Arc fault detection circuit, method, device, storage medium and program product
By using a solid-state conductive microphone to detect arc faults, and combining the characteristics of sound waves and electrical energy, the shortcomings of traditional detection methods are overcome, achieving higher detection accuracy and reliability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-13
- Publication Date
- 2026-03-13
AI Technical Summary
Traditional arc fault detection methods are limited in scope, resulting in insufficient completeness, accuracy, and reliability of detection.
The acoustic wave signal conducted by the circuit under test is detected by a solid conductive microphone, and combined with the electrical energy signal, the characteristics of arc energy acoustic wave and electrical energy are extracted to determine the result of arc fault.
It improves the integrity, accuracy and reliability of arc fault detection, reduces the attenuation and distortion of acoustic signals, and improves the detection quality.
Smart Images
Figure CN121656752A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the electrical field, and more particularly to an arc fault detection circuit, method, device, storage medium, and program product. Background Technology
[0002] An arc fault is an electrical fault in which an electric arc occurs in a circuit. When an arc fault occurs, it is easy to generate high temperatures and heat, which may ignite the circuit and pose a fire hazard.
[0003] In traditional technology, electrical energy characteristics are analyzed based on signals such as voltage, current, and spectrum in the circuit to determine whether an arc fault exists.
[0004] Traditional detection methods are relatively simple, relying solely on analyzing electrical energy characteristics to determine the presence of abnormalities, which leads to issues with the completeness, accuracy, and reliability of arc fault detection. Summary of the Invention
[0005] This application provides an arc fault detection circuit, method, device, storage medium, and program product to improve the integrity, accuracy, and reliability of arc fault detection.
[0006] In a first aspect, embodiments of this application provide an arc fault detection circuit, including:
[0007] A solid-state conductive microphone is used to detect sound wave signals conducted by the circuit under test and convert the sound wave signals into acoustic-electric signals for output. The solid-state conductive microphone is placed on the circuit under test and is connected to the processing module.
[0008] The power wave detection module is used to detect the electrical energy signal of the circuit under test; the power wave detection module is connected to the processing module.
[0009] The processing module is used to extract arc energy acoustic wave characteristics based on acoustic and electrical signals, determine electrical energy characteristics based on electrical energy signals, and determine the arc fault result of the circuit under test based on the arc energy acoustic wave characteristics and electrical energy characteristics.
[0010] In one possible implementation, the circuit under test includes a power supply line between the power source and the load, and connected to the power source output.
[0011] In one possible implementation, the circuit under test further includes a return line between the power supply and the load, and connected to the power supply return terminal.
[0012] In one possible implementation, the solid-state conductive microphone is connected to a connection terminal of the circuit under test, which is a terminal for connecting a load; or, the solid-state conductive microphone is disposed in contact with the conductor surface of the circuit under test.
[0013] Secondly, embodiments of this application provide an arc fault detection method, including:
[0014] A solid-state conductive microphone is installed on the circuit under test to detect the sound wave signal transmitted by the circuit under test and convert the sound wave signal into an acoustic-electric signal for output.
[0015] Detect the electrical signal of the circuit under test;
[0016] Arc energy acoustic wave characteristics are extracted based on acoustic and electrical signals, electrical energy characteristics are determined based on electrical energy signals, and the arc fault result of the circuit under test is determined based on the arc energy acoustic wave characteristics and electrical energy characteristics.
[0017] In one possible implementation, the arc fault result of the circuit under test is determined based on the arc energy acoustic wave characteristics and electrical energy characteristics, including: comparing and analyzing the arc energy acoustic wave characteristics and preset arc energy acoustic wave characteristics to obtain arc energy detection results; comparing and analyzing the electrical energy characteristics and preset electrical energy characteristics to obtain electrical energy detection results; and determining the arc fault result of the circuit under test based on the arc energy detection results and electrical energy detection results.
[0018] Thirdly, embodiments of this application provide an arc fault detection device, comprising:
[0019] The acoustic wave detection module is used to detect the acoustic wave signal transmitted by the circuit under test through a solid conductive microphone installed on the circuit under test, and convert the acoustic wave signal into an acoustic-electric signal for output.
