1934results about "Voltage measurements only" patented technology

A system-side harmonic impedance estimation method and apparatus, and a storage medium and an electronic device. The method comprises: acquiring an h-th harmonic parameter equivalent circuit simplified on the basis of power grid characteristics, h being a positive integer greater than or equal to 2 (S1); on the basis of the h-th harmonic parameter equivalent circuit, establishing a system-side harmonic impedance estimation mathematical model (S2); acquiring amplitude and phase data of a harmonic voltage and a harmonic current at a PCC (S3); dividing the amplitude data of the harmonic voltage at the PCC into several stable intervals (S4); on the basis of the amplitude and phase data of the harmonic voltage and the harmonic current in the several stable intervals, establishing a variable coefficient regression model between a harmonic voltage phasor and a harmonic current phasor (S5); selecting an optimal window width of a kernel function of the variable coefficient regression model (S6); and calculating a system harmonic impedance on the basis of the variable coefficient regression model and the optimal window width (S7).

A high-altitude electrode discharge voltage prediction method and system, a device and a medium, relating to the technical field of electrode discharge. The method comprises: acquiring a measured dataset of a high-altitude true electrode, and performing normalization processing and data partitioning on the measured dataset in a preset selection ratio to generate an initial training set and a test set; on the basis of the degree of influence between a feature variable and a target variable in the initial training set, constructing a target training set; carrying out model construction on the basis of a support vector regression method and an ant lion optimization algorithm in combination with the target training set, to generate an intermediate intelligent model; using the test set to test the intermediate intelligent model, and determining a target intelligent model; and inputting the measured dataset into the target intelligent model for discharge voltage calculation, to generate discharge voltage prediction data corresponding to the high-altitude true electrode. By means of the ant lion optimization intelligent algorithm and the target intelligent model, the accuracy of prediction results can be improved.

The invention provides a multi-band radio frequency power amplifier dynamic range adaptive test method and a system thereof. The method comprises the following steps: acquiring an output signal frequency spectrum of a tested radio frequency power amplifier, extracting characteristic frequency points including a center frequency and a bandwidth, matching the characteristic frequency points with a preset frequency band database, and automatically loading a test scheme of a corresponding frequency band. According to the method, the frequency bands are automatically matched through spectrum sensing, the test scheme is loaded, the multi-frequency-band characteristics can be rapidly adapted without manual parameter configuration, index missing test is avoided, and the switching efficiency is improved; dynamically optimizing test parameters by using a genetic algorithm, and accurately capturing a nonlinear distortion critical point while balancing coverage and efficiency; by combining multi-dimensional signal analysis and a deep learning model, the problem of missing detection of traditional single-domain analysis is solved, and the abnormal signal recognition capability is remarkably enhanced; through linear model correction, impedance dynamic matching and index threshold iteration, full automation and high precision of the test are realized, the environmental interference influence is effectively reduced, and a self-adaptive test system is constructed.

The invention discloses an equipment fault diagnosis method and system based on a large electric power model, and the method comprises the steps: collecting and fusing voltage and current waveform data and alarm log information in a short time window before and after a fault moment, achieving the context integration of a multi-dimensional feature vector through multi-level feature coding and semantic embedding, and achieving the fault diagnosis of a large electric power model. And relevant knowledge fragment retrieval is carried out in combination with a power field knowledge base. On the basis, relevant knowledge fragments, voltage-current waveform fusion feature coding vectors and fault alarm key information semantic embedding coding feature vectors are jointly embedded into a preset Prompt template and then are input into a diagnosis engine based on large model driving, so that intelligent analysis and report generation of fault types, reasons and key features are realized. Through the mode, the limitation of dependence on single data or rules traditionally is broken through, the accuracy, automation and interpretability of fault diagnosis under complex working conditions are remarkably improved, and a solid support is provided for intelligent and high-reliability equipment operation and maintenance.

The invention provides a distributed photovoltaic access distribution network voltage fluctuation evaluation method, medium and system, and belongs to the technical field of distributed photovoltaic, and the method comprises the steps: firstly collecting the parameters of a photovoltaic system and a distribution network, and building a power grid response equation set considering the parameters; more parameter samples are obtained through data augmentation and expansion, and indexes such as voltage, power and harmonic waves of each node are calculated according to the response equation set. Constructing a voltage fluctuation evaluation index matrix including voltage deviation, fluctuation, harmonic waves, short-circuit capacity change and the like; and decomposing the matrix by adopting singular value decomposition to obtain a voltage stability and fluctuation evaluation matrix, and finally calculating a voltage stability index and a fluctuation index. If the voltage fluctuation evaluation index exceeds a preset threshold value, an alarm is triggered, and decision support is provided for distribution network planning and operation. According to the invention, the technical problems of short evaluation time scale and difficulty in capturing the dynamic characteristics of voltage fluctuation in the evaluation of the distributed photovoltaic access distribution network in the prior art are solved.

