different measurement requirements enables an instrument to simultaneously meet the precision requirement of micro-parameter measurement and the safety requirement of power and high-voltage measurement, fundamentally breaks through the limitation of the range design of traditional instruments, greatly widens the application scene and comprehensive test capability of the electric measuring instrument, and provides a solid hardware foundation for developing a multifunctional, wide-range general electric measuring platform.

Description

Technical Field

[0001] This invention relates to the field of electronic measurement technology, and in particular to an automatic range switching method and system for electrical measuring instruments. Background Technology

[0002] With the continuous upgrading of demands for refined and efficient electrical parameter measurement in fields such as industrial automation, electronic manufacturing, and power system operation and maintenance, the automated and intelligent adaptation capabilities of various electrical measuring instruments, such as resistance testers, voltmeters, and high-precision current sources or meters, have become core factors determining their measurement accuracy, stability, and testing efficiency. In a wide range of electrical parameter measurements, the dynamic range of the measured signal is extremely wide—from small signals at the microvolt or microampere level to large signals at the kilovolt or ampere level. This requires instruments to possess wide-range, high-precision measurement capabilities. However, traditional range switching technologies, whether initial manual switching or later automatic switching based on fixed thresholds, are insufficient to meet the challenges of complex operating conditions.

[0003] Traditional range switching methods share the following common drawbacks: First, their decision-making logic is simplistic, often relying solely on the instantaneous amplitude of the measured parameter while ignoring the influence of crucial factors such as ambient temperature fluctuations, load power variations, circuit noise, and signal frequency characteristics. For example, in resistance measurement, thermal drift caused by high temperatures may be misinterpreted as a change in resistance, leading to erroneous switching; in AC voltage or current measurement, different frequency response characteristics can also cause inaccurate amplitude measurements. Second, relay switching timing designs are often simple, employing fixed delays and neglecting critical phase information such as the zero-crossing point of the AC signal. This can easily generate arcing during switching, damaging relay contacts, shortening their lifespan, and introducing transient interference, affecting the accuracy of measurement data. Third, the hardware channels lack targeted design, typically using relays of the same specification for different ranges. This leads to errors in contact resistance during small-signal measurements and poses safety risks due to insufficient current-carrying capacity or inadequate insulation withstand voltage during high-current or high-voltage measurements.

[0004] Therefore, it is essential to invent an automatic range switching method and system for electrical measuring instruments to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide an automatic range switching method and system for electrical measuring instruments to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an automatic range switching method for electrical measuring instruments, specifically comprising the following steps:

[0007] S1. The data acquisition module acquires the original electrical characteristic data of the object under test to form an electrical characteristic dataset; the electrical characteristic dataset includes original parameter values, ambient temperature data, and load power values;

[0008] S2. The signal conditioning module performs multi-frequency impedance spectrum scanning on the original parameter values ​​to generate an enhanced characteristic dataset containing phase angle and frequency domain response amplitude.

[0009] S3. The feature analysis module performs time-frequency domain fusion analysis on the electrical characteristic dataset and the enhanced characteristic dataset to obtain the stability coefficient, load characteristic coefficient and environmental drift coefficient. The stability coefficient, load characteristic coefficient and environmental drift coefficient are then input into the adaptive range decision model, and the range switching index is output.

[0010] S4. The model decision module generates range instructions based on the comparison results between the range switching index and the preset threshold range.

[0011] S5. The range control module parses the range command and calculates the relay control timing of the target range.

[0012] S6. The execution drive module drives multiple relay groups to switch to the target range according to the relay control timing.

[0013] Preferably, the original parameter value is the original resistance value R0, including measured values ​​collected at frequencies of 10Hz, 1kHz, and 100kHz; the ambient temperature data includes the contact point temperature value T. j and ambient temperature value T a The load power value P l Including the constant current source output current I s With the voltage V at the end of the resistor to be measured r The product of the base values, after noise suppression processing, is calculated using the following formula: Where f is the frequency of the circuit noise detected in real time, f n This is the preset noise cutoff frequency.