[0020] The power wave detection module is used to detect the electrical energy signal of the circuit under test.
[0021] The processing module is also used to extract arc energy acoustic wave characteristics based on acoustic and electrical signals, determine electrical energy characteristics based on electrical energy signals, and determine the arc fault result of the circuit under test based on the arc energy acoustic wave characteristics and electrical energy characteristics.
[0022] Fourthly, embodiments of this application provide an arc fault detection device, including: a memory and a processor;
[0023] The memory stores computer-executed instructions;
[0024] The processor executes computer execution instructions stored in the memory, causing the processor to perform the second aspect and / or various possible implementations of the second aspect as described above.
[0025] Fifthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the second aspect and / or various possible implementations of the second aspect as described above.
[0026] Sixthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the second aspect and / or various possible implementations of the second aspect as described above.
[0027] The arc fault detection circuit, method, device, storage medium, and program product provided in this application embodiment detects the acoustic wave signal transmitted through the circuit under test using a solid-state conductive microphone and outputs the corresponding acoustic-electric signal. Based on the acoustic-electric signal analysis, the arc energy characteristics and electrical energy characteristics of the circuit under test are obtained, and the arc fault result of the circuit under test is determined by combining the arc energy characteristics and electrical energy characteristics. By superimposing the arc energy characteristics on the arc fault detection based on the electrical energy characteristics, the accuracy and reliability of arc fault detection are improved. Furthermore, acoustic waves are affected by environmental noise and obstacles during air propagation, leading to attenuation and distortion, making it difficult to accurately detect arc energy characteristics. This application uses a solid-state conductive microphone to detect the acoustic wave signal transmitted through the solid of the circuit under test. This results in fast transmission speed, low transmission loss, and minimal low-frequency loss, greatly reducing the attenuation and distortion of the acoustic wave signal, improving the quality of the detected acoustic wave signal, and further enhancing the completeness, accuracy, and reliability of arc fault detection. Attached Figure Description
[0028] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0029] Figure 1 A schematic diagram of the arc fault detection provided in this application;
[0030] Figure 2 This is a schematic diagram of an arc fault detection circuit provided in one embodiment of this application;
[0031] Figure 3 This is a schematic diagram of an arc fault detection circuit provided in another embodiment of this application;
[0032] Figure 4 This is a schematic diagram of an arc fault detection circuit provided in another embodiment of this application;
[0033] Figure 5 A flowchart illustrating the arc fault detection method provided in this application;
[0034] Figure 6 This is a schematic diagram illustrating the application of the arc fault detection method of this application in a specific scenario.
[0035] Figure 7 This is a schematic diagram illustrating the application of the arc fault detection method of this application in another scenario;
[0036] Figure 8 A schematic diagram of the arc fault detection device provided in this application;
[0037] Figure 9 This is a schematic diagram of the arc fault detection equipment provided in this application.
[0038] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation
[0039] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0040] First, let me explain the terms used in this application:
[0041] Arc fault: refers to an electrical fault in which an unintentional electric arc occurs in a live circuit. An electric arc is a gas discharge phenomenon. When current passes through certain insulating media, it will generate instantaneous sparks between contacts or electrodes. When an arc fault occurs, the center temperature is very high, which may be accompanied by metal splashes that can ignite flammable materials and cause an electrical fire.
[0042] A solid-state conductive microphone is a device that uses the scientific principle of sound transmission through solids to capture and convert sound wave signals. When sound waves are transmitted through solid materials, they cause elastic vibrations inside the object. These vibrations can be detected and converted into acoustic signals for processing. Solid materials are highly sensitive to vibration, and solid-state conductive microphones have high sensitivity. Therefore, solid-state conductive microphones can effectively isolate sound signals and electromagnetic interference from the outside air, improving the quality of sound wave signal transmission and detection.
[0043] Solid-state conductive microphones are contact microphones, meaning that when a solid-state conductive microphone detects sound wave signals, it needs to be in close contact with the solid medium through which the sound waves are conducted. For example, bone conduction microphones are solid-state conductive microphones, which use bone as the solid medium for conducting sound wave signals. The solid-state conductive microphone in this application uses the metal conductor of the circuit as the solid medium for conducting sound wave signals. The metal conductor can be a copper conductor, an aluminum conductor, an alloy conductor, etc.