The invention provides a power network state recognition method and system based on data feature analysis, which are used for continuously improving the power network state recognition precision through a data-driven optimization mechanism, providing full-process intelligent decision support for power grid operation and maintenance, and effectively promoting the power network to be converted from a passive operation and maintenance mode to an active prevention and control mode. The method comprises the following steps: acquiring a multi-dimensional power data set of a target power network, performing dynamic feature extraction processing on the multi-dimensional power data set to generate a power network operation feature set, and inputting the power network operation feature set into a debugged power state recognition model, and carrying out conjoint analysis on the voltage fluctuation characteristics, the current phase deviation characteristics and the equipment health degree characteristics through a power state identification model to generate a power network state classification result, and generating a network operation and maintenance strategy according to the power network state classification result. And the network operation and maintenance strategy is sent to the power dispatching terminal so as to activate corresponding equipment maintenance operation or load adjustment operation.

The invention discloses a new energy automobile charging station abnormity monitoring method and system, and the method comprises the steps: collecting voltage data of each charging pile measurement point of a new energy automobile charging station, and obtaining a voltage fluctuation state feature value of each charging pile measurement point and a clustering region of each charging pile, calculating a local voltage fluctuation characteristic value of each charging pile clustering region, determining a voltage fluctuation similar region of each charging pile clustering region, obtaining a region voltage fluctuation synthesis vector of each charging pile clustering region, calculating a charging abnormal factor of each charging pile clustering region, determining each charging abnormal region, and obtaining a charging abnormal result of each charging abnormal region; and obtaining an abnormal score of each charging pile measurement point in each charging abnormal area so as to evaluate an abnormal degree of each charging pile measurement point. According to the new energy vehicle charging station abnormity monitoring method and system provided by the embodiment of the invention, the efficiency of monitoring the abnormity of the new energy vehicle charging station is improved.

The invention relates to the technical field of substations, and discloses a safety assessment system and method for a main grounding grid of a substation. The method comprises the following steps: arranging a multi-point potential gradient sensor for a main grounding grid of a power transmission and transformation project transformer substation and carrying out synchronous measurement to obtain an original potential gradient data set; performing effective signal and interference signal distinguishing processing on the original potential gradient data set to obtain potential distribution information of the transformer substation grounding grid; establishing a transformer substation grounding grid dynamic impedance model for fault current analysis to obtain a whole-process potential distribution diagram including an initial stage, a steady-state stage and a recovery stage; and performing security risk assessment based on the whole-process potential distribution diagram, and outputting a security risk area report. According to the invention, effective measurement signals and interference signals are effectively distinguished, reliability and accuracy of grounding grid potential measurement data in a complex electromagnetic environment are significantly improved, and accurate positioning of a risk area and effective tracking of a hazard source are realized.

The invention discloses a capacitive voltage transformer for a gas insulated substation, which comprises a capacitive voltage divider and an electromagnetic unit, the capacitive voltage divider comprises a high-voltage capacitor C1 and a medium-voltage capacitor, the medium-voltage capacitor comprises a medium-voltage capacitor C21 and an externally connected medium-voltage capacitor C22, and the capacitance of the medium-voltage capacitor C22 is greater than that of the medium-voltage capacitor C21; the electromagnetic unit is connected with the capacitive voltage divider, an intermediate transformer and a compensation reactor are arranged in the electromagnetic unit, a full-shielding high-voltage shielding cover is arranged outside a high-voltage coil of the intermediate transformer, a damper and an overvoltage protector are arranged outside the electromagnetic unit, and the damper and the overvoltage protector are placed in an external junction box. The problem that in the prior art, an extra-high voltage transformer is low in lightning impulse overvoltage tolerance capacity is solved, the impulse overvoltage tolerance capacity is improved, and the breakdown risk is reduced.