[0014] Preferably, the formula for calculating the stability coefficient is:

[0015] ,

[0016] Where R0 is the original resistance value, Let R0 be the standard deviation over N sampling periods. Let k be the arithmetic mean of R0. R k is the resistance dispersion compensation coefficient. T Here, ΔT is the temperature sensitivity coefficient, and ΔT is the temperature fluctuation value at the contact point, specifically ΔT = max(T j )-min(T j), where T j is the contact point temperature value, max is the maximum value function, and min is the minimum value function.

[0017] Preferably, the calculation formula for the load characteristic coefficient is:

[0018] ,

[0019] where P l is the load power value, P nom is the rated power set value, A f is the response amplitude at the 100 kHz frequency point, f c is the critical frequency set value, ln is the natural logarithm with base e, and e is the natural constant.

[0020] Preferably, the calculation formula for the environmental drift coefficient is:

[0021] ,

[0022] where T a is the environmental temperature value, T max is the maximum allowable operating temperature, T ref is the reference temperature, min is the minimum value function, π is the pi, and cos is the cosine function.

[0023] Preferably, the adaptive range decision model is specifically:

[0024] ,

[0025] where Q is the range switching index, α is the stability coefficient, β is the load characteristic coefficient, γ is the environmental drift coefficient, λ is the smoothing factor, ω1 and ω2 are the dynamic weight coefficients, ω1 + ω2 = 1 and ω1 and ω2 ∈ [0, 1].

[0026] Preferably, the range command is:

[0027] When the range switching index Q > Q1, generate the first - gear range command;

[0028] When the range switching index Q2 ≤ Q ≤ Q1, generate the second - gear range command;

[0029] When the range switching index Q < Q2, generate the third - gear range command;

[0030] The Q1 and Q2 are the preset thresholds of the range switching index.

[0031] Preferably, the relay control timing sequence includes:

[0032] A1. Disconnect the current range relay group;

[0033] A2, Delay , where t d f0 is the relay switching delay time, f0 is the zero-crossing frequency of the phase angle, and π is pi.

[0034] A3. Close the target range relay group;

[0035] A4. Apply pre-charging current P l This represents the load power value.

[0036] Preferably, the multi-channel relay group includes:

[0037] A high-precision relay channel with a contact resistance of less than 10mΩ is used for the first measurement range.

[0038] A power relay channel with a current carrying capacity greater than 3A is used for the second range.

[0039] A high-voltage relay channel with an insulation withstand voltage greater than 300V is used for the third range.

[0040] An automatic range switching system for electrical measuring instruments includes a data acquisition module, a signal conditioning module, a feature analysis module, a model decision module, a range control module, and an execution drive module, wherein:

[0041] The data acquisition module is used to collect the raw electrical characteristic data of the object under test and form an electrical characteristic dataset; the electrical characteristic dataset includes raw parameter values, ambient temperature data and load power values;

[0042] The signal conditioning module is used to perform multi-frequency impedance spectrum scanning on the original parameter values ​​to generate an enhanced characteristic dataset containing phase angle and frequency domain response amplitude.

[0043] The feature analysis module is used to perform time-frequency domain fusion analysis on the electrical characteristic dataset and the enhanced characteristic dataset to obtain the stability coefficient, load characteristic coefficient and environmental drift coefficient. The stability coefficient, load characteristic coefficient and environmental drift coefficient are then input into the adaptive range decision model, and the range switching index is output.

[0044] The model decision module is used to generate range instructions based on the comparison results between the range switching index and the preset threshold range.

[0045] The range control module is used to parse the range command and calculate the relay control timing of the target range.

[0046] The execution drive module is used to drive multiple relay groups to switch to the target range according to the relay control timing.

[0047] The technical effects and advantages of this invention are as follows:

[0048] 1. This invention performs time-frequency domain fusion analysis on the original electrical characteristic dataset and the enhanced characteristic dataset through a feature analysis module, extracts stability, load characteristics and environmental drift coefficients, and inputs them into an adaptive decision model to generate a range switching index. This intelligent decision-making mechanism based on multi-dimensional feature fusion overcomes the limitations of the traditional single-parameter threshold method, can effectively distinguish between the real changes in parameters and environmental interference, and significantly improves the accuracy and intelligent adaptability of electrical measuring instruments in range switching under various complex working conditions.