[0044] In traditional technologies, arc faults cause power wave distortion. Arc fault detection methods determine whether an arc fault has occurred by detecting power wave distortion. Specifically, they track and analyze the voltage, current, phase, or spectrum signals of the power waves in the line, use a central processing unit for sampling and calculation, and determine whether an arc fault has occurred based on a preset arc fault threshold.
[0045] Traditional techniques use power wave detection to detect arc faults. However, since arc-like waves can also cause power wave distortion, the power wave detection method cannot distinguish between arc-like waves and arc faults. Therefore, the power wave detection method is prone to misdetection and misjudgment, resulting in problems with the completeness, accuracy, and reliability of arc fault detection.
[0046] In the field of circuit transmission, the detection of sound wave signals transmitted by conductors in a line using solid-state conductive microphones and their application in detecting arc faults is currently a blank area in both theoretical research and engineering practice; the principles involved in this application will be explained below.
[0047] First, the principle of detecting arc faults based on electrical energy characteristics and arc energy acoustic wave characteristics is explained. Arc faults are usually a comprehensive physical phenomenon in which sound, light, and electricity occur almost simultaneously. In this phenomenon, the electrical breakdown and glow discharge phenomena between the arc electrodes (including the electrodes themselves) caused by the power supply will excite the propagation and conduction of sound waves. Therefore, detecting the acoustic wave signal when an arc fault occurs can serve as a basis for detecting arc faults. Furthermore, by superimposing the detection of acoustic wave signals on the detection of electrical energy signals, the detection of arc energy acoustic wave characteristics can be superimposed on the detection of electrical energy characteristics, thereby improving the completeness, accuracy, and reliability of arc fault detection. This is the basic principle of arc fault detection in this application.
[0048] Specifically, the arc energy generated when an arc fault occurs consists of two parts: electrical energy and arc energy, namely: P 电弧 =P 电能 +P 弧能 ; Figure 1 This is a schematic diagram of arc fault detection, such as... Figure 1 As shown, the following derivation is performed:
[0049] Because: P i =P 电弧 +P L =P 电能 +P 弧能 +P L ;
[0050] P 电能 =U 电弧 ×I 电能 ;P 弧能 =U 电弧 ×I 弧能;
[0051] I L = I i ,U L = YU i ;
[0052] Therefore, P L = I i U i = P i ;
[0053] Suppose: I 电能 = XI i ; U 电弧 = YU i ; (0 ≤ X ≤ 1, 0 ≤ Y ≤ 1);
[0054] Then: I 弧能 = (1 - X)I i ; U 电弧 = YU i ;
[0055] Thus: P 弧能 = (1 - X)I i YU i = (1 - X)YP i ;
[0056] Note:
[0057] (1) When X = 1 and Y = 0, no arc occurs;
[0058] (2) When X = 0 and Y = 1, parallel arc occurs;
[0059] (3) When 0 < X < 1 and 0 < Y < 1, series arc occurs.
[0060] Therefore, based on the principle of P 电弧 = P 电能 + P 弧能 If the electrical energy and arc energy of the arc fault can be detected, when the arc fault occurs, it is possible to accurately detect whether the arc fault has occurred.
[0061] Secondly, the principle of detecting the sound wave signal conducted by the待测线路 (to-be-tested circuit) through the solid-conduction microphone is explained. Sound wave is a mechanical elastic wave. Those with a frequency below 20 Hz are called infrasonic waves, those with a frequency in the range of 20 Hz - 20 kHz are called audio sound waves, and those with a frequency above 20 kHz are called ultrasonic waves; Sound waves can be naturally conducted in solid materials. By studying and detecting the sound wave signal conducted in solid materials when an arc fault occurs, the arc fault can be detected based on this.