The invention relates to the technical field of electricity metering anomaly monitoring, and provides a distributed resource access-oriented lightweight electricity metering anomaly monitoring method, which comprises the following steps of: acquiring electrical data and environment associated data of distributed access points at an edge side, and constructing a fluctuation fingerprint feature vector; when it is detected that the fluctuation fingerprint feature vector meets a preset fluctuation triggering condition, based on Pearson correlation analysis between the electrical data and the environment associated data, performing decoupling and elimination on false anomalies caused by environmental factors to obtain a fluctuation fingerprint feature vector of non-environmental suspicious anomalies; based on historical normal operation data, constructing a normal working condition mode library by adopting a clustering analysis method, and determining a feature center and a dynamic safety radius of each normal working condition mode; and calculating the feature distance between the non-environmental suspicious abnormal fluctuation fingerprint feature vector and each normal working condition feature center at the edge side, and judging whether the electricity consumption metering is abnormal or not according to the relationship between the feature distance and the dynamic safety radius.

The invention discloses a deteriorated insulator detection device, method and device based on a three-dimensional radial electric field trend. Relates to the field of power equipment, solves the problem of angle limitation of detection of degraded insulators, and provides a controller for controlling flight equipment to fly along an axis to ensure that a voltage signal acquired by a three-dimensional electric field sensor is matched with actual electric field distribution of an insulator string, so as to meet detection requirements of insulator strings with different inclination angles. The three-dimensional electric field sensor collects an electric field signal and converts the electric field signal into a voltage signal, and the controller receives the voltage signal sent by the three-dimensional electric field sensor and judges whether a deteriorated insulator exists in the insulator string. Through non-contact detection, the problems of potential safety hazards and low efficiency in a traditional detection method are avoided, and the accuracy and safety of detection are improved. And the workload of manual climbing and measurement is reduced. Power failure detection is not needed, and the influence and risk on power grid operation in the detection process are reduced.

The invention relates to the field of power distribution network ground fault accurate judgment, and discloses a power distribution network ground fault accurate positioning method based on traveling wave detection and artificial intelligence, which comprises the following steps: (a) collecting a power distribution network traveling wave voltage signal through a multi-node synchronous sensor array, and generating a preprocessing signal through baseline correction and wavelet threshold denoising; (b) constructing a Gaussian random field model of line resistance, inductance and capacitance, and simulating a traveling wave propagation process in combination with a nonlinear wave equation; and (c) defining Finsler measurement on the traveling wave signal manifold, and separating the aliasing mode by minimizing path integration. According to the invention, the technical scheme of multi-node synchronous signal acquisition and self-adaptive preprocessing is adopted, so that the effect of eliminating coupling of power frequency interference and high-frequency noise is achieved. Compared with a scheme depending on a single sensor and a fixed filtering threshold in the prior art, the method solves the defect that the wave head time difference extraction is not accurate due to asynchronous sampling.

The invention relates to a PCB over-temperature protection device, method and equipment, and relates to the technical field of servers, the device comprises at least one control circuit and a complex programmable logic device CPLD, and the control circuit comprises a thermistor and at least one voltage comparator; the thermistor is arranged in a monitoring area of a printed circuit board (PCB) and is used for converting the temperature of the monitoring area into a target voltage signal; the forward input end of the voltage comparator receives a target voltage signal, the reverse input end of the voltage comparator receives a reference voltage signal corresponding to the voltage comparator, and the voltage comparator is used for outputting a high level when the target voltage signal is higher than the reference voltage signal; the CPLD comprises a plurality of input pins respectively corresponding to the voltage comparators, each input pin is electrically connected with the output end of the corresponding voltage comparator, and the CPLD is used for triggering over-temperature protection operation corresponding to the input pin when the high level is received through the input pin, so that the timeliness of PCB over-temperature protection is improved.

Method for estimating the voltage value relating to a live element uses five capacitors, wherein a first capacitor has its first pole connected to said live element; a second capacitor has its first pole connected to said live element; a third capacitor has its first pole connected to the second pole of the first capacitor and its second pole connected to ground; a fourth capacitor has its first pole connected to the second pole of the second capacitor and its second pole connected to the first pole of a fifth capacitor. The voltage value is estimated using: 1) a voltage value relating to a first node positioned along the conducting wire that connects the first capacitor to the third capacitor 2) a voltage value relating to a second node positioned along the conducting wire that connects the fourth capacitor to the fifth capacitor; 3) a capacitance value of the third capacitor; 4) a capacitance value of the fourth capacitor; 5) a capacitance value of the fifth capacitor.