[0049] 2. After parsing the instruction through the range control module, this invention executes a relay control timing based on dynamic delay and pre-charging current using the phase angle zero-crossing frequency. This timing strategy ensures that the relay contacts operate near the current or voltage zero crossing, greatly suppressing arc discharge, reducing contact wear, and extending the mechanical and electrical life of the relay. At the same time, the pre-charging current smooths the circuit impact at the moment of switching, improving the stability of the entire range switching process and the accuracy of the measurement data. This advantage has universal reliability and safety value for any electrical measuring instrument that uses relays for range switching.

[0050] 3. This invention configures a multi-channel relay group consisting of a high-precision relay channel, a power relay channel, and a high-voltage relay channel through an execution drive module. This heterogeneous hardware design concept, which uses dedicated relays for different measurement needs, enables a single instrument to simultaneously meet the accuracy requirements of microparameter measurement and the safety requirements of power and high-voltage measurement. This fundamentally breaks through the limitations of traditional instrument range design, greatly expands the application scenarios and comprehensive testing capabilities of electrical measuring instruments, and provides a solid hardware foundation for developing a multi-functional, wide-range general-purpose electrical measurement platform. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0052] Figure 2 This is a timing diagram of the relay of the present invention.

[0053] Figure 3 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0054] The technical solutions of 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.

[0055] This invention provides, for example Figure 1 The automatic range switching method for electrical measuring instruments shown includes the following steps:

[0056] S1. The resistance acquisition module acquires the original electrical characteristic data of the object under test to form an electrical characteristic dataset; the electrical characteristic dataset includes original parameter values, ambient temperature data, and load power values;

[0057] Furthermore, in the above technical solution, the original parameter value is the original resistance value R0, including measured values ​​collected at frequencies of 10Hz, 1kHz, and 100kHz; the ambient temperature data includes the contact point temperature value T. j and ambient temperature value T a The load power value P l Including the constant current source output current I s With the voltage V at the end of the resistor to be measured r The product of the base values, after noise suppression processing, is calculated using the following formula: Where f is the frequency of the circuit noise detected in real time, f n This is the preset noise cutoff frequency.

[0058] It should be noted that the original resistance value R0 is obtained through a constant current source excitation circuit combined with a four-wire measurement method. Specifically, a precision constant current source applies an excitation current with an adjustable frequency of 10Hz, 1kHz, and 100kHz to the resistor under test, while a 24-bit high-precision ADC synchronously acquires the voltage V at the terminal of the resistor under test. r According to Ohm's law, R0=V r / I s Real-time calculation of resistance value, where the constant current source output current I s The signal is converted into a voltage signal by a 0.1Ω precision sampling resistor connected in series in the excitation circuit, amplified by the INA128 instrumentation amplifier, and then input to the ADC.

[0059] The contact point temperature value T j The temperature data was collected using a Pt1000 platinum resistance temperature sensor mounted on the base of the test probe. The sensor formed a thermally conductive connection with the probe through an alumina ceramic substrate. A three-wire compensation circuit powered by a constant current source was used to eliminate the influence of wire resistance. The raw data was acquired by a 24-bit Σ-Δ ADC at a sampling rate of 10 times / second, and the resistance value was converted into a temperature value by a lookup table method.

[0060] The ambient temperature value T aThe system is detected by an NTC thermistor installed in the ventilation vent inside the equipment chassis. This sensor is physically isolated from the metal heat sink and covered with a dust filter. The resistance change is converted into a voltage signal through a voltage divider circuit. The ADC sampling data is processed by a moving average filtering algorithm. The ambient temperature value is updated every 30 seconds. The measurement range covers the industrial temperature range of -40℃ to +85℃.

[0061] The real-time detected circuit noise frequency f is transmitted to V via a high-speed ADC. r After sampling the signal at 256 points, the main noise frequency component is obtained by applying FFT spectrum analysis. Specifically, the ARM processor performs Hanning window weighting processing and calculates the power spectral density, automatically identifying the peak positions of 50Hz or 60Hz power frequency and high-frequency switching noise, and the detection frequency range covers 10Hz~100kHz.

[0062] The preset noise cutoff frequency f n Dynamically set based on real-time spectrum analysis results: When the main noise frequency component is detected as 50Hz or 60Hz power frequency interference, set f n =200Hz; When high-frequency switching noise exists, i.e., >10kHz, set f n =20kHz; in other scenarios, it is adaptively adjusted according to the point where the noise power spectral density drops by 3dB, and constrained within the range of 200Hz to 20kHz, so as to achieve the optimal balance between noise suppression and signal fidelity.