[0062] It should be noted that the term "待测线路" in the original text is not clear and should be replaced with a specific and accurate expression in a more formal context. Here, I have translated it as "to-be-tested circuit" tentatively.The conductors of the circuit under test are commonly made of copper, aluminum, or alloys. Conductors not only have electrical conductivity but also sound conduction capabilities, or the ability to transmit sound. In other words, the sound wave signal generated by an electric arc fault can be conducted through the conductor of the circuit under test. This application studies the physical phenomenon of sound wave signal transmission through a conductor. The research shows that when the sound wave signal generated by an electric arc fault is transmitted through a conductor, it can be effectively detected at a distance from the sound source (e.g., more than 500 meters). This detection is achieved by transmitting the sound wave signal through a conductor, providing an innovative method for electric arc fault detection.
[0063] The conduction characteristics of sound waves in solid materials (such as the conductor of the circuit under test) depend on the inherent properties and boundary conditions of the solid material. In solid materials, sound waves can be conducted by various wave types such as longitudinal waves and transverse waves. For power transmission systems, the most commonly used conductors in equipment and lines including power generation, transmission and distribution are metal conductors (conductors made of metal). The following explanation of the conduction characteristics of sound waves will be based on copper conductors.
[0064] Sound waves can propagate in media such as gases, liquids, and solids, but cannot propagate in a vacuum; therefore, sound waves are a type of mechanically elastic wave. According to classical acoustic theory, the propagation of sound waves in a copper conductor follows these physical principles:
[0065] (1) When sound waves propagate in a medium, the sound speed in solids > the sound speed in liquids > the sound speed in gases, and solids have a faster conduction speed.
[0066] (2) When sound waves propagate in a medium, solid attenuation < liquid attenuation < gas attenuation, and solid conduction loss is small;
[0067] (3) When a sound wave propagates in a medium, the lower the frequency of the sound wave, the smaller the conduction attenuation, and the higher the frequency of the sound wave, the greater the conduction attenuation.
[0068] In typical power transmission systems, the cross-sectional diameter of copper conductors (e.g., less than 26 mm) is much smaller than the length of copper conductors (e.g., greater than 500 m). Therefore, sound wave signals are transmitted through copper conductors, mainly in the form of longitudinal waves. According to the theory of sound wave transmission, copper conductors can be regarded as waveguide structures that transmit sound waves along their length. Therefore, the transmission characteristics of plane waves in longitudinal waves can be studied in detail based on the theory of sound waveguides.
[0069] Sound intensity is a primary parameter for measuring the size and strength of a sound source. As the sound wave travels a greater distance in a copper conductor, the sound intensity gradually decreases. According to acoustic theory, the attenuation of sound intensity in a copper conductor follows the formula: I x =I0e -2αx .
[0070] Where x is the distance from the sound source, Ix Let I0 be the sound intensity at a distance x from the sound source, I0 be the sound intensity at the sound source, and α be the medium attenuation coefficient. The attenuation constant of the sound wave in solid copper is 445 Np / m. The ratio of the attenuation coefficient to the attenuation constant is the square of the sound wave frequency, i.e., α = A·f 2 According to the acoustic law that solid attenuation < liquid attenuation < gas attenuation, the air attenuation coefficient for sound waves is 2.0 × 10⁻⁶. -11 ·f 2 Under the premise of considering the parameter errors between theory and practice, the attenuation coefficient of sound waves in solid copper can be set as: 4.45 × 10⁻⁶. -11 ·f 2 ; Due to 4.45×10 -11 ·f 2 and 2.0×10 -11 ·f 2 The magnitudes are comparable, and theoretical calculations will not significantly exceed the limits of acoustic principles. Furthermore, given the lack of a universally accepted attenuation coefficient for copper conductors, the research proceeds from a challenging starting point. Therefore, this assumption is credible and experimentally verifiable; in the audio frequency band, specifically below 20kHz, the actual attenuation in copper conductors is largely consistent with reality.
[0071] Based on this attenuation coefficient, the theoretical value of the propagation distance of sound waves in a copper wire can be derived as follows:
[0072]
[0073] In copper conductors, when the sound intensity level attenuation at a distance x from the sound source is 60 dB, calculations show that the sound wave propagation distance at a 17.5 kHz frequency can reach 506.87 m. At frequencies below 17.5 kHz, the propagation distance will be greater. Arc fault experiments have verified that both these calculated and experimental data are conservative; the actual sound wave propagation distance will be even greater. In other words, the measured propagation distance of arc energy sound waves in copper conductors is larger than the theoretically calculated data. Therefore, this estimation method is practical and reliable in engineering applications, providing a theoretical basis for the actual detection of sound wave signals transmitted through conductors.
