A method and device for monitoring faults of a power amplifier

Abstract

The present invention discloses a method and device for fault monitoring of a power amplifier, and relates to the technical field of fault monitoring. The method comprises: setting a monitoring unit at a key node of the power amplifier; collecting the voltage, current, temperature and humidity monitoring data of the power amplifier in real time, analyzing and identifying the monitoring data through the built-in algorithm of the ARM processor, and obtaining the working state information; making a fault determination according to the working state information, and obtaining a fault determination result; when the fault determination result is yes, performing an analysis and positioning according to the monitoring data, and determining the fault point; establishing a mapping association between the fault point and the fault determination result, and generating monitoring feedback data. The present invention solves the technical problem in the prior art that the working state information of the power amplifier cannot be obtained in a timely and accurate manner, resulting in inaccurate fault determination, and achieves the technical effect of real-time monitoring of the power amplifier and improving the accuracy and reliability of fault determination.

Description

Technical Field

[0001] The present invention relates to the technical field of fault monitoring, and in particular to a method and device for monitoring fault of a power amplifier. Background Art

[0002] Power amplifiers are widely used in various electronic devices, such as audio amplifiers, RF amplifiers, etc. They are responsible for amplifying the input signal to the required power level to drive the load or achieve long-distance signal transmission. However, since power amplifiers usually work in a high voltage and high current environment and run for a long time, they are prone to various faults.

[0003] Traditional power amplifier fault monitoring methods mainly rely on manual detection or simple sensor monitoring, which have many limitations. Manual detection is not only inefficient, but also difficult to detect the occurrence of faults in real time; simple sensor monitoring may only detect some obvious fault symptoms, and often cannot accurately identify potential faults or complex fault modes. Summary of the invention

[0004] The present invention provides a method and device for monitoring faults of a power amplifier, which are used to solve the technical problem in the prior art that the working state information of the power amplifier cannot be obtained timely and accurately, resulting in inaccurate fault judgment.

[0005] In view of the above problems, the present invention adopts the following technical solutions.

[0006] A first aspect of the present invention provides a method for monitoring a fault of a power amplifier, the method comprising:

[0007] A monitoring unit is set at a key node of the power amplifier, including an ARM processor, an ADC sampling chip, a Hall sensor, and a temperature and humidity sensor; based on the ADC sampling chip, the Hall sensor, and the temperature and humidity sensor, the voltage, current, temperature, and humidity monitoring data of the power amplifier are collected in real time, and the monitoring data is analyzed and identified through the built-in algorithm of the ARM processor to obtain working status information; a fault judgment is performed according to the working status information to obtain a fault judgment result; when the fault judgment result is yes, the fault point is determined by analyzing and locating according to the monitoring data; a mapping association between the fault point and the fault judgment result is established to generate monitoring feedback data.

[0008] Furthermore, based on the ADC sampling chip, the Hall sensor and the temperature and humidity sensor, the voltage, current, temperature and humidity monitoring data of the power amplifier are collected in real time, specifically including:

[0009] Using a voltage divider circuit to reduce the circuit voltage of the power amplifier to the range of the ADC sampling chip to obtain a voltage to be measured, and converting the analog signal of the voltage to be measured into a digital signal through the ADC sampling chip to obtain voltage monitoring data;

[0010] The magnetic field of the conductor is obtained by the Hall sensor, and the current intensity is determined according to the change of the magnetic field of the conductor to obtain the current monitoring data;

[0011] The temperature and humidity of the power amplifier are detected and uploaded by the temperature and humidity sensor to obtain temperature monitoring data and humidity monitoring data.

[0012] Furthermore, a monitoring unit is set at the key node of the power amplifier, which is previously:

[0013] A first amplifier module is constructed based on a digital power amplifier, and a second amplifier module is constructed based on a linear power amplifier. The first amplifier module and the second amplifier module are connected in parallel and connected to a central control module to obtain the power amplifier; wherein the central control module has a switching mechanism, and the switching mechanism is to switch between the first amplifier module and the second amplifier module according to load and test requirement parameters;

[0014] According to the framework structure of the power amplifier, the power input port, the input and output nodes of the first amplifier module, the input and output nodes of the second amplifier module and the input and output nodes of the central control module are used as the key nodes.

[0015] Furthermore, the monitoring data is analyzed and identified by the built-in algorithm of the ARM processor to obtain the working status information, which specifically includes:

[0016] Locate and execute the amplifier module according to the monitoring data to determine the data execution path;

[0017] According to the data execution path, the monitoring data is spliced ​​to construct a target data chain;

[0018] Based on the type of the execution amplifier module, feature extraction is performed on the target data link, and voltage and current signal waveforms and temperature and humidity change curves are constructed according to the data features;

[0019] The working status information is obtained according to the characteristic changes of the voltage and current signal waveforms and the temperature and humidity change curves.

[0020] Furthermore, the extracting features of the target data link based on the type of the amplifier module specifically includes:

[0021] When the execution amplifier module is the first amplifier module, high-frequency switching noise filtering is performed on the current and voltage monitoring data in the target data chain, and then PWM signal demodulation is performed, and the demodulated analog signal is used as the actual output current and voltage to extract the time domain characteristics, frequency domain characteristics and statistical characteristics of the current and voltage monitoring data, wherein the frequency domain characteristics include the switching frequency and its harmonic components;

[0022] When the execution amplifier module is the second amplifier module, low-frequency and high-frequency noise filtering is performed on the current and voltage monitoring data in the target data chain to extract the time domain characteristics, frequency domain characteristics and statistical characteristics of the current and voltage monitoring data, wherein the frequency domain characteristics include the main frequency component and its harmonic distortion characteristics.