[0063] S2. The signal conditioning module performs multi-frequency impedance spectrum scanning on the original resistance value to generate an enhanced characteristic dataset containing phase angle and frequency domain response amplitude.

[0064] The signal conditioning module executes by sequentially applying excitation currents at three characteristic frequencies—10Hz, 1kHz, and 100kHz—to the resistor under test using a programmable constant current source. A four-wire measurement method combined with a 24-bit high-precision ADC is used to synchronously acquire the resistor terminal voltage signal at each frequency. Digital phase-locked loop (PLL) technology is applied to the acquired time-domain voltage signal to extract orthogonal components with the same frequency as the excitation current, calculating the phase angle data for each frequency point with a phase resolution of 0.01 degrees. Simultaneously, a 256-point FFT spectrum analysis is performed on the voltage signal, and the power spectral density is calculated after Hanning window weighting to obtain the response amplitude at characteristic frequencies within the 10Hz to 100kHz frequency band. Finally, the phase angles at the three frequencies and the corresponding frequency domain response amplitudes are integrated into structured data to form an enhanced characteristic dataset. The phase angle data characterizes the dielectric properties of the resistive material, and the frequency domain response amplitude reveals the nonlinear characteristics of impedance variation with frequency. The dataset is stored in matrix form and output to the feature analysis module.

[0065] S3. The feature analysis module performs time-frequency domain fusion analysis on the electrical characteristic dataset and the enhanced characteristic dataset to obtain the stability coefficient, load characteristic coefficient and environmental drift coefficient. The stability coefficient, load characteristic coefficient and environmental drift coefficient are then input into the adaptive range decision model, and the range switching index is output.

[0066] Furthermore, in the above technical solution, the formula for calculating the stability coefficient is:

[0067] ,

[0068] in, Let R0 be the standard deviation over N sampling periods. Let k be the arithmetic mean of R0. R k is the resistance dispersion compensation coefficient. T Here, ΔT is the temperature sensitivity coefficient, and ΔT is the temperature fluctuation value at the contact point, specifically ΔT = max(T j )-min(T j ), where T j Let be the contact point temperature value, max be the maximum value function, and min be the minimum value function.

[0069] What needs to be known is that max(T) j (T) represents the contact point temperature value over N consecutive sampling periods. j The maximum value, min(T) j (T) represents the contact point temperature value over N consecutive sampling periods. j The minimum value;

[0070] The resistance dispersion compensation coefficient k R The value is set based on the expected measurement accuracy of the measured resistance and the material properties, and is preferably set to k. R =0.003, this value was determined through calibration after repeated measurements of a standard resistor and analysis of its discrete distribution characteristics. It is used to effectively balance the inherent discreteness of the resistor with respect to the standard deviation of the measurement system noise in the calculation of the stability coefficient. The impact;

[0071] The temperature sensitivity coefficient k T The value is set by comprehensively considering the temperature coefficient of the resistor under test and the thermal conductivity of the contact point, and is preferably set to k. T =0.05Ω / ℃. This value is obtained by measuring the ratio of the temperature fluctuation ΔT at the contact point to the resistance drift through a thermal shock test. It is used to quantify the equivalent impact of unit temperature fluctuation on the stability of resistance measurement and to ensure that changes in ambient temperature are accurately compensated in the stability coefficient.

[0072] Furthermore, in the above technical solution, the formula for calculating the load characteristic coefficient is:

[0073] ,

[0074] Among them, P l P represents the load power value. nom A is the rated power setting value. f f is the response amplitude at a frequency of 100kHz. c The critical frequency is set, where ln is the logarithm to the base e, and e is the natural constant.