[0074] Detecting sound wave signals transmitted through solids is completely different from detecting sound wave signals transmitted through air. For sound wave signals transmitted through solids, solid-conducting microphones (which are contact microphones, such as bone conduction microphones) are required. Based on the principle of vibration pickup, sound wave signals transmitted through solids can be effectively detected. This detection method, which involves direct contact with the solid medium, also has the ability to resist air noise interference.
[0075] Based on the above two principles (arc energy equals electrical energy plus arc energy, and the sound wave signal transmitted through the solid medium is detected by a solid conductive microphone), the arc fault detection circuit and arc fault detection method of this application were designed.
[0076] The arc fault detection circuit provided in this application uses a solid-state conductive microphone to detect the acoustic signal transmitted through the circuit under test and outputs the corresponding acoustic-electric signal. Based on the analysis of the acoustic-electric signal, the arc energy characteristics and electrical energy characteristics of the circuit under test are obtained. The arc fault result of the circuit under test is determined by combining the arc energy characteristics and electrical energy characteristics. By superimposing the arc energy characteristics on the arc fault detection based on the electrical energy characteristics, the completeness, accuracy, and reliability of arc fault detection are improved. Furthermore, acoustic signals are affected by environmental noise and obstacles during air propagation, leading to attenuation and distortion, making it difficult to accurately detect arc energy characteristics. This application uses a solid-state conductive microphone to detect the acoustic signal transmitted through the circuit under test. This microphone has a fast transmission speed, low transmission loss, and minimal low-frequency loss, greatly reducing the attenuation and distortion of the acoustic signal, improving the quality of the detected acoustic signal, and further enhancing the completeness, accuracy, and reliability of arc fault detection.
[0077] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.
[0078] Figure 2 The schematic diagram of the arc fault detection circuit provided in this application is as follows: Figure 2 As shown, the circuit includes: a solid-state conductive microphone 201, used to detect the acoustic wave signal conducted by the circuit under test and convert the acoustic wave signal into an acoustic-electric signal for output; the solid-state conductive microphone 201 is disposed on the circuit under test and is connected to the processing module 202; an electric power wave detection module 203, used to detect the electrical energy signal of the circuit under test; the electric power wave detection module 203 is connected to the processing module 202; the processing module 202 is used to extract arc energy acoustic wave characteristics based on the acoustic-electric signal, determine electrical energy characteristics based on the electrical energy signal, and determine the arc fault result of the circuit under test based on the arc energy acoustic wave characteristics and the electrical energy characteristics.
[0079] The circuit under test (DUT) is the circuit in the circuit system under test. The solid-state conductive microphone is placed on the DUT and must be connected to the conductor layer of the DUT. It can be understood that the DUT includes a conductor layer and an insulating layer. The conductor layer and the insulating layer are different medium materials. According to acoustic theory, the propagation of sound waves between different media will follow the principles of incident, refraction and reflection. Multiple incident, refraction and reflection of sound waves will inevitably produce a large attenuation and reduce the transmission efficiency. The conductor layer is usually made of homogeneous metal, and the propagation of sound waves in homogeneous materials follows the principle of transmission. Therefore, the conductor layer can serve as an excellent medium for sound wave transmission.
[0080] Specifically, a solid-state conductive microphone detects the acoustic wave signal transmitted by the circuit under test. The solid-state conductive microphone converts the detected acoustic wave signal into an acoustic-electric signal and outputs it to the processing module. The processing module extracts the arc energy acoustic wave characteristics based on the acoustic-electric signal. A power wave module detects the electrical energy signal of the circuit under test and outputs the electrical energy signal to the processing module. The processing module determines the electrical energy characteristics based on the electrical energy signal and determines the arc fault result based on the arc energy acoustic wave characteristics and the electrical energy characteristics.