[0023] Further, performing fault determination according to the working status information specifically includes:

[0024] According to the data execution path, establishing a node relationship with the work status information according to key nodes in the path;

[0025] Performing node waveform change amplitude comparison according to the node relationship, and when the node waveform change amplitude reaches a standard threshold, performing fault determination according to the waveform change amplitude comparison result;

[0026] When the node waveform change amplitude does not reach the standard threshold, the historical waveform change amplitude comparison results are extracted based on the key nodes, and a time series amplitude comparison is performed, and a fault judgment is made according to the time series amplitude comparison results.

[0027] Further, performing fault determination according to the working status information further includes:

[0028] A comprehensive fault determination is performed based on the waveform change amplitude comparison result and the timing amplitude comparison result.

[0029] Furthermore, obtaining the fault determination result specifically includes:

[0030] Fault determination formula: , and obtain the comprehensive fault judgment probability, where is the comprehensive fault judgment probability, is the amplitude of the waveform change at the current node, is the fitting parameter for determining the waveform change amplitude comparison result, is the amplitude of the timing waveform change, is the fitting parameter for determining the time series amplitude comparison result, is the fault probability expression for fault judgment based on the waveform change amplitude comparison result, is the fault probability expression for fault determination based on the timing amplitude comparison result;

[0031] The fault determination result is obtained by comparing the comprehensive fault determination probability with a preset fault threshold.

[0032] A second aspect of the present invention provides a fault monitoring device for a power amplifier, the device comprising:

[0033] A monitoring unit setting module is used to set a monitoring unit at a key node of the power amplifier, wherein the monitoring unit includes an ARM processor, an ADC sampling chip, a Hall sensor, and a temperature and humidity sensor; a working status information acquisition module, based on the ADC sampling chip, the Hall sensor, and the temperature and humidity sensor, collects the voltage, current, temperature, and humidity monitoring data of the power amplifier in real time, analyzes and identifies the monitoring data through the built-in algorithm of the ARM processor, and obtains the working status information; a fault judgment result acquisition module is used to perform fault judgment according to the working status information and obtain the fault judgment result; a fault point determination module is used to analyze and locate the fault point according to the monitoring data when the fault judgment result is yes; a monitoring feedback data generation module is used to establish a mapping association between the fault point and the fault judgment result and generate monitoring feedback data.

[0034] One or more technical solutions provided by the present invention have at least the following technical effects or advantages:

[0035] The present invention solves the technical problem in the prior art that the working status information of the power amplifier cannot be obtained timely and accurately, resulting in inaccurate fault judgment, and achieves the technical effect of real-time monitoring of the power amplifier and improving the accuracy and reliability of fault judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0037] Figure 1 A schematic flow chart of a method for monitoring a power amplifier fault provided by an embodiment of the present invention;

[0038] Figure 2 A schematic structural diagram of a fault monitoring device for a power amplifier provided by an embodiment of the present invention.

[0039] Explanation of the reference numerals: 10 - monitoring unit setting module, 20 - working status information acquisition module, 30 - fault determination result acquisition module, 40 - fault point determination module, 50 - monitoring feedback data generation module. DETAILED DESCRIPTION

[0040] The present invention provides a method and device for monitoring faults of a power amplifier, which are used to solve the technical problem in the prior art that the working state information of the power amplifier cannot be obtained timely and accurately, resulting in inaccurate fault judgment.

[0041] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Embodiment 1, as Figure 1 As shown, the present invention provides a fault monitoring method for a power amplifier, the method comprising:

[0043] Step S100: Setting a monitoring unit at a key node of the power amplifier, including an ARM processor, an ADC sampling chip, a Hall sensor, and a temperature and humidity sensor.

[0044] Specifically, monitoring units are set for the key nodes of the power amplifier. First, the key nodes are usually the core parts of the power amplifier that determine its performance and stability, such as the input and output ports. The signal conditions here directly affect the overall effect and are susceptible to external interference; there are also around the power amplifier components. These components are the key to achieving power amplification and their working state is crucial; and the power supply part. A stable power supply is the basis for the normal operation of the equipment. In the monitoring unit, the ARM processor coordinates the work of the ADC sampling chip, Hall sensor, temperature and humidity sensor, etc. on the one hand, and performs in-depth processing and analysis on the collected data on the other hand. The ADC sampling chip is responsible for converting analog signals into digital signals. For analog quantities such as voltage and current in the power amplifier, it quantizes them at a specific sampling frequency and accuracy, so that continuous physical quantities become discrete digital quantities that can be processed by the processor to ensure the accuracy of the measurement. The Hall sensor focuses on non-contact measurement of current. Based on the Hall effect, it can accurately sense the current size through magnetic field changes without affecting the circuit, especially in the high current environment of the power amplifier. The temperature and humidity sensors always pay attention to the temperature and humidity conditions of the environment in which the equipment is located, because changes in temperature and humidity have potential effects on the performance and life of the power amplifier. These monitoring units work together to provide strong support for the stable operation and fault monitoring of the power amplifier.

[0045] Step S200: Based on the ADC sampling chip, Hall sensor, and temperature and humidity sensor, the voltage, current, temperature, and humidity monitoring data of the power amplifier are collected in real time, and the monitoring data are analyzed and identified through the built-in algorithm of the ARM processor to obtain working status information.