[0075] It is important to know that the response amplitude A at the 100kHz frequency point is... f Impedance spectrum is obtained through multi-frequency scanning using a signal conditioning module: a programmable constant current source applies an excitation current at a characteristic frequency of 100kHz to the resistor under test, and a four-wire measurement method combined with a 24-bit ADC is used to acquire the time-domain signal of the resistor terminal voltage; digital phase-locked loop technology is applied to the acquired data to extract the orthogonal component with the same frequency as the excitation current, and then the power spectral density is calculated by 256-point FFT spectrum analysis with Hanning window weighting; finally, the response amplitude at the characteristic frequency of 100kHz is extracted from the 10Hz-100kHz frequency band. This amplitude data, together with the phase angle, constitutes an enhanced characteristic dataset, which is used to reveal the high-frequency impedance characteristics and nonlinear load effects of the resistor.

[0076] The rated power setting value P nom The safe operating area of ​​the resistor under test is determined based on its characteristics, specifically the operating area of ​​the resistor at a reference temperature T. ref The maximum allowable power dissipation under the specified conditions must be set by comprehensively considering the physical dimensions of the resistor under test, the thermal capacity of the material, and the thermal conductivity characteristics of the test environment; preferably, P nom The value should not exceed 70% of the nominal power value specified in the resistor manufacturer's datasheet, and should be used in high-temperature environments, i.e., T. a At temperatures above 60℃, the adjustment factor needs to be multiplied by P. nom Dynamic adjustment, with an adjustment coefficient of k. derate =1-0.015×(T) a -25), to ensure that the resistance testing process is always within a safe operating range;

[0077] The critical frequency setting value f c The setting is based on the frequency response characteristics of the resistor under test, calibrated through impedance spectrum scanning experiments. Specifically, multi-frequency excitation is performed in the 10Hz to 100kHz frequency band, and the turning point where the impedance amplitude significantly decreases with increasing frequency is identified. This value is preset to a typical value, such as 20kHz, based on the dielectric constant of the resistor material and structural design parameters. The calibration is performed by verifying the frequency position where the impedance amplitude drops by 3dB on a standard resistor sample to ensure that the influence of high-frequency noise and parasitic parameters on the nonlinear characteristics of the resistor is effectively quantified in the load characteristic coefficient, thereby optimizing the adaptability of the range decision model.

[0078] Furthermore, in the above technical solution, the formula for calculating the environmental drift coefficient is:

[0079] ,

[0080] Among them, T a T represents the ambient temperature value. max To allow for the highest operating temperature, T ref Let be the reference temperature, min be the minimum value function, π be the value of pi, and cos be the cosine function.

[0081] It should be noted that the maximum allowable operating temperature T max Based on the core electronic components of the intelligent resistance tester, including the multi-channel relay group, signal conditioning circuit, and temperature sensor, the safe operating boundaries are set. Specifically, these boundaries are determined by combining the highest junction temperature parameters in the specifications provided by the component suppliers with the results of the internal thermal simulation model and high-temperature aging tests. This temperature value must ensure that the contact resistance of the relay contacts, the heat resistance of the insulation material, and the operational amplifier drift in the signal conditioning circuit are all within a controllable range. It also considers the thermal resistance characteristics of the equipment's heat dissipation structure and the heat dissipation capacity of the forced air cooling system. A typical value is set at 85℃, which is used as the critical upper limit for temperature standardization in the calculation of the environmental drift coefficient. When the ambient temperature T... a Approaching T max When the environmental drift coefficient γ approaches 0, the range decision model is triggered to switch to the high insulation withstand voltage range first to ensure test safety.

[0082] The reference temperature T ref The value is determined based on the standard test conditions of the measured resistance and the thermal design parameters of the equipment itself. Specifically, it needs to be related to the contact point temperature T. j The measurement reference and rated operating environment of the resistance tester, where T ref As a normalized benchmark for the environmental drift coefficient, its typical value is set at 25℃. This value must also be consistent with the calibration benchmark point of the equipment's temperature sensor, and its performance at T... is verified through thermal equilibrium experiments. max -T ref The linearity error within the temperature difference range is less than ±0.5%, when the ambient temperature T a Approaching T ref The environmental drift coefficient γ approaches 1, ensuring the stability of the range decision model under the baseline operating conditions.

[0083] Furthermore, in the above technical solution, the adaptive range decision model is specifically as follows:

[0084] ,

[0085] Among them, Q is the range switching index, α is the stability coefficient, β is the load characteristic coefficient, γ is the environmental drift coefficient, λ is the smoothing factor, ω1 and ω2 are dynamic weight coefficients, ω1 + ω2 = 1 and ω1 and ω2 ∈ [0, 1].

