206 results about "Output transformer" patented technology

Methods for co-designing transformer-accelerator pairs are provided. The methods may include using a transformer embedding to generate a computational graph and a transformer model. The methods may include running the computational graph through a surrogate model and outputting accuracy data of the surrogate model. The methods may include using an accelerator embedding and the transformer model to simulate training and inference tasks and outputting hardware performance data of the transformer model. The methods may include sending the hardware performance data (such as latency, energy leakage, dynamic energy, and chip area, which may be optimizable performance parameters) and model accuracy data to a co-design optimizer. The methods may include generating an output transformer-accelerator or a transformer-edge-device pair from the co-design optimizer. The transformer model and accelerator embedding may be the output transformer-accelerator or a transformer-edge-device pair.

A power-over-Ethernet (PoE) PD / PSE device comprises a powered device (PD) interface configured to connect to an upstream power sourcing equipment (PSE) and receive input PoE power from the PSE, and a PSE interface configured to connect to a downstream PD and to supply output PoE power to the PD. The PD / PSE also comprises a device power rail to supply operational power to one or more components of the PD / PSE, and a DC-DC converter comprising a multi-output transformer comprising a transformer input, a first transformer output electrically connected to the PSE interface, and a second transformer output electrically connected to the device power rail. The DC-DC converter is configured to receive the input PoE power and, in response, supply the input PoE power to the transformer input, generate the output PoE power at the first transformer output, and generate the operational power at the second transformer output.

The invention belongs to the technical field of power distribution networks, and discloses a load prediction and early warning method and system for a transformer area containing distributed resources, and the method comprises the steps: combining a two-dimensional time sequence data sample set of a high-risk transformer area with a transformer area feature operation data set according to the transformer area and a timestamp, and generating a prediction model training sample data set; building a lightweight gradient boosting tree as a main prediction model, inputting a training sample data set for training, and optimizing hyper-parameters of the main prediction model by adopting a Bayesian optimization algorithm; and establishing a residual error correction model based on local weighted Gaussian process regression, superposing a load prediction result of a prediction day of the main prediction model of the to-be-predicted transformer area with a residual error correction value of a prediction day of the residual error correction model to obtain a final load prediction result, and outputting transformer area weight / overload early warning information. According to the method, the LGBM is adopted as the main prediction model for load prediction, the residual error correction model is adopted for residual error correction, and the robustness and adaptability of the model are improved.

The invention discloses a 10kV distribution transformer on-load voltage regulation control method and system, and relates to the technical field of transformer on-load voltage regulation, and the method comprises the steps: collecting the three-phase voltage and current of a low-voltage side of a distribution transformer and a tap switch gear signal, and loading a preset voltage regulation control mode and an oscillation region parameter; based on the acquired three-phase voltage and current of the low-voltage side of the distribution transformer and the tap switch gear signal, calculating a feeder comprehensive impedance parameter and a load reactive power parameter, and outputting a transformer operation state index; according to the transformer operation state index, the voltage regulation control mode and the oscillation area rule, current voltage out-of-limit and reactive power deviation are judged, and a voltage regulation strategy triggering instruction is generated according to the judgment result; and calculating upper and lower limit values of feed line correction voltage based on the voltage regulation strategy trigger instruction, and controlling the tap switch to execute voltage regulation action. According to the method, a combined calculation scheme of feeder comprehensive impedance and load reactive power is fused, and dynamic optimization of the triggering condition of the voltage regulation strategy is achieved.

The invention provides a transformer construction period environmental protection risk assessment method and system, and the method comprises the steps: inputting transformer image data of a construction site in a construction period into an image recognition model, and recognizing the current abnormal coordinate information of a transformer; obtaining current abnormal state data based on the current abnormal coordinate information; inputting the current abnormal state data, the obtained current operation state parameters of the transformer and the obtained current environment parameters into a pre-constructed dynamic evaluation model for evaluation to obtain the current risk degree of the transformer; based on the current risk degree, outputting an environmental protection risk assessment result and an equipment safety monitoring result of the transformer; wherein the dynamic evaluation model is obtained by training an adaptive neural network by adopting historical abnormal state data, historical operation state parameters, historical environment parameters and historical risk degrees of the transformer. The current environmental protection risk degree of the transformer can be output in real time, and the dynamic monitoring requirement of the transformer in the construction period is met.