[0046] Specifically, first, the ADC sampling chip, the Hall sensor and the temperature and humidity sensor begin to work together. Among them, the ADC sampling chip periodically samples the voltage and current analog signals of the power amplifier at a specific frequency and converts them into digital quantities that can be processed. The Hall sensor relies on the Hall effect to accurately measure the current size indirectly by detecting the magnetic field strength without interfering with the circuit. The temperature and humidity sensor continuously senses the surrounding environment, uses the internal sensitive components to convert the physical quantities of temperature and humidity into electrical signals, and then processes them into digital signals. Then, the ARM processor begins to play a core role, receiving these digital monitoring data from different sensors, and using a variety of built-in algorithms for in-depth processing. For example, the noise interference in the data is removed by data filtering methods, such as mean filtering and median filtering to make the data more accurate and reliable; feature extraction is performed to extract key characteristic parameters that can reflect the working status of the power amplifier from the data, such as calculating the mean and peak values ​​of voltage and current, analyzing the changing trend and fluctuation range of temperature and humidity; and statistical analysis is also used to evaluate the stability and degree of change of the data. Finally, after comprehensive judgment, the ARM processor determines the working status information of the power amplifier from these data. If all data are within the normal range, the equipment is in normal working condition; once abnormal voltage, excessive current, high temperature or high humidity occur, it means that the power amplifier is faulty or abnormal, which provides a key basis for subsequent fault diagnosis and equipment maintenance.

[0047] Step S300: Perform fault determination according to the working status information to obtain a fault determination result.

[0048] Specifically, the working status information is the key basis for fault judgment. The obtained working status information is deeply interpreted. These working status information include the voltage, current, temperature, humidity and other data of the power amplifier as well as their changing trends and mutual relationships. After comprehensively considering these factors, the fault judgment rules are used to make a judgment, and finally a clear fault judgment result is obtained, that is, whether the power amplifier has a fault. If there is a fault, it will provide an important basis for subsequent fault location and processing; if there is no fault, the power amplifier can continue to operate normally.

[0049] Step S400: When the fault determination result is yes, analyze and locate the fault point according to the monitoring data.

[0050] Specifically, when the fault judgment result is "yes", the fault is analyzed and located based on the monitoring data. First, analyze the monitoring data collected previously, which includes the precise voltage collected by the ADC sampling chip, the current information measured by the Hall sensor, and the ambient temperature and humidity data obtained by the temperature and humidity sensor. In the monitoring data analysis phase, the collected data is subjected to in-depth statistical analysis, such as calculating the mean, variance, maximum value and other statistics to observe its distribution and change trend, and paying attention to the mutation point to assist in determining the approximate time range of the fault. Then, these data are closely related to the structure and working principle of the power amplifier, and the functions and relationships of each module and component are fully considered to better understand the problems reflected by the data. Then, fault mode identification is performed. For example, when overloaded, there will be excessive current and increased temperature. Short circuit will cause a sharp increase in current. Abnormal temperature will be too high or too low. After that, key node analysis is performed, focusing on nodes prone to failure such as power input ports, amplifier module input and output ports. Then, by comparing the data when the fault occurs with the data during normal operation, the differences are found. Finally, the position of the fault point is accurately located based on the data comparison results, laying a solid foundation for subsequent fault repair work.

[0051] Step S500: Establish a mapping association between the fault point and the fault determination result to generate monitoring feedback data.

[0052] Specifically, establishing a mapping association between the fault point and the fault judgment result plays a key role. First, the specific fault point information that has been determined, such as a specific electronic component (such as a damaged capacitor or resistor), a specific circuit line (such as a line section with an open circuit or short circuit), or a module (such as a subunit in an amplifier module), etc., is matched with the fault judgment result obtained previously. The establishment of this mapping association clearly shows the complete path and logical relationship from the initial discovery of the fault (the fault judgment result is "yes") to the precise location of the fault point. Generate monitoring feedback data, which contains rich information. On the one hand, there is a detailed description of the fault point, including the physical location of the fault point (the coordinates on the circuit board or the position mark in the circuit), the type of fault point (whether it is a component fault, a line fault or other type of fault), and the specific manifestation of the fault (such as short circuit, open circuit, abnormal parameter change, etc.). On the other hand, it also includes relevant information about the corresponding fault judgment results, such as which monitoring data (specific values ​​and changes of current, voltage, temperature, humidity, etc.) the fault judgment result is based on, providing clear fault guidance, which can quickly and accurately find the fault point and take corresponding repair measures, greatly improving the efficiency of fault repair.

[0053] In a possible implementation, step S200 specifically includes:

[0054] Step S210: using a voltage divider circuit to reduce the circuit voltage of the power amplifier to the range of the ADC sampling chip to obtain a voltage to be measured, and converting the analog signal of the voltage to be measured into a digital signal through the ADC sampling chip to obtain voltage monitoring data.

[0055] Step S220: Acquire the magnetic field of the conductor through the Hall sensor, determine the current intensity according to the change of the magnetic field of the conductor, and obtain current monitoring data.

[0056] Step S230: Detecting and uploading the temperature and humidity of the power amplifier through the temperature and humidity sensor to obtain temperature monitoring data and humidity monitoring data.

[0057] Specifically, the voltage divider circuit is a commonly used circuit structure that realizes proportional voltage division of the input voltage by connecting resistors of different resistance values ​​in series. Its purpose is to reduce the high voltage that may originally exceed the range of the ADC sampling chip to a range that the chip can accurately measure. The ADC sampling chip receives the voltage to be measured after voltage division, and uses its internal analog-to-digital conversion mechanism to convert the analog voltage signal into a digital signal, which usually involves periodic sampling and quantization of the analog voltage. The analog voltage value of each sampling point is quantized into a corresponding digital code, which constitutes the voltage monitoring data, which can be analyzed and processed by the subsequent processor.