[0086] It should be noted that the dynamic weight coefficients ω1 and ω2 are set as ω1 = 0.7 and ω2 = 0.3 when the feature analysis module detects that the stability coefficient α < 0.9 or the contact point temperature fluctuation value ΔT > 5°C, so as to strengthen the weights of resistance stability and temperature drift compensation in range decision-making; when the load characteristic coefficient β < 0.8 or the response amplitude A f is 30% lower than the reference value at the 100 kHz frequency point, set ω1 = 0.4 and ω2 = 0.6, focusing on the influence of load nonlinear effects and high-frequency characteristics on range decision-making; in normal working conditions, that is, α ≥ 0.9, β ≥ 0.8 and ΔT ≤ 5°C, an equal configuration of ω1 = 0.5 and ω2 = 0.5 is adopted.

[0087] S4. The model decision module generates a range command according to the comparison result between the range switching index and the preset threshold interval;

[0088] Furthermore, in the above technical solution, the range command is:

[0089] When the range switching index Q > Q1, a first-range command is generated;

[0090] When the range switching index Q2 ≤ Q ≤ Q1, a second-range command is generated;

[0091] When the range switching index Q < Q2, a third-range command is generated.

[0092] It should be noted that Q1 and Q2 are preset thresholds for the range switching index. The setting of their values needs to be optimized by comprehensively considering the resistance measurement range, test accuracy requirements, and load power characteristics, and is specifically determined based on the association between the range switching index Q output by the adaptive range decision model and the physical characteristics of the three range gears. Among them, Q1 is the demarcation threshold between the first range and the second range, and its setting needs to meet the error constraint conditions for high-precision small-resistance measurement: when Q > Q1, the system switches to a high-precision relay channel with a contact resistance less than 10 mΩ. This threshold needs to ensure that when the resistance value is lower than 10 Ω and the load power fluctuates dynamically, the combined calculation result of the stability coefficient α and the load characteristic coefficient β can accurately trigger the high-sensitivity range; Q2 is the demarcation threshold between the second range and the third range, and its setting needs to adapt to the safe switching boundary between the power relay and the high-voltage relay: when Q < Q2, the system automatically enables the high-voltage relay channel with an insulation withstand voltage greater than 300 V. This threshold needs to ensure that when the resistance value is higher than 1 kΩ or there is a high-voltage test requirement, the downward trend of the environmental drift coefficient γ can timely trigger the high-isolation range. Preferably, Q1 and Q2 are dynamically calibrated through a calibration experiment: under the condition of a reference temperature of 25 °C, standard resistance samples of 10 Ω ± 1% and 1 kΩ ± 1% are respectively used, combined with a step change test of the load power from 10% to 90% of the rated value. With the constraint conditions that the measurement error during the range switching process does not exceed ±0.2% and the relay switching arc energy is lower than 5 mJ, the initial values of Q1 = 0.85 ± 0.03 and Q2 = 0.65 ± 0.03 are determined through an iterative optimization algorithm, and a dynamic compensation of ±0.05 is performed in actual applications according to the environmental temperature fluctuation range (-40 °C to +85 °C) and the noise spectrum characteristics (10 Hz to 100 kHz), so as to achieve the safe and reliable switching of the multi-channel relay group while ensuring the test accuracy;

[0093] The first range command corresponds to the first range, specifically the 10 mΩ to 10 Ω range gear;

[0094] The second range command corresponds to the second range, specifically the 10 Ω to 1 kΩ range gear;

[0095] The third range command corresponds to the third range, specifically the 1 kΩ to 100 kΩ range gear.

[0096] S5. The range control module analyzes the range command and calculates the relay control timing of the target range gear;

[0097] Further, in the above technical solution, the relay control timing is as Figure 2 shown, including:

[0098] A1. Disconnect the current range relay group;

[0099] A2. Delay , where t d f0 is the relay switching delay time, f0 is the zero-crossing frequency of the phase angle, and π is pi.

[0100] A3. Close the target range relay group;

[0101] A4. Apply pre-charging current .