The invention discloses an oil-immersed power transformer monitoring method, and relates to the field of power systems, and the method comprises the steps: collecting data, collecting historical operation data, and carrying out the preprocessing; performing feature extraction on the preprocessed sensor data and historical operation data to form a sensor data feature vector and a historical operation data feature vector; fusing the sensor data feature vector and the historical operation data feature vector to form a comprehensive feature data set; establishing a fault threshold based on the historical operation data; establishing a transformer fault prediction model based on the comprehensive feature data set, and outputting a transformer fault occurrence probability; automatically adjusting a fault threshold according to a transformer fault prediction result; generating an environment state report based on the current environment state; formulating and executing a dynamic compensation strategy according to the environment state report; according to the invention, early warning of potential faults of the transformer is realized. Preventive measures can be taken before the fault occurs, and the influence of the fault on the power grid is reduced.

The invention belongs to the technical field of power electronics, and discloses a high-performance multi-output driving power supply and a low-coupling capacitance multi-channel transformer, the low-coupling capacitance multi-channel transformer comprises a pair of magnetic cores, a group of primary windings and N groups of secondary windings, and N is greater than 2; wherein one magnetic core comprises a primary side magnetic column and N secondary side magnetic columns, and the N secondary side magnetic columns evenly surround the circumference with the primary side magnetic column as the circle center; the primary winding is wound on the primary magnetic column, and the N groups of secondary windings are respectively wound on the corresponding secondary magnetic columns; therefore, the coupling capacitance of the primary side and the secondary side is effectively reduced so as to limit the common-mode current excited by the high-speed action of the switching device; based on the multi-output transformer, the invention also provides a high-performance multi-output driving power supply, and a post-stage voltage regulating circuit is configured in the driving power supply, so that the cross regulation rate of multi-output is effectively reduced, and the working consistency and stability of a switching device in a power module are ensured.

The invention provides an ESR and C monitoring method for a C-type single-ended power amplifier output transformer, and the method comprises the steps: obtaining equivalent capacitance parameters caused by the primary winding resistance, secondary winding resistance, iron core loss resistance, inter-winding distributed capacitance, winding self-distributed capacitance and iron core dielectric loss of the C-type single-ended power amplifier output transformer according to a winding structure and an iron core material of the C-type single-ended power amplifier output transformer; sampling voltage and current waveforms of the primary winding and the secondary winding by adopting a sampling circuit, and determining ESR and C values in an equivalent circuit of the output transformer by adopting a least square fitting method according to sampled data and acquired parameters; and calculating the distortion degree, the frequency response high-frequency decline slope, the transient response time constant and the overshoot under different ESR and C value combinations by using the optimized index prediction formula, and establishing a mapping table of the index values and the ESR and C values.

The invention discloses a transformer state recognition method and device based on multi-scale time-frequency characteristics. The method comprises the steps that voiceprint signals generated when a transformer operates are collected; processing the voiceprint signal, and extracting a multi-scale time-frequency feature to obtain a time-frequency tensor; the time-frequency tensor is input into a pre-constructed multi-scale time-frequency model, and the multi-scale time-frequency model is constructed based on multi-scale convolution, a Transform neural network and a double-branch attention mechanism; and outputting a transformer state identification result through the multi-scale time-frequency model. According to the method, the voiceprint feature expression capability can be remarkably improved by extracting the multi-scale time-frequency features and the multi-scale time-frequency model, so that the transformer state recognition precision and speed are improved, and stable real-time recognition of the transformer state can still be realized in a complex noise environment.

Provided is a direct-current converter. The direct-current converter is provided with a processor (1), a phase-shifting full-bridge circuit (2), a primary resonance circuit (3), a transformer (4), a secondary resonance circuit (5), and a rectifier circuit (6); because the transformer (4) outputs alternating current, the secondary resonance circuit (5) can simultaneously perform energy storage and discharging when the direction of the current of the transformer (4) is changed; specifically, when the direction of the current of the transformer (4) is changed, the secondary resonance circuit (5) can store the electric energy outputted by the transformer (4), and simultaneously discharge the electric energy stored before the direction of the current of the transformer (4) is changed, so as to supply power for a load; the electric energy outputted by the transformer (4) is stored into the secondary resonance circuit (5); and the electric energy outputted by the transformer (4) is outputted to the load by means of the secondary resonance circuit (5). When the direction of the current of the transformer (4) is changed, the secondary resonance circuit (5) can perform corresponding energy storage and discharging, and the transformer (4) can perform normal output, i.e., it is also ensured that the output duty ratio of the transformer (4) is not lost.