[0058] The Hall sensor works based on the Hall effect. When current passes through a wire, a magnetic field is generated around the wire. The Hall sensor is placed close to the wire and can detect the strength and changes of this magnetic field. According to the principle of the Hall effect, the strength of the magnetic field is proportional to the magnitude of the current. Therefore, by measuring the changes in the magnetic field of the wire, the Hall sensor can indirectly determine the strength of the current. The sensor converts the magnetic field signal into an electrical signal, and after internal processing and conversion, it finally outputs the current monitoring data, which reflects the magnitude and changes of the current in the wire.

[0059] The temperature and humidity sensor contains components that are sensitive to temperature and humidity, such as thermistors for sensing temperature changes and humidity-sensitive capacitors for detecting humidity changes. For temperature monitoring, the resistance value of the thermistor will change accordingly with changes in the ambient temperature. By measuring the change in resistance value and based on the characteristic curve of the sensor, the current temperature value can be determined. For humidity monitoring, the capacitance value of the humidity-sensitive capacitor will change with changes in ambient humidity. Similarly, by measuring the change in capacitance value and based on the characteristics and calibration data of the sensor, the humidity value of the environment can be obtained. The sensor converts these physical quantities of temperature and humidity into electrical signals. After processing and digitization, it outputs temperature monitoring data and humidity monitoring data respectively, providing important information for understanding the environmental conditions of the power amplifier.

[0060] In a possible implementation, before step S100, there are:

[0061] Step S80: construct a first amplifier module based on a digital power amplifier, construct a second amplifier module based on a linear power amplifier, connect the first amplifier module and the second amplifier module in parallel, and connect them to a central control module to obtain the power amplifier, wherein the central control module has a switching mechanism, and the switching mechanism is to switch between the first amplifier module and the second amplifier module according to load and test requirement parameters.

[0062] Step S90: according to the framework structure of the power amplifier, the power input port, the input and output nodes of the first amplifier module, the input and output nodes of the second amplifier module and the input and output nodes of the central control module are used as the key nodes.

[0063] Specifically, the first amplifier module and the second amplifier module are constructed based on the digital power amplifier and the linear power amplifier, respectively. For the first amplifier module, by selecting a suitable digital power amplifier chip or integrated circuit as the core, the peripheral circuits including power supply, input signal interface, output filtering, etc. are designed. For the second amplifier module, it is necessary to select appropriate linear power amplifier devices such as transistors, design bias circuits to determine the appropriate static operating point so that it works in the linear amplification area, and construct feedback circuits and input and output circuits. Then the two modules are connected in parallel, and power distribution and synthesis circuits are used during the process to ensure that the input signals are synchronized and the output signals are reasonably superimposed, and load sharing and thermal management are also taken into account. Then they are connected to the central control module, which is usually a microcontroller or digital signal processor, responsible for overall control and management, which is achieved by connecting the control signal input terminal and receiving the feedback signal. Among them, the central control module has a unique switching mechanism, which will switch between the two amplifier modules according to the load and test requirement parameters. For example, when the load changes, if the load is small and the efficiency requirement is high, it will switch to the digital power amplifier module; when there are extremely high requirements for sound quality, it may switch to the linear power amplifier module. During the test process, it will also select the appropriate amplifier module according to different test items and indicator requirements, thereby making the entire power amplifier system more flexible and efficient.

[0064] Clarify the key nodes based on the framework structure of the power amplifier. The power input port is the starting point of energy supply, and its condition is related to the power stability of the entire system. The input and output nodes of the first and second amplifier modules are crucial to the signal processing of their respective modules, affecting the amplification effect and the quality of the final output. The input and output nodes of the central control module are responsible for receiving and sending control information and coordinating the work of various parts. These key nodes play a key role in the operation and performance of the power amplifier. Monitoring and controlling them is an important part of ensuring the normal operation of the power amplifier.

[0065] In a possible implementation, step S200 further includes:

[0066] Step S240: Locate and execute the amplifier module according to the monitoring data to determine the data execution path.

[0067] Step S250: According to the data execution path, the monitoring data is spliced ​​to construct a target data chain.

[0068] Step S260: Based on the type of the execution amplifier module, feature extraction is performed on the target data link, and voltage and current signal waveforms and temperature and humidity change curves are constructed according to the data features.

[0069] Step S270: Obtain the working status information according to the characteristic change amount of the voltage and current signal waveforms and the temperature and humidity change curve.

[0070] Specifically, the execution amplifier module refers to the amplifier module (i.e., the first amplifier module or the second amplifier module) that is performing data processing and signal amplification. The specific amplifier module that is performing the work is located based on the specific identification or characteristics contained in the monitoring data (such as a specific module number, signal frequency range, signal strength characteristics, etc.). At the same time, it is also necessary to connect and analyze the monitoring data of each node in the entire process from input to output based on the transmission path of the input data between amplifiers and to accurately determine the data execution path, that is, to clarify the complete route of how the input data passes through the first or second amplifier and other parts in sequence to the final output, so as to provide key basic information for subsequent operations and analysis.

[0071] After the data execution path is determined, the monitoring data from different stages and parts are spliced ​​along the path. For example, the data from the voltage sensor, current sensor, temperature sensor and humidity sensor for the same amplifier module in the same time period are combined in chronological order or a specific logical order. Building the target data chain is to form an ordered data set with these spliced ​​data, so that there is a clear correlation and logical relationship between the data, so as to facilitate a more comprehensive and in-depth analysis later.

[0072] Different types of executive amplifier modules (digital power amplifier modules or linear power amplifier modules) differ in their working characteristics and signal processing methods, so targeted feature extraction is required according to their types. For voltage and current signals, the peak, valley, period, frequency and other characteristics of the signal are determined by sampling and analyzing their data, and then the corresponding waveform is constructed. For example, for a sine wave signal, its amplitude, frequency and phase characteristics can be extracted to draw a waveform. For temperature and humidity data, according to the data changes at different time points, with time as the horizontal axis and temperature or humidity value as the vertical axis, a change curve is constructed to reflect its change trend and fluctuation range over time.