The present invention provides a PV sensor including a control circuit, a RC calibration circuit, and a voltage sensor. The control circuit is configured to generate at least one control signal. The RC calibration circuit is configured to receive the at least one control signal to generate a voltage indicates information of (1 / R*C). The voltage sensor comprises a comparator, wherein the voltage sensor senses a voltage level of a received signal by using comparator to generate a sensing result, and the comparator is further configured to compare the calibration result within a reference voltage to generate a comparison result to the control circuit.

The invention relates to a voltage sag source positioning method based on measured data. The method comprises the following steps: S1, acquiring monitoring data; s2, performing sag-fault matching based on time sequence matching; the voltage sag of one monitoring point is matched with the same bus fault and the external fault according to the time sequence of events, and the time difference between each pair of voltage sag and fault in the matching result is calculated; s3, dynamically adjusting a window to calculate a quantile detection abnormal value; s4, performing secondary matching and iteration termination based on the reduced data set; and S5, repeating the steps S2-S4 for other monitoring points to obtain all matching data in the region, and realizing accurate positioning of the voltage sag source. According to the method, accurate and efficient fault positioning and matching can be carried out on the voltage sag event.

The invention relates to the technical field of voltage measurement, and provides a medical cyclotron acceleration voltage measurement method and system, and the method comprises the steps: obtaining a resistance voltage sequence and a resistance temperature sequence; obtaining an abnormal degree according to a resistance voltage value in the resistance voltage sequence; obtaining the load impedance influence degree according to the difference of the abnormal degrees of different parallel resistors at the same moment; acquiring a plurality of trend time periods according to the resistance temperature sequence; obtaining a temperature influence degree according to the resistance temperature value of the trend time period; obtaining a voltage instability coefficient according to the temperature influence degree and the load impedance influence degree; obtaining a temperature influence index according to the voltage instability coefficient; obtaining an abnormal probability according to the temperature influence index; and according to the abnormal probability and the load impedance influence degree, cleaning the resistance voltage sequence to obtain an acceleration voltage sequence. According to the method, the resistance voltage sequence is cleaned, so that the accuracy of the acceleration voltage measurement of the medical cyclotron is improved.

The invention relates to a photovoltaic grid-connected node voltage prediction method and device and computer equipment, and the method comprises the steps: obtaining real-time voltages collected for a plurality of photovoltaic grid-connected nodes in a target region at at least two collection moments, and a voltage prediction duration for the target region; based on the interval duration between the acquisition moments, determining the expected number of prediction moments included in the voltage prediction duration; for each acquisition moment, based on the adjacency relation between the photovoltaic grid-connected nodes, spatial analysis is carried out on each real-time voltage obtained at the acquisition moment, and spatial characteristics of each photovoltaic grid-connected node at the acquisition moment are obtained; according to a time sequence between the acquisition moments, performing time sequence analysis on the spatial features corresponding to the acquisition moments to obtain a target time feature; and performing voltage prediction processing on the target time characteristic based on the prediction moment number to obtain a prediction voltage corresponding to each photovoltaic grid-connected node at each prediction moment. By adopting the method, the voltage prediction accuracy can be improved.

A method for monitoring voltage drift includes measuring a voltage across a diode of a power device, providing the measured voltage as an input to a controller, the controller being configured to run a transformer-based model, and forecasting a range of expected future values of the voltage across the diode of the power device with the transformer-based model. The transformer-based model may include a temporal fusion transformer with a temporal convolutional neural network and an adversarial compensation model with a backpropagation algorithm.

The invention discloses a power distribution equipment voltage quality adjustment control method, device and equipment, and the method comprises the steps: collecting voltage waveform data in the operation process of power distribution equipment, and carrying out the feature extraction of the voltage waveform data, and constructing a voltage feature library; identifying a resonance voltage mode based on the voltage feature library, performing energy density analysis on the resonance voltage mode to position a resonance energy collection point, generating a resonance compensation signal, and converting resonance energy into adjusting power; performing voltage distribution evaluation on the resonance enhancement control domain, identifying an energy surplus region and an energy deficient region, and constructing a bidirectional energy channel between the two regions to generate an energy balance configuration table; carrying out oscillation characteristic analysis on the energy balance configuration table, and implementing oscillation type voltage regulation at a periodic regulation point; carrying out key path identification on the oscillation adjustment parameters, and optimizing a processing sequence to generate an adjustment time sequence table; and extracting execution instructions of each node according to the adjustment time sequence table to generate a hierarchical control instruction set, thereby realizing active perception, intelligent analysis and accurate regulation and control of voltage quality.