[0102] It should be noted that the acquisition of the zero-crossing frequency f0 of the phase angle is achieved through the signal conditioning module: this module performs continuous frequency point analysis on the phase angle data obtained in the multi-frequency impedance spectrum scan. During the application of step scan excitation from 10Hz to 100kHz, it detects in real time the critical frequency position where the phase angle between adjacent frequency points changes from a positive value to a negative value. Specifically, a linear interpolation algorithm is used to calculate the accurate frequency value of the zero-crossing point between two consecutive frequency points where the phase angle sign changes.

[0103] S6. The execution drive module drives multiple relay groups to switch to the target range according to the relay control timing.

[0104] Furthermore, in the above technical solution, the multi-channel relay group includes:

[0105] A high-precision relay channel with a contact resistance of less than 10mΩ is used for the first measurement range.

[0106] A power relay channel with a current carrying capacity greater than 3A is used for the second range.

[0107] A high-voltage relay channel with an insulation withstand voltage greater than 300V is used for the third range.

[0108] It is important to know that for the first measurement range, a high-precision magnetic latching relay with a contact resistance of less than 10mΩ is used to ensure that the contact voltage drop does not affect the accuracy of micro-resistance measurement; for the second measurement range, a power relay with a current carrying capacity of more than 3A is selected, and its silver-plated contacts and heat dissipation substrate design can withstand the maximum output current of the constant current source; for the third measurement range, a high-voltage reed relay with an insulation withstand voltage of more than 300V is configured, and its ceramic sealing structure provides sufficient dielectric strength to isolate high-voltage test signals.

[0109] The high-precision relay is a Panasonic TQ2-5V magnetic latching relay, whose coil drive circuit is connected in series in the low-power output channel of the range control module; the power relay is a TE EA2-12NJ power relay, driven by a Darlington transistor array and equipped with an RC snubber circuit; the high-voltage relay is a Standex-Meder SIL05-1A72 reed relay, which avoids high-voltage crosstalk through optocoupler isolation control.

[0110] An automatic range switching system for electrical measuring instruments, such as Figure 3 As shown, it includes a data acquisition module, a signal conditioning module, a feature analysis module, a model decision module, a range control module, and an execution drive module, wherein:

[0111] The data acquisition module is used to collect the raw electrical characteristic data of the object under test and form an electrical characteristic dataset; the electrical characteristic dataset includes raw parameter values, ambient temperature data and load power values;

[0112] The signal conditioning module is used to perform multi-frequency impedance spectrum scanning on the original parameter values ​​to generate an enhanced characteristic dataset containing phase angle and frequency domain response amplitude.

[0113] The feature analysis module is used to perform time-frequency domain fusion analysis on the electrical characteristic dataset and the enhanced characteristic dataset to obtain the stability coefficient, load characteristic coefficient and environmental drift coefficient. The stability coefficient, load characteristic coefficient and environmental drift coefficient are then input into the adaptive range decision model, and the range switching index is output.

[0114] The model decision module is used to generate range instructions based on the comparison results between the range switching index and the preset threshold range.

[0115] The range control module is used to parse the range command and calculate the relay control timing of the target range.

[0116] The execution drive module is used to drive multiple relay groups to switch to the target range according to the relay control timing.

[0117] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automatic range switching method for an electrical measuring instrument, characterized in that, Specifically comprising the following steps: S1, the data acquisition module collects the original electrical characteristic data of the object to be measured to form an electrical characteristic data set; the electrical characteristic data set includes original parameter values, environmental temperature data and load power values; S2, the signal conditioning module performs multi-frequency point impedance spectrum scanning on the original parameter values to generate an enhanced characteristic data set containing phase angles and frequency domain response amplitudes; S3, the feature analysis module performs time-frequency domain fusion analysis on the electrical characteristic data set and the enhanced characteristic data set to obtain stability coefficients, load characteristic coefficients and environmental drift coefficients, and inputs the stability coefficients, load characteristic coefficients and environmental drift coefficients into an adaptive range decision model to output a range switching index; The calculation formula of the stability coefficient is: ， wherein R0 is an original resistance value, is a standard deviation of R0 in N sampling periods, is an arithmetic mean of R0, k R is a resistance dispersion compensation coefficient, k T is a temperature sensitivity coefficient, and ΔT is a contact point temperature fluctuation value, specifically ΔT = max(T j ) - min(T j ), wherein T j is a contact point temperature value, max is a maximum value function, and min is a minimum value function; S4, the model decision module generates a range instruction according to the comparison result of the range switching index and the preset threshold interval; S5, the range control module analyzes the range instruction and calculates the relay control timing of the target range gear; S6, the execution driving module drives the multi-way relay group to switch to the target range gear according to the relay control timing.