[0073] The characteristic changes of the voltage and current signal waveforms include the degree of waveform distortion, sudden changes in amplitude, frequency offset, etc. For example, if the voltage signal is a standard sine wave under normal circumstances and the waveform is distorted or harmonics increase, it indicates that there may be a fault or abnormal working state. The characteristic changes of the temperature and humidity change curve can be a sharp rise or fall in temperature, fluctuations beyond the normal range, abnormal changes in humidity, etc. For example, a rapid increase in temperature in a short period of time means that there is a problem with the heat dissipation of the amplifier module or a component is overheated. By comprehensively analyzing these characteristic changes, combined with the preset normal working state standards and fault judgment rules, we can finally obtain information that can accurately reflect the working state of the power amplifier, including normal operation, potential fault risks, or faults that have occurred.

[0074] In a possible implementation, step S260 specifically includes:

[0075] Step S261: When the execution amplifier module is the first amplifier module, high-frequency switching noise filtering is performed on the current and voltage monitoring data in the target data chain, and then PWM signal demodulation is performed, and the demodulated analog signal is used as the actual output current and voltage to extract the time domain characteristics, frequency domain characteristics, and statistical characteristics of the current and voltage monitoring data, wherein the frequency domain characteristics include the switching frequency and its harmonic components.

[0076] Step S262: When the execution amplifier module is the second amplifier module, low-frequency and high-frequency noise filtering is performed on the current and voltage monitoring data in the target data chain to extract the time domain characteristics, frequency domain characteristics, and statistical characteristics of the current and voltage monitoring data, wherein the frequency domain characteristics include the main frequency component and its harmonic distortion characteristics.

[0077] Specifically, when the execution amplifier module is the first amplifier module, the current and voltage monitoring data in the target data chain are first filtered for high-frequency switching noise. Because when the first amplifier module composed of the digital power amplifier is working, the high-frequency switching of the switching element will generate interfering high-frequency switching noise. These noises can be removed by filtering technology to make the data more accurate. Then the PWM signal is demodulated. Since the digital power amplifier often uses PWM technology, the PWM signal is a digital signal, which needs to be demodulated into a continuous analog signal to reflect the actual current and voltage output. Then, various features of the current and voltage monitoring data are extracted. In terms of time domain features, information such as signal amplitude, period, rise time, etc. can be obtained to intuitively reflect the changes of the signal on the time axis; in frequency domain features, the switching frequency and its harmonic components are very critical, which can help understand the working state of the power amplifier and the signal spectrum distribution; in statistical features, such as the skewness and kurtosis of voltage and current, can be used to determine whether the data distribution is normal and whether there are abnormal conditions. The extraction of these features provides an important basis for subsequent analysis and judgment.

[0078] When the execution amplifier module is the second amplifier module (linear power amplifier), the current and voltage monitoring data in the target data chain are first filtered for low-frequency and high-frequency noise, because the linear power amplifier will be affected by low-frequency noise such as thermal noise, 1 / f noise and high-frequency noise such as external electromagnetic interference when working, which will interfere with the accuracy of the monitoring data. After filtering, the time domain characteristics (such as the amplitude and period of the signal, which can intuitively reflect the change of the signal over time), frequency domain characteristics (the main frequency component and its harmonic distortion characteristics are very important, the main frequency component is the frequency of the input signal, and the harmonic distortion characteristics reflect the size of the harmonic component in the output signal, which can evaluate the linearity and distortion of the amplifier) ​​and statistical characteristics (used to judge the distribution and abnormality of the data). Through the extraction of these features, the working state and signal characteristics of the linear power amplifier can be more comprehensively and deeply understood, providing strong support for subsequent analysis and judgment.

[0079] In a possible implementation, step S300 specifically includes:

[0080] Step S310: according to the data execution path, a node relationship with the work status information is established according to key nodes in the path.

[0081] Step S320: performing node waveform change amplitude comparison according to the node relationship, and when the node waveform change amplitude reaches a standard threshold, performing fault determination according to the waveform change amplitude comparison result.

[0082] Step S330: When the node waveform change amplitude does not reach the standard threshold, extract the historical waveform change amplitude comparison result based on the key node, perform time series amplitude comparison, and make a fault judgment based on the time series amplitude comparison result.

[0083] Specifically, the data execution path plays a key guiding role. The data execution path clearly shows the key nodes that the monitoring data passes through from input to output. For example, starting from the power input port, passing through the input node of the first or second amplifier module, the internal processing unit, and then to the output node. The working status information reflects the operating status of the entire power amplifier system at different nodes, such as the magnitude of voltage and current, the value of temperature and humidity, and their changing trends. Establishing a node relationship is to associate each key node in the data execution path with the corresponding working status information. For example, the voltage monitoring data of the power input port is linked to the working status of the port to clarify the normal working range of the port under different voltage values, possible abnormal conditions, etc.; for the input and output nodes of the amplifier module, its current and voltage monitoring data are associated with the signal transmission and amplification functions of the node to understand whether the module works normally under different current and voltage waveforms.