[0081] like Figure 3 As shown, the processing module 202 also includes an opto-isolation unit 301, a filtering and conversion unit 302, and a processing unit 303. One end of the opto-isolation unit 301 is connected to the output end of the solid-state microphone 201, and the other end of the opto-isolation unit 301 is connected to one end of the filtering and conversion unit 302. The other end of the filtering and conversion unit 302 is connected to the processing unit 303. Specifically, the solid-state microphone 201 outputs an acoustic signal to the opto-isolation unit 301. After opto-isolation processing, the acoustic signal is output to the filtering and conversion unit 302. The filtering and conversion unit 302 performs filtering and analog-to-digital conversion processing to obtain a digital signal, which is then output to the processing unit 303. The processing unit 303 extracts the arc energy acoustic wave characteristics based on the digital signal.
[0082] The arc fault detection circuit provided in this application uses a solid-state conductive microphone to detect the acoustic signal transmitted through the circuit under test and outputs the corresponding acoustic-electric signal. Based on the analysis of the acoustic-electric signal, the arc energy characteristics and electrical energy characteristics of the circuit under test are obtained. The arc fault result of the circuit under test is determined by combining the arc energy characteristics and electrical energy characteristics. By superimposing the arc energy characteristics on the arc fault detection based on the electrical energy characteristics, the accuracy and reliability of arc fault detection are improved. Furthermore, acoustic signals are affected by environmental noise and obstacles during air propagation, leading to attenuation and distortion, making it difficult to accurately detect arc energy characteristics. This application uses a solid-state conductive microphone to detect the acoustic signal transmitted through the circuit under test. This microphone has a fast transmission speed, low transmission loss, and minimal low-frequency loss, greatly reducing the attenuation and distortion of the acoustic signal, improving the quality of the detected acoustic signal, and further enhancing the completeness, accuracy, and reliability of arc fault detection.
[0083] In some embodiments, the circuit under test includes a power supply line between the power supply and the load, and connected to the power supply output terminal.
[0084] In some embodiments, the circuit under test further includes a return line between the power supply and the load, and connected to the power supply return terminal.
[0085] In a circuit system, one end of the power supply line is connected to the power output terminal (positive terminal), or in other words, the power supply line is the phase line, and the return line is connected to the power return terminal (negative terminal), or in other words, the return line is the neutral line.
[0086] It should be noted that the power supply line and the return circuit are two different circuits under test. A first solid-state conductive microphone can be installed on the power supply line to detect the sound wave signal generated by an arc fault in the power supply line; a second solid-state conductive microphone can be installed on the return circuit to detect the sound wave signal generated by an arc fault in the return circuit. In other words, sound wave signals transmitted by different circuits under test are detected by different solid-state conductive microphones.
[0087] It should be noted that when a sound wave signal is propagated in the same solid medium, its transmission characteristics, such as sound velocity, acoustic impedance, and sound attenuation coefficient, are exactly the same. In other words, even if the solid medium is extended by mechanical connection methods (such as by extending the circuit transmission by extending the wire) without changing the transmission medium, the transmission characteristics of the sound wave signal will remain unchanged. However, if the transmission medium changes, causing the sound wave signal to be propagated from one solid medium to another, incident, refraction, and reflection phenomena will occur, thereby changing the transmission characteristics of the sound wave signal and affecting the quality of the detected sound wave signal.
[0088] For example, in a circuit system, the materials of the lines, power supply, and load are all different. When an arc fault occurs on the power supply line, the sound wave signal is conducted through the power supply line. When the sound wave signal continues to be conducted to the back end of the power supply or load, it will change the conduction characteristics. If a solid-state conductive microphone is set on the return line to detect the sound wave signal whose source is the power supply line, the sound wave signal detected by the solid-state conductive microphone may be of poor quality or even undetectable, thus affecting the accuracy of the arc fault detection results.
[0089] To avoid changes in the conduction characteristics of acoustic signals due to transmission in different solid media, which could affect the arc fault detection results, this application uses different solid-state conductive microphones to detect acoustic signals transmitted by different circuits under test; specifically, such as... Figure 4 As shown, the circuit under test includes a power supply line A and a return line B. Solid-state conductive microphone v1 is used to detect the sound wave signal transmitted by the power supply line A, and solid-state conductive microphone v2 is used to detect the sound wave signal transmitted by the return line B, so that the sound wave signals generated by the arc fault occurring on the power supply line and the return line can be effectively detected.