2. An automatic range switching method for an electrical measuring instrument according to claim 1, characterized in that, The original parameter value is an original resistance value R0, including measurement values collected at 10 Hz, 1 kHz, and 100 kHz frequencies; the environmental temperature data includes a contact point temperature value T j and an environmental temperature value T a ; the load power value P l includes a constant current source output current I s and a product of a to-be-measured resistance end voltage V r , and is subjected to noise suppression processing, and the calculation formula is: , wherein f is a real-time detected circuit noise frequency, and f n is a preset noise cutoff frequency.

3. An automatic range switching method for an electrical measuring instrument according to claim 1, characterized in that, The calculation formula of the load characteristic coefficient is: ， where P l is the load power value, P nom is the rated power set value, A f is the response amplitude at 100 kHz frequency point, f c is the critical frequency set value, ln is the logarithm with base e, and e is the natural constant.

4. An automatic range switching method for an electrical measuring instrument according to claim 1, characterized in that, The calculation formula of the environmental drift coefficient is: ， where T a is the ambient temperature value, T max is the maximum allowable operating temperature, T ref is the reference temperature, min is the minimum function, and π is the circular constant, and cos is the cosine function.

5. An automatic range switching method for an electrical measuring instrument according to claim 1, characterized in that, The adaptive range decision model is specifically: ， Wherein, Q is the range switching index, α is the stability coefficient, β is the load characteristic coefficient, γ is the environmental drift coefficient, λ is the smoothing factor, ω1 and ω2 are dynamic weight coefficients, ω1+ω2=1 and ω1 and ω2∈[0, 1].

6. An automatic range switching method for an electrical measuring instrument according to claim 1, characterized in that, The range instruction is: When the range switching index Q>Q1, a first-gear range instruction is generated; When the range switching index Q2≤Q≤Q1, a second-gear range instruction is generated; When the range switching index Q<Q2, a third-gear range instruction is generated; Q1 and Q2 are preset threshold values of the range switching index.

7. An automatic range switching method for an electrical measuring instrument according to claim 1, characterized in that, The relay control timing includes: A1, open the current range relay group; A2, delay time where t d is the relay switching delay time, f0is the phase angle zero-crossing frequency, and π is the circular constant. A3, close the target range relay group; A4, applying a pre-charge current , P l is a load power value.

8. An automatic range switching method for an electrical measuring instrument according to claim 1, characterized in that, The multi-way relay group contains: High-precision relay channels with contact resistance less than 10 mΩ for the first-gear range; Power relays with current-carrying capacity greater than 3 A for the second-gear range; High-voltage relays with insulation withstand voltage greater than 300 V for the third-gear range.

9. An automatic range switching system for an electrical measuring instrument, applied to an automatic range switching method for an electrical measuring instrument according to any one of claims 1 to 8, characterized in that, It includes a data acquisition module, a signal conditioning module, a feature analysis module, a model decision module, a range control module and an execution driving module, wherein: The data acquisition module is used to collect the original electrical characteristic data of the object to be measured to form an electrical characteristic data set; the electrical characteristic data set includes original parameter values, environmental temperature data and load power values; The signal conditioning module is used to perform multi-frequency point impedance spectrum scanning on the original parameter values to generate an enhanced characteristic data set containing phase angles and frequency domain response amplitudes; The feature analysis module is used to perform time-frequency domain fusion analysis on the electrical characteristic data set and the enhanced characteristic data set to obtain stability coefficients, load characteristic coefficients and environmental drift coefficients, and input the stability coefficients, load characteristic coefficients and environmental drift coefficients into an adaptive range decision model to output a range switching index; The model decision module is used to generate a range instruction according to the comparison result of the range switching index and the preset threshold interval; A range control module is configured to parse the range instruction and calculate a relay control timing sequence for the target range gear. An execution driving module is configured to drive the multi-way relay group to switch to the target range gear according to the relay control timing sequence.

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