[0084] The node waveform change amplitude comparison is to compare and analyze the waveform change amplitudes at different key nodes. The waveform can be a voltage waveform, a current waveform, or other signal waveforms related to the working state. Each key node has a relatively stable waveform change range under normal working conditions. When performing node waveform change amplitude comparison, a standard threshold is first determined. This standard threshold is determined based on the design parameters of the power amplifier, historical operating data, experience and other factors. For example, for a specific voltage node, a reasonable standard threshold for the voltage waveform change amplitude is set according to the voltage fluctuation range during normal operation. If the node waveform change amplitude reaches this standard threshold, it is necessary to make a fault judgment based on the waveform change amplitude comparison result. For example, if the voltage waveform change amplitude of a node exceeds the set standard threshold, it means that the node has a voltage instability problem, such as power supply fluctuations, component aging or damage, etc., so that it is preliminarily judged that the node may have a fault.

[0085] When the node waveform change amplitude does not reach the standard threshold, it does not mean that the system is in a completely normal state. At this time, it is necessary to further extract the historical waveform change amplitude comparison results based on the key nodes to perform timing amplitude comparison. The historical waveform change amplitude comparison results refer to the waveform change amplitude data of the node in the past period of time. Timing amplitude comparison is to compare the current waveform change amplitude with the historical data in the time series. Fault judgment is made based on the timing amplitude comparison results. If an abnormal change trend is found in the timing, even if the current waveform change amplitude does not reach the standard threshold, it indicates that the key node has potential faults or abnormal conditions, and further in-depth inspection and analysis are required, such as checking whether the performance of related circuit components has declined, whether there is poor contact, etc.

[0086] In a possible implementation, step S300 further includes:

[0087] Step S340: Perform comprehensive fault judgment based on the waveform change amplitude comparison result and the timing amplitude comparison result.

[0088] Specifically, when making a comprehensive fault judgment, the waveform change amplitude comparison results and the timing amplitude comparison results must be fully considered. The waveform change amplitude comparison results can intuitively reflect whether the current signal change amplitude of the key node is abnormal. For example, if the voltage or current waveform change amplitude of a node exceeds the standard threshold, it means that the node currently has abnormal fluctuations and corresponding faults. At the same time, it is also used to preliminarily determine the fault location. For example, the abnormality of the output node of the amplifier module suggests that there is a problem with the module or the subsequent circuit, while the timing amplitude comparison results start from the perspective of time series. By analyzing the change trend of the key nodes at different time points, it is determined whether there is a potential fault. Even if the current waveform change amplitude does not exceed the threshold, if there is an abnormal change trend different from the past in the timing, there is also a fault. Combining these two results, the status of the key nodes is comprehensively evaluated to more accurately judge the fault condition of the entire system and improve the accuracy and reliability of fault judgment.

[0089] In a possible implementation, step S340 specifically includes:

[0090] Step S341: Fault determination formula: , and obtain the comprehensive fault judgment probability, where is the comprehensive fault judgment probability, is the amplitude of the waveform change at the current node, is the fitting parameter for determining the waveform change amplitude comparison result, is the amplitude of the timing waveform change, is the fitting parameter for determining the time series amplitude comparison result, is the fault probability expression for fault judgment based on the waveform change amplitude comparison result, It is the fault probability expression for fault judgment based on the timing amplitude comparison result.

[0091] Step S342: Compare the comprehensive fault judgment probability with a preset fault threshold to obtain the fault judgment result.

[0092] Specifically, the fault judgment formula is: , Indicates the comprehensive fault judgment probability, according to the amplitude of the current node waveform change and the amplitude of the timing waveform change And the corresponding determination fitting parameters and Calculated. It is a fault probability expression for fault judgment based on the waveform change amplitude comparison result. When the current node waveform change amplitude Large, and determine the fitting parameters When appropriate, the value of this expression will increase, indicating that the probability of fault is high based on the waveform change amplitude comparison result. It is the fault probability expression for fault judgment based on the timing amplitude comparison result. There are large abnormal changes in the time series, and the fitting parameters are determined If it is reasonable, the value of the expression will also increase, which means that the probability of fault is higher according to the timing amplitude comparison result.

[0093] Calculate the comprehensive fault judgment probability After that, it is compared with the preset fault threshold, which is a critical value set based on the normal operating range of the power amplifier, historical fault data, experience and other factors. If the preset fault threshold is exceeded, it means that the power amplifier is more likely to fail, and the fault determination result is yes, that is, it is determined that there is a fault. If the preset fault threshold is exceeded, it is determined that there is no fault. In summary, by comparing this fault determination formula with the preset fault threshold, it is possible to comprehensively determine whether the power amplifier has a fault, thereby improving the accuracy and reliability of the fault determination.

[0094] Embodiment 2

[0095] Based on the same inventive concept as the fault monitoring method of a power amplifier in the aforementioned embodiment, Figure 2 As shown, the present invention provides a fault monitoring device for a power amplifier, and the device and method embodiments in the embodiments of the present invention are based on the same inventive concept. The device includes:

[0096] The monitoring unit setting module 10 is used to set a monitoring unit at a key node of the power amplifier, including an ARM processor, an ADC sampling chip, a Hall sensor, and a temperature and humidity sensor.

[0097] The working status information acquisition module 20 collects the voltage, current, temperature and humidity monitoring data of the power amplifier in real time based on the ADC sampling chip, Hall sensor and temperature and humidity sensor, and analyzes and identifies the monitoring data through the built-in algorithm of the ARM processor to obtain the working status information.

[0098] The fault determination result acquisition module 30 is used to perform fault determination according to the working state information to obtain a fault determination result.

[0099] The fault point determination module 40 is used to perform analysis and positioning according to the monitoring data to determine the fault point when the fault determination result is yes.

[0100] The monitoring feedback data generating module 50 is used to establish a mapping association between the fault point and the fault determination result to generate monitoring feedback data.