A HHT-based voltage quality disturbance detection method, including: obtaining frequency spectrum information of an original voltage signal, and determining whether the original voltage signal is a closely spaced mode signal; based on the frequency spectrum information, performing a singular value decomposition on the original voltage signal and performing a reconstruction to obtain a reconstructed voltage signal with an interference signal removed; if the original voltage signal is the closely spaced mode signal, performing a frequency modulation on the reconstructed voltage signal to obtain a frequency-modulated signal; adding white noise to the reconstructed voltage signal or the frequency-modulated signal, and then performing an empirical mode decomposition; and performing a Hilbert transform on each intrinsic mode function obtained by the empirical mode decomposition to obtain an amplitude and frequency information of a corresponding intrinsic mode function.

The invention discloses a voltage sensitivity fitting method and system driven by measurement data of a power distribution network, and the method comprises the steps: constructing a node input feature matrix based on the injection power, measurement voltage and neighborhood features of a power distribution network node in a certain operation state, inputting the node input feature matrix to a variational auto-encoder model, and estimating the node voltage of the whole network; constructing a plurality of groups of micro-power reference disturbance samples around the operation state, and generating corresponding voltage response by using the model again; and finally, calculating a power difference and a voltage difference between each disturbance sample and the reference state, constructing an overdetermined equation set, fitting a voltage sensitivity matrix by adopting a least square method, and averaging fitting results to improve the estimation precision. According to the method, high-precision voltage estimation and voltage sensitivity fitting can still be realized under the conditions of lack of topological structures and line parameters and sparse voltage measurement, and the method is suitable for state estimation, voltage treatment and operation optimization tasks in typical power distribution network scenes of sparse voltage measurement, incomplete topological information and the like.

A method and a system for estimating the value of the voltage relating to an element under voltage ET. The system comprises alive element ET, a first capacitor C1.sx, a second capacitor 01.dx, a third capacitor 02.sx, a fourth capacitor 02.dx, a fifth capacitor CS.dx. The method involves the use of the electrical values obtained through this system.

The embodiment of the invention discloses a transformer on-line winding state evaluation method. The method comprises the following steps: acquiring voltage signals at a high-voltage side bus and a neutral point; judging whether disturbance signals exist in the voltage signals or not; determining whether the disturbance signal is an effective disturbance signal; acquiring amplitudes of the amplitude-frequency response curve of the transformer under different frequencies; acquiring amplitudes of the amplitude-frequency response curve of the transformer under different frequencies when the line winding state is normal; carrying out subtraction on the two amplitudes to obtain a difference vector; segmenting and numbering the difference vector to obtain a quantile serial number vector; constructing a transfer matrix according to the quantile box number vector; determining a second moment, a positive offset coefficient, a negative offset coefficient and a stationary offset coefficient of the transfer matrix; determining a state evaluation factor; and evaluating the state of the transformer according to the state evaluation factor to obtain an evaluation result. According to the method, the online winding state of the transformer is evaluated, and the evaluation accuracy can be improved.

The invention discloses a spacing-adjustable magnetic steel wire electricity-taking clamp, and aims to solve the problems of poor stability, difficult installation of an electricity-taking clamp and poor adaptability in the adsorption electricity-taking process of an existing magnetic steel wire. The electricity taking clamp comprises a clamping assembly, an adjusting assembly, a fixing assembly and a plurality of magnetic steel wires, the clamping assembly is connected with the adjusting assembly, and the fixing assembly is connected with the clamping assembly; the adjusting assembly is used for adjusting the clamping width of the clamping assembly, the clamping assembly abuts against the circuit breaker, the fixing assembly is matched with the clamping assembly to fix the multiple magnetic steel wires, and the multiple magnetic steel wires are electrically connected with the circuit breaker. The electricity taking clamp can be adapted to circuit breakers with different widths, so that the universality of the electricity taking clamp is improved, and the cost is reduced; the adaptation process during power taking of the circuit breaker is saved, the power taking operation time is shortened, and the power taking efficiency is improved. The matching efficiency of the magnetic steel wire and the screw hole of the circuit breaker is improved, the wiring operation is simplified, the clamping assembly abuts against the circuit breaker, the stability of the power taking clamp after installation is ensured, and continuous power supply is guaranteed.