The invention discloses a transformer multi-measuring-point working condition identification method based on deep convolution feature fusion, and belongs to the technical field of transformer detection, and the method comprises the steps: obtaining vibration signals of a plurality of preset points of a transformer, carrying out the processing based on a pre-trained transformer working condition identification model, and outputting a transformer working condition identification result, based on a Swin Transformer encoder and a depth deformable MobileNet module, a double-path collaborative architecture is adopted, a first path and a second path of a transformer working condition recognition model are constructed, and the first path and the second path are subjected to feature interaction through a cross-modal attention fusion module. According to the method, the problems of low efficiency and poor accuracy caused by neglecting vibration signal time sequence dependence, local detail features, global structures and spatial features in existing transformer multi-measuring-point working condition identification are solved.

The invention discloses a current type electric shock weeding device, a control method and a weeding system. The device comprises a battery side voltage source; the primary side full-bridge inverter circuit is connected with the battery side voltage source; the voltage doubling circuit is used for generating high-voltage direct current output; the primary side of the transformer winding is connected with the midpoint of the primary side full-bridge inverter circuit, and the secondary side of the transformer winding is connected with the voltage doubling circuit; and the phase shift control module is configured to change the phase shift duty ratio phi = theta / pi by adjusting the phase shift angle theta and control the output current. The embodiment of the invention aims to provide a DC-DC converter which is free of ripples, has a constant-current characteristic and is simple to control for the field of electric shock weeding.

The invention relates to the technical field of gas concentration detection of power equipment, and discloses a method and system for detecting the concentration of gas dissolved in oil based on an improved extreme learning machine, and the method comprises the steps: improving the extreme learning machine into a kernel extreme learning machine and a depth extreme learning machine, and respectively combining with a seagull optimization algorithm to obtain the concentration of gas dissolved in oil; constructing a model for predicting the concentration of the dissolved gas in the transformer oil, and training the model; and based on the transformer data, inputting the transformer data into the model for predicting the concentration of the dissolved gas in the transformer oil, and outputting a prediction result of the dissolved gas in the transformer oil and a fault type. According to the method, an intelligent optimization algorithm and a data processing method are combined, an extreme learning machine with high learning speed and good generalization performance is improved to form a deep extreme learning machine and kernel extreme learning machine model, an improved seagull algorithm is used for optimization, and a prediction model is formed for prediction. And the detection precision of the equipment gas concentration in the power system is improved.

The invention discloses a power grid transformer technical renovation and overhaul time domain interval evaluation method. The method comprises the steps of 1, establishing an evaluation basic data set through multi-source data acquisition and data preprocessing; 2, screening key influence variables, quantifying variable influence weights by adopting regression modeling, and realizing accurate quantification of the health state of the transformer in combination with a TOPSIS algorithm; 3, forming a dynamic fault rate model; 4, constructing a system dynamics-Monte Carlo cooperation model, a fault tree-Bayesian network dynamic and static diagnosis model and a long and short term memory network time sequence prediction model; 5, setting an optimization target and a constraint condition, and outputting an optimal time point and a reasonable time domain interval of technical renovation and overhaul of the transformer by adopting a multi-target optimization solution method; and 6, model evaluation precision is tested back and verified through historical data, and key parameters of the model are subjected to feedback adjustment by adopting a particle swarm optimization algorithm. The method effectively solves the problems that a traditional method is low in evaluation precision, single in target and poor in dynamic adaptability, and is convenient to popularize and use.

The invention discloses a defect coupling low-noise amplifier. The low-noise amplifier solves the problem that the performance of a low-noise amplifier in the prior art is influenced by a grid source inductance coupling coefficient. Forward coupling of an input inductor and a grid inductor and reverse coupling of the input inductor and a source inductor are achieved through a unique defect coupling transformer matching network, meanwhile, reverse coupling of a grid inductor and the source inductor is achieved, and the coupling coefficient of the grid-source inductor is reduced through coupling counteracting inductance; by combining a differential common-source transconductance amplification stage, a four-order magnetic coupling resonance unit, a differential transconductance amplification stage with a neutralizing capacitor and an output transformer matching network, the characteristics of high gain bandwidth and low noise are realized; simulation and actual tests verify that the low-noise amplifier can effectively reduce the noise coefficient and broaden the input matching range, has good compatibility and wide application prospects based on a conventional integrated circuit production process, can be applied to a phased array system, and can also form a receiver system with other circuits.