[0101] Specifically, the working status information acquisition module 20 includes:

[0102] A voltage monitoring data acquisition unit is used to use a voltage divider circuit to reduce the circuit voltage of the power amplifier to the range of the ADC sampling chip to obtain a voltage to be measured, and convert the analog signal of the voltage to be measured into a digital signal through the ADC sampling chip to obtain voltage monitoring data.

[0103] A current monitoring data acquisition unit is used to acquire the magnetic field of the conductor through a Hall sensor, determine the current intensity according to the change of the magnetic field of the conductor, and obtain current monitoring data.

[0104] The temperature and humidity monitoring data acquisition unit is used to detect and upload the temperature and humidity of the power amplifier through the temperature and humidity sensor to obtain temperature monitoring data and humidity monitoring data.

[0105] Furthermore, the fault monitoring device for the power amplifier further comprises:

[0106] An amplifier module construction unit, wherein the amplifier module construction unit constructs a first amplifier module based on a digital power amplifier, constructs a second amplifier module based on a linear power amplifier, connects the first amplifier module and the second amplifier module in parallel, and connects them to a central control module to obtain the power amplifier, wherein the central control module has a switching mechanism, and the switching mechanism is for switching between the first amplifier module and the second amplifier module according to load and test requirement parameters.

[0107] A key node determination unit, wherein the key node determination unit is used to use the power input port, the input and output nodes of the first amplifier module, the input and output nodes of the second amplifier module and the input and output nodes of the central control module as the key nodes according to the framework structure of the power amplifier.

[0108] Furthermore, the working status information acquisition module 20 also includes:

[0109] A data execution path determination unit is used to locate the execution amplifier module according to the monitoring data and determine the data execution path.

[0110] A target data chain construction unit is used to splice the monitoring data according to the data execution path to construct a target data chain.

[0111] A feature extraction unit is used to extract features of the target data link based on the type of the execution amplifier module, and to construct voltage and current signal waveforms and temperature and humidity change curves according to data features.

[0112] A working status information acquisition unit is used to obtain the working status information according to the characteristic change amount of the voltage and current signal waveforms and the temperature and humidity change curve.

[0113] Specifically, the feature extraction unit includes:

[0114] A high-frequency switching noise filtering unit is used to perform high-frequency switching noise filtering on the current and voltage monitoring data in the target data chain when the execution amplifier module is the first amplifier module, and then perform PWM signal demodulation, and use the demodulated analog signal as the actual output current and voltage to extract the time domain characteristics, frequency domain characteristics, and statistical characteristics of the current and voltage monitoring data, wherein the frequency domain characteristics include the switching frequency and its harmonic components.

[0115] A low- and high-frequency noise filtering unit, wherein the low- and high-frequency noise filtering unit is used to perform low-frequency and high-frequency noise filtering on the current and voltage monitoring data in the target data chain when the execution amplifier module is the second amplifier module, and extract the time domain characteristics, frequency domain characteristics, and statistical characteristics of the current and voltage monitoring data, wherein the frequency domain characteristics include the main frequency component and its harmonic distortion characteristics.

[0116] Specifically, the fault determination result acquisition module 30 includes:

[0117] A node relationship establishing unit is used to establish a node relationship with the work status information according to the key nodes in the path based on the data execution path.

[0118] A fault determination unit is used to compare the node waveform change amplitudes according to the node relationship, and when the node waveform change amplitude reaches a standard threshold, a fault determination is performed according to the waveform change amplitude comparison result.

[0119] A timing amplitude comparison unit is used to extract historical waveform change amplitude comparison results based on the key nodes when the waveform change amplitude of the node does not reach the standard threshold, perform timing amplitude comparison, and make a fault judgment based on the timing amplitude comparison results.

[0120] Furthermore, the fault determination result acquisition module 30 further includes:

[0121] A comprehensive fault determination unit is used to perform comprehensive fault determination based on the waveform change amplitude comparison result and the timing amplitude comparison result.

[0122] Specifically, the comprehensive fault determination unit includes:

[0123] A fault determination probability unit is used to determine the fault through the following formula: , and obtain the comprehensive fault judgment probability, where is the comprehensive fault judgment probability, is the amplitude of the waveform change at the current node, is the fitting parameter for determining the waveform change amplitude comparison result, is the amplitude of the timing waveform change, is the fitting parameter for determining the time series amplitude comparison result, is the fault probability expression for fault judgment based on the waveform change amplitude comparison result, It is the fault probability expression for fault judgment based on the timing amplitude comparison result.

[0124] A fault determination result acquisition unit is used to compare the comprehensive fault determination probability with a preset fault threshold to obtain the fault determination result.

[0125] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0126] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

[0127] This specification and the accompanying drawings are merely exemplary illustrations of the present invention and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present invention. Obviously, a person skilled in the art may make various changes and modifications to the present invention without departing from the scope of the present invention. Thus, the present invention is intended to include such changes and modifications if they fall within the scope of the present invention and its equivalents.