[0090] In some embodiments, a solid-state conductive microphone may include at least two sub-microphones, i.e., a solid-state conductive microphone array group is formed by at least two sub-microphones. In use, at least two sub-microphones are placed on the line under test, and each of the at least two sub-microphones detects the sub-sound wave signal conducted by the line under test. The sound wave signal detected by the solid-state conductive microphone is obtained by superimposing the at least two sub-sound wave signals. The superposition operation of the at least two sub-sound wave signals can be implemented by mathematical calculation methods such as calculating the mean, variance, weight, and vector.
[0091] In the above embodiments, the circuit under test includes a power supply line between the power source and the load. A first solid-state conductive microphone installed on the power supply line is used to detect the acoustic signal generated by an arc fault on the power supply line. The circuit under test also includes a return signal. A second solid-state conductive microphone installed on the return line is used to detect the acoustic signal generated by an arc fault on the return line. This avoids detecting acoustic signals transmitted across media, ensuring that the arc energy acoustic signals generated by arc faults on both the power supply line and the return line can be effectively detected. This improves the quality of the detected arc energy acoustic signals, thereby improving the accuracy and reliability of the arc fault detection results.
[0092] In some embodiments, the solid-state microphone is connected to a connection terminal of the circuit under test, the connection terminal being a terminal for connecting a load; or, the solid-state microphone is disposed in contact with the conductor surface of the circuit under test.
[0093] In one implementation, the circuit under test is a line between a power source and a load. Therefore, the circuit under test includes a connection terminal for connecting the load. A solid-state conductive microphone is connected to the connection terminal of the circuit under test. The connection terminal is made of the same material as the conductor of the circuit under test. When the sound wave signal conducted by the circuit under test reaches the connection terminal, the conduction characteristics will not change. Thus, the solid-state conductive microphone connected to the connection terminal can detect the sound wave signal generated by an arc fault on the circuit under test.
[0094] In another implementation, the solid-state microphone is placed in contact with the conductor surface of the circuit under test. This can be achieved by attaching the solid-state microphone to the conductor surface of the circuit under test and wrapping the solid-state microphone and the conductor together through the insulation layer of the circuit under test, so that the solid-state microphone is in close contact with the conductor surface, ensuring that the solid-state microphone can detect the sound wave signal generated by the arc fault on the circuit under test.
[0095] In the above embodiments, the solid-state conductive microphone is connected to the connection terminal of the circuit under test, or the solid-state conductive microphone is disposed in contact with the conductor surface of the circuit under test, so that the solid-state conductive microphone can effectively detect the sound wave signal transmitted through the circuit under test, thereby improving the quality of the detected sound wave signal and thus improving the accuracy and reliability of arc fault detection.
[0096] The aforementioned arc fault detection circuit uses a solid-state conductive microphone to detect the acoustic signal transmitted through the circuit under test and outputs the corresponding acoustic-electric signal. Based on the analysis of the acoustic-electric signal, the arc energy characteristics and electrical energy characteristics of the circuit under test are obtained. The arc fault result of the circuit under test is determined by combining the arc energy characteristics and electrical energy characteristics. By superimposing the arc energy characteristics on the arc fault detection based on the electrical energy characteristics, the accuracy and reliability of arc fault detection are improved. Furthermore, acoustic signals are affected by environmental noise and obstacles during air propagation, leading to attenuation and distortion, making it difficult to accurately detect arc energy characteristics. This application uses a solid-state conductive microphone to detect the acoustic signal transmitted through the circuit under test. This microphone has a fast transmission speed, low transmission loss, and minimal low-frequency loss, greatly reducing the attenuation and distortion of the acoustic signal, improving the quality of the detected acoustic signal, and further enhancing the completeness, accuracy, and reliability of arc fault detection.
[0097] This application also provides an arc fault detection method, applied to an arc fault detection circuit, such as... Figure 5 As shown, it includes:
[0098] S501 detects the sound wave signal transmitted by the circuit under test through a solid-state conductive microphone installed on the circuit under test, and converts the sound wave signal into an acoustic-electric signal for output.