The invention discloses an operation state identification method and device of a transformer, a medium and equipment. According to the method, the real-time operation data, the historical data and the physical attribute parameters of the converter transformer are acquired, and the data are combined with the preset multi-physical-field high-fidelity simulation model to carry out multi-physical-field solution, so that a plurality of predicted values are obtained. Meanwhile, a time sequence neural network model based on an LSTM-Transform network obtained by training real-time and historical data is utilized to predict a temperature residual value. And dynamically adjusting the fusion weight of the first temperature prediction value and the actual monitoring value by comparing the residual error of the first temperature prediction value and the actual monitoring value of the simulation model, and generating a mixed temperature prediction value. And finally, the mixed temperature prediction value is input into a knowledge layer decision-making system, the system uses a preset threshold value judgment and similarity matching algorithm to output an operation state identification result of the transformer, and the problem that the operation state of the transformer cannot be accurately and efficiently identified in the prior art is effectively solved.

The invention belongs to the technical field of data processing, and discloses a transformer polymerization degree distribution visualization method, system and device and a medium, and the method comprises the steps: generating an internal temperature field distribution simulation result of a transformer model through simulation software, and outputting transformer polymerization degree distribution data under different temperature changes; performing mesh generation on the transformer simulation model to obtain a triangular mesh model, and mapping the triangular mesh model to a plane parameter domain; selecting parameter points in the plane parameter domain, and generating corresponding data sampling points of the parameter points in the triangular mesh model by using an inverse mapping technology; and performing curved surface interpolation fitting on the data sampling points to obtain a curved surface fitting result, and performing visualization processing on the curved surface fitting result. According to the method, the sensor simulation model is subdivided to obtain the triangular mesh model, a complex model can be converted into a model with a small number of vertexes and a single boundary, the operation complexity of the fitting process is simplified, and the curved surface fitting efficiency is improved.

The invention discloses an on-chip transformer automatic drawing method which can be suitable for various structures including a staggered mutual winding transformer, a symmetrical mutual winding transformer and a symmetrical laminated transformer. According to the on-chip transformer automatic drawing method, drawing of transformers of any polygons, different structures and multiple turn ratios can be achieved, a tap structure can be additionally arranged at any position, and common radio frequency circuit application scenes can be covered. Compared with traditional manual drawing, the method has the advantages that the transformer layout can be quickly output only by providing required structural parameters and structural types, and the design efficiency of passive devices is greatly improved. Meanwhile, the drawing structure is pre-screened in combination with geometric priori knowledge, and the automatic modeling success rate can reach 100%. According to the method, the success rate is guaranteed, and meanwhile automation and intelligentization of radio frequency circuit design are promoted.

The invention discloses a transformer abnormal state diagnosis and early warning method based on voiceprint characteristics. The method comprises the following steps: acquiring a network topological graph and voiceprint information of a transformer network node; the method comprises the following steps: dividing a transformer into category voiceprint information data by using a support vector machine algorithm, generating a category voiceprint data set, establishing a transformer abnormal voiceprint data optimization model, and updating and outputting transformer abnormal state voiceprint features by using feature smoothing processing according to the transformer abnormal voiceprint data optimization model. And according to the abnormal voiceprint map feature database, through similarity analysis, generating a transformer abnormal state analysis result and outputting the transformer abnormal state analysis result. According to the method, the transformer voiceprint information can be recognized and updated in a complex sound field environment by optimizing and smoothing the voiceprint features, so that the precision and robustness of a subsequent fusion diagnosis model are improved, and the abnormal state diagnosis and early warning effects of the transformer are further improved.