Claims

1. A method for monitoring a power amplifier fault, characterized in that: include: A monitoring unit is set up at the key nodes of the power amplifier, including an ARM processor, an ADC sampling chip, a Hall sensor, and a temperature and humidity sensor; Based on the ADC sampling chip, Hall sensor and temperature and humidity sensor, the voltage, current, temperature and humidity monitoring data of the power amplifier are collected in real time, and the monitoring data are analyzed and identified through the built-in algorithm of the ARM processor to obtain the working status information; Perform fault determination according to the working status information to obtain a fault determination result; When the fault determination result is yes, analyzing and locating the fault point according to the monitoring data; Establishing a mapping association between the fault point and the fault determination result to generate monitoring feedback data; Monitoring units are set up at key nodes of the power amplifier. Previously, there were: A first amplifier module is constructed based on a digital power amplifier, and a second amplifier module is constructed based on a linear power amplifier. The first amplifier module and the second amplifier module are connected in parallel and connected to a central control module to obtain the power amplifier; wherein the central control module has a switching mechanism, and the switching mechanism is to switch between the first amplifier module and the second amplifier module according to load and test requirement parameters; According to the framework structure of the power amplifier, the power input port, the input and output nodes of the first amplifier module, the input and output nodes of the second amplifier module and the input and output nodes of the central control module are used as the key nodes; The monitoring data is analyzed and identified through the built-in algorithm of the ARM processor to obtain working status information, which specifically includes: Locate and execute the amplifier module according to the monitoring data to determine the data execution path; According to the data execution path, the monitoring data is spliced ​​to construct a target data chain; Based on the type of the execution amplifier module, feature extraction is performed on the target data link, and voltage and current signal waveforms and temperature and humidity change curves are constructed according to the data features; Obtaining the working status information according to the characteristic changes of the voltage and current signal waveforms and the temperature and humidity change curves; Performing fault determination according to the working status information specifically includes: According to the data execution path, establishing a node relationship with the work status information according to key nodes in the path; Performing node waveform change amplitude comparison according to the node relationship, and when the node waveform change amplitude reaches a standard threshold, performing fault determination according to the waveform change amplitude comparison result; When the waveform change amplitude of the node does not reach the standard threshold, extract the historical waveform change amplitude comparison result based on the key node, perform time series amplitude comparison, and make a fault judgment according to the time series amplitude comparison result; Performing fault determination according to the working status information also includes: Performing a comprehensive fault determination based on the waveform change amplitude comparison result and the timing amplitude comparison result; The obtaining of the fault determination result specifically includes: Fault determination formula: , and obtain the comprehensive fault judgment probability, where is the comprehensive fault judgment probability, is the amplitude of the waveform change at the current node, is the fitting parameter for determining the waveform change amplitude comparison result, is the amplitude of the timing waveform change, is the fitting parameter for determining the time series amplitude comparison result, is the fault probability expression for fault judgment based on the waveform change amplitude comparison result, is the fault probability expression for fault determination based on the timing amplitude comparison result; The fault determination result is obtained by comparing the comprehensive fault determination probability with a preset fault threshold.

2. The method for monitoring a power amplifier fault according to claim 1, wherein: Based on the ADC sampling chip, Hall sensor and temperature and humidity sensor, the voltage, current, temperature and humidity monitoring data of the power amplifier are collected in real time, specifically including: Using a voltage divider circuit to reduce the circuit voltage of the power amplifier to the range of the ADC sampling chip to obtain a voltage to be measured, and converting the analog signal of the voltage to be measured into a digital signal through the ADC sampling chip to obtain voltage monitoring data; The magnetic field of the conductor is obtained by the Hall sensor, and the current intensity is determined according to the change of the magnetic field of the conductor to obtain the current monitoring data; The temperature and humidity of the power amplifier are detected and uploaded by the temperature and humidity sensor to obtain temperature monitoring data and humidity monitoring data.

3. The method for monitoring a fault of a power amplifier according to claim 1, wherein: The extracting features of the target data link based on the type of the execution amplifier module specifically includes: When the execution amplifier module is the first amplifier module, high-frequency switching noise filtering is performed on the current and voltage monitoring data in the target data chain, and then PWM signal demodulation is performed, and the demodulated analog signal is used as the actual output current and voltage to extract the time domain characteristics, frequency domain characteristics and statistical characteristics of the current and voltage monitoring data, wherein the frequency domain characteristics include the switching frequency and its harmonic components; When the execution amplifier module is the second amplifier module, low-frequency and high-frequency noise filtering is performed on the current and voltage monitoring data in the target data chain to extract the time domain characteristics, frequency domain characteristics and statistical characteristics of the current and voltage monitoring data, wherein the frequency domain characteristics include the main frequency component and its harmonic distortion characteristics.

4. A power amplifier fault monitoring device, used to execute the power amplifier fault monitoring method according to any one of claims 1 to 3, characterized in that: include: A monitoring unit setting module is used to set a monitoring unit at a key node of the power amplifier, wherein the monitoring unit includes an ARM processor, an ADC sampling chip, a Hall sensor, and a temperature and humidity sensor; A working status information acquisition module, based on the ADC sampling chip, the Hall sensor and the temperature and humidity sensor, collects the voltage, current, temperature and humidity monitoring data of the power amplifier in real time, analyzes and identifies the monitoring data through the built-in algorithm of the ARM processor, and obtains the working status information; A fault determination result acquisition module is used to perform fault determination according to the working state information and obtain a fault determination result; A fault point determination module is used to analyze and locate the fault point according to the monitoring data when the fault determination result is yes; The monitoring feedback data generating module is used to establish a mapping association between the fault point and the fault determination result to generate monitoring feedback data.

5. The fault monitoring device for a power amplifier according to claim 4, characterized in that: The monitoring unit setting module also includes an amplifier module construction unit and a key node determination unit; The amplifier module construction unit constructs a first amplifier module based on a digital power amplifier, constructs a second amplifier module based on a linear power amplifier, connects the first amplifier module and the second amplifier module in parallel, and connects them to a central control module to obtain the power amplifier; wherein the central control module has a switching mechanism, and the switching mechanism is to switch between the first amplifier module and the second amplifier module according to load and test requirement parameters; The key node determination module is used to use the power input port, the input and output nodes of the first amplifier module, the input and output nodes of the second amplifier module and the input and output nodes of the central control module as the key nodes according to the framework structure of the power amplifier.

Images