The invention relates to the technical field of submarine cable fault detection, in particular to a submarine cable fault detection system. The method comprises the steps that an adjustable low-frequency pulse injection unit injects a low-frequency pulse excitation signal and collects a response signal generated by a submarine cable fault; the multi-source signal fusion acquisition unit acquires a reflected voltage signal, an acoustic signal and a leakage magnetic field signal, and constructs a multi-modal fusion response characteristic matrix; the intelligent broadband noise suppression unit is used for performing noise suppression processing on each modal sub-matrix to obtain a de-noised multi-modal fusion response characteristic matrix; and the intelligent fault positioning interpretation unit is used for constructing a three-dimensional signal fingerprint spectrogram, performing classification analysis on fault events based on a fuzzy clustering algorithm and a depth feature matching model to obtain a fault type, and performing calculation through a path residual fitting method to obtain a fault position. The invention realizes a detection system which does not depend on a special cable structure, can actively excite and fuse multi-source signals, and can position submarine cable faults at high precision.

The present disclosure provides a power supply voltage drop detection device and system. The device comprises a gating unit, a first detection channel, and a second detection channel. In a first duration of a control cycle, the gating unit outputs a power supply voltage to the first detection channel, and outputs a threshold voltage to the second detection channel; and in a second duration, the gating unit outputs a threshold voltage to the first detection channel, and outputs a power supply voltage to the second detection channel. The first detection channel detects a first voltage characterization value of the first duration and a second voltage characterization value of the second duration, and outputs a first alarm signal when the first voltage characterization value is smaller than the second voltage characterization value. The second detection channel detects a third voltage characterization value of the first duration and a fourth voltage characterization value of the second duration, and outputs a second alarm signal when the fourth voltage characterization value is smaller than the third voltage characterization value.

The invention discloses a power distribution network cluster local control method and device, equipment and a medium. The method adopts a cloud edge end three-level collaborative architecture, and comprises the following steps: acquiring electrical parameters through a terminal equipment layer; constructing a graph model based on an electrical distance at the edge calculation layer; performing initial cluster division and issuing on the cloud computing layer; dynamically optimizing cluster division in an edge calculation layer through a lightweight deep reinforcement learning model; local control strategies such as voltage reactive power cooperative control, frequency active power balance control and fault rapid isolation and self-healing are executed based on the final division. The system comprises a terminal device layer, an edge computing layer and a cloud computing layer. According to the method, decoupling of global optimization and local real-time control is realized through cloud-side cooperation, the problems of high data processing pressure, high communication delay, expanded local fault influence range and the like of centralized control are effectively solved, and the real-time performance, reliability and disaster resistance of the power distribution network are remarkably improved.

A voltage meter includes a sampler, a gain circuit, an accumulator and a feedback circuit. The sampler samples an input signal to generate a series of first signals and a series of second signals. The gain circuit, coupled to the sampler, modifies at least one of the series of first signals and the series of second signals, to generate a series of modified first signals and a series of modified second signals. The accumulator, coupled to the gain circuit, accumulates an operational result of the series of modified first signals and the series of modified second signals, to generate an accumulation result. The feedback circuit, coupled between the accumulator and the sampler, sends a feedback signal back to the sampler according to the accumulation result.

The invention discloses a control cabinet wiring detection device, and belongs to the technical field of detection devices. The device comprises a body and two groups of detection cylinders, moving cylinders are sleeved with the two groups of detection cylinders in an up-down sliding manner, the lower sides of the moving cylinders are fixedly connected with moving frames, the outer sides of the detection cylinders are fixedly connected with bottom plates through arc-shaped rods, and positioning assemblies used for adjusting and fixing the positions of the moving cylinders are installed in the detection cylinders. The positioning assembly comprises a positioning rod, a fixing plate, an arc-shaped plate and a first spring, and the positioning rod is slidably sleeved with the detection cylinder. When a connecting line in the control cabinet needs to be detected, the movable frame and the bottom plate are moved to the two ends of the detected connecting line, the voltage of the connecting line is detected through the body, in the process, under the action of the compressed first spring, the connecting line, the movable frame and the bottom plate are connected more tightly, and the detection accuracy is improved. The detection cylinder does not need to be held by hands all the time, and the workload is reduced.