The invention discloses an active phase shifter with temperature compensation. The active phase shifter comprises an input transformer balun, a multi-phase filter, a vector modulation module based on a Gilbert unit, an output transformer balun and a positive temperature coefficient current source, the input transformer Balun is used for converting a single-ended signal of an input end into a differential signal; the multi-phase filter is used for converting the differential signal into an orthogonal signal; the vector modulation module based on the Gilbert unit is used for carrying out polarity selection on the orthogonal signals and carrying out vector synthesis; the output transformer Balun is used for converting the output end differential signal into a single-end signal; the positive temperature coefficient current source is used for controlling the gain of the Gilbert unit. By designing the positive temperature coefficient current source changing along with the temperature, the change of the gain of the vector modulation module along with the temperature is slowed down, and the stability of the key performance of the active phase shifter within the temperature range of-55 DEG C to 85 DEG C is improved.

This invention discloses a method and system for real-time analysis of transformer operating status oriented towards edge computing, specifically relating to the field of power equipment condition monitoring and edge computing data processing technology. The method includes acquiring load values, oil temperature values, winding temperature values, cooling status values, and status monitoring values ​​collected from the transformer site. It generates three types of change symbols (increase, decrease, and remain unchanged) for each type of value according to the sampling order, and binds each change symbol to its corresponding sampling sequence number, outputting ordered transformer operating data. By converting the load values, oil temperature values, winding temperature values, cooling status values, and status monitoring values ​​collected from the transformer site into change symbols with sampling sequence numbers, it identifies load change segments or cooling change points and extracts the current temperature rise response segment. Then, it compares the current temperature rise response segment with existing temperature rise response segments in response order, and generates transformer operating status analysis results based on the order differences formed by oil temperature reversal, winding temperature changes, and status monitoring value changes.

The utility model provides a junction box for a transformer, and relates to the technical field of transformer junction boxes. The junction box comprises a box body, a power connector, a signal connector and a cover plate, the box body is fixedly connected with a transformer, a plurality of mounting holes are formed in the box body, and the mounting holes are distributed in different surfaces of the box body; the power connector is fixedly connected with the box body through one of the mounting holes, and the power connector is used for inputting a high-voltage power supply to the transformer; the signal connector is fixedly connected with the box body through one of the plurality of mounting holes, and the signal connector is used for outputting a transformer working signal to a control cabinet; and the cover plate is used for blocking other unused mounting holes. A plurality of mounting holes are arranged on different surfaces of the box body, when power connectors and signal connectors of specific models are mounted, the mounting holes matched with the connectors in size are selected, the connectors are fixed on the box body through the mounting holes, and other unused mounting holes are blocked by cover plates, so that the junction box can adapt to connecting and mounting of the connectors of different models.

The invention provides an anti-magnetic saturation control method for an inverter, which belongs to the field of power electronics and comprises the following steps of: sampling a primary side current instantaneous value of a transformer at an output voltage zero-crossing moment of the inverter; calculating the deviation between the current instantaneous value and a transformer primary side current sampling value half a period ahead of the zero-crossing moment, judging whether the deviation exceeds a set threshold value or not, if so, determining a compensation direction according to the deviation and the modulation wave, updating the current compensation amount according to the deviation and the compensation direction, injecting the updated compensation amount into the modulation wave, and outputting the updated compensation amount. The updated compensation amount is attenuated; if not, injecting the current compensation amount into the modulation wave, and attenuating the current compensation amount; the invention also provides an inverter anti-magnetic saturation control device and an inverter system. The DC magnetic bias of the inverter output transformer can be eliminated.

The utility model relates to a current collection device of a slide wire rail. The current collection device comprises a linear rail, a sliding block is slidably connected to the outer surface of the linear rail, a battery pack is fixedly installed on the upper surface of the sliding block, a strip-shaped hole is formed in the right side face of the linear rail, a conductor rail is fixedly connected to the bottom face of the linear rail, and a sliding supporting plate is slidably connected to the inner wall of the strip-shaped hole. According to the device, a conductor rail is arranged at the bottom of a linear rail and is matched with a strip-shaped hole, a sliding support plate and a connecting block, so that a battery pack, the connecting block and the sliding support plate can be driven to move through sliding of the sliding block above the linear rail, and a current collector conductive head can be driven to slide in the conductor rail by utilizing movement of the sliding support plate; and through the arrangement of a current collector conductive head, a wiring terminal and a power line, and the cooperation with an output transformer and an inverter, the electric energy of the conductor rail can be conducted, and power can be continuously supplied to the storage battery when the storage battery moves.

The utility model discloses a medium-frequency induction heating device, comprising a medium-frequency power supply which is an induction heating power supply based on high-speed DSP chip control; the output transformer is connected with the medium-frequency power supply; a cantilever crane; the heating device comprises an induction heating coil connected with the output transformer, and the induction heating coil is mounted on the cantilever crane; the far infrared temperature measurement system and the induction heating coil are integrally designed; and the industrial constant-temperature water cooler is respectively connected with the output transformer, the medium-frequency power supply and the induction heating coil. The preheating device changes the preheating mode of top bending in a steel rail factory, the whole process is automatically controlled, the possibility of uncontrollable factors existing in manual operation is eliminated, it is ensured that the temperature meets the process requirement, heating is safe, efficient and uniform, steel rail breaking is avoided, the rejection rate is reduced, and the preheating device has popularization value in the industry.

The present invention discloses an intelligent diagnosis method for partial discharge of a transformer based on an improved transformation network, which relates to the technical field of transformer fault diagnosis. The method includes collecting partial discharge signals of the transformer, preprocessing the partial discharge signals to obtain a time series; using the Markov transition field (MTF) algorithm, the Gram angular field (GASF) algorithm, and the Gram angular difference field (GADF) algorithm to convert the time series into feature images respectively; processing the feature images through an improved transformation network model to obtain a fused feature vector; and inputting the fused feature vector into a fault diagnosis model to output a fault diagnosis result of the partial discharge of the transformer. By combining an interpretable graph reasoning mechanism of environmental parameters and signal features, the present invention improves the recognition rate of oil gap discharge in tests, enabling the fault diagnosis to leap from the traditional threshold-based judgment mode to an intelligent mode based on causal logic reasoning.

A valve amplifier (105, 305) comprising an output transformer (110, 310) and a capacitor (210, 410) connected in parallel with a secondary winding (205, 405) of the output transformer (110, 310) Systems (100, 300), methods, and valve amplifier accessories (325, 500, 600) are also provided.

This invention discloses a millimeter-wave broadband high harmonic suppression tripler, comprising an input matching network, a time-domain shaping tripler unit, and a differential common-source output stage. The proposed time-domain shaping tripler unit employs transistor pairs with different gate widths and bias voltages to superimpose two sets of voltage signals of different amplitudes in the time domain, thereby enhancing the inherent harmonic suppression of the tripler unit. Furthermore, by connecting a common-mode impedance control in series at the center tap of the primary inductor coil of the output transformer of the tripler unit, the output power of the third harmonic is further improved. The input matching network achieves single-ended to differential conversion, with its primary and secondary coil center taps grounded and open-circuited respectively in a counterintuitive manner, improving differential-mode balance and common-mode stability. Simultaneously, by using a series-coupled inductor, the quality factor of the transistor input impedance is reduced, improving the bandwidth performance of the tripler.

The present invention discloses a signal injection device for a TN‑S power supply system, and belongs to the field of power monitoring technology. The device comprises: a signal generation and amplification module, a multifunctional tuning module, a data processing and control module, a communication module, and a working power supply module. The multifunctional tuning module comprises: a coupling capacitor, a signal output transformer, a power supply transformer, and a reactor; the present invention adopts an open triangle line signal injection method, and considers the signal amplifier, coupling capacitor, signal transformer, power supply transformer, and reactor as a whole, and designs them into an L‑C‑R series resonance mode, which is a technical innovation method for creating a basic signal for online real-time monitoring of insulation resistance in a TN‑S system under the condition of symmetrical line-to-ground impedance, and provides an important means for the safe and reliable operation of the power supply system.

The present invention discloses an active phase shifter with temperature compensation, comprising an input transformer balun, a polyphase filter, a vector modulation module based on a Gilbert cell, an output transformer balun, and a positive temperature coefficient current source. The input transformer balun is used to convert a single-ended input signal into a differential signal; the polyphase filter is used to convert the differential signal into a quadrature signal; the vector modulation module based on the Gilbert cell is used to select polarity and perform vector synthesis on the quadrature signal; the output transformer balun is used to convert the differential signal at the output into a single-ended signal; and the positive temperature coefficient current source is used to control the gain of the Gilbert cell. By designing a temperature-dependent positive temperature coefficient current source, the present invention mitigates the temperature-dependent gain change of the vector modulation module, thereby improving the stability of the key performance of the active phase shifter within a temperature range of 55 to 85°C.