[0099] The circuit under test (DUT) is a circuit in the circuit system under test. The DUT includes the power supply line between the power source and the load and connected to the power source output terminal, and may also include the return line between the power source and the load and connected to the power source return terminal. A first solid-state conductive microphone can be installed on the power supply line to detect the sound wave signal generated by an arc fault on the power supply line. A second solid-state conductive microphone can be installed on the return line to detect the sound wave signal generated by an arc fault on the return line.
[0100] The following explanation uses the detection of acoustic wave signals conducted by the power supply line by the first solid-state conductive microphone as an example. The acoustic wave signals conducted by the power supply line are detected in real time by the first solid-state conductive microphone installed on the power supply line, and the acoustic wave signals are converted into acoustic-electric signals for output.
[0101] S502 detects the electrical signal of the circuit under test.
[0102] This embodiment can detect the electrical signal of the circuit under test through the power wave detection module in the arc fault detection circuit.
[0103] S503 extracts arc energy acoustic wave characteristics based on acoustic and electrical signals, determines electrical energy characteristics based on electrical signals, and determines the arc fault result of the circuit under test based on the arc energy acoustic wave characteristics and electrical energy characteristics.
[0104] This embodiment can be implemented through a processing module in an arc fault detection circuit; the processing module extracts arc energy acoustic wave characteristics based on acoustic and electrical signals, and determines electrical energy characteristics based on electrical energy signals.
[0105] Specifically, the processing module performs photoelectric isolation, filtering, and analog-to-digital conversion on the acoustic and electrical signals to obtain digital signals, and extracts arc energy acoustic wave characteristics based on the digital signals; the processing module determines the electrical energy characteristics based on the electrical energy signals.
[0106] The processing module acquires the preset arc energy acoustic wave characteristics and preset electrical energy characteristics of the circuit under test, and determines the arc fault result based on the arc energy acoustic wave characteristics, preset arc energy acoustic wave characteristics, electrical energy characteristics and preset electrical energy characteristics.
[0107] The aforementioned arc fault detection method uses a solid-state conductive microphone to detect the acoustic signal transmitted through the circuit under test and outputs the corresponding acoustic-electric signal. Based on the analysis of the acoustic-electric signal, the arc energy characteristics and electrical energy characteristics of the circuit under test are obtained. The arc fault result of the circuit under test is determined by combining the arc energy characteristics and electrical energy characteristics. By superimposing the arc energy characteristics on the arc fault detection based on the electrical energy characteristics, the accuracy and reliability of arc fault detection are improved. Furthermore, acoustic signals are affected by environmental noise and obstacles during air propagation, leading to attenuation and distortion, making it difficult to accurately detect arc energy characteristics. This application uses a solid-state conductive microphone to detect the acoustic signal transmitted through the circuit under test. This method features fast transmission speed, low transmission loss, and minimal low-frequency loss, greatly reducing the attenuation and distortion of the acoustic signal, improving the quality of the detected acoustic signal, and further enhancing the completeness, accuracy, and reliability of arc fault detection.
[0108] In some embodiments, determining the arc fault result of the circuit under test based on the arc energy acoustic wave characteristics and electrical energy characteristics includes: comparing and analyzing the arc energy acoustic wave characteristics and preset arc energy acoustic wave characteristics to obtain the arc energy detection result; comparing and analyzing the electrical energy characteristics and preset electrical energy characteristics to obtain the electrical energy detection result; and determining the arc fault result of the circuit under test based on the arc energy detection result and the electrical energy detection result.
[0109] Specifically, the arc energy acoustic wave characteristics and the preset arc energy acoustic wave characteristics are compared in multiple aspects, including spectrum characteristics, phase characteristics, amplitude characteristics, and power characteristics, to determine the arc energy detection result, which is normal or abnormal; the electrical energy characteristics and the preset electrical energy characteristics are compared in multiple aspects, including spectrum characteristics, phase characteristics, amplitude characteristics, and power characteristics, to determine the electrical energy detection result, which is normal or abnormal.
[0110] In practical applications, for the arc energy acoustic wave characteristics and the preset arc energy acoustic wave characteristics, the first feature similarity of the two in terms of spectrum characteristics, phase characteristics, amplitude characteristics and power characteristics is determined. Based on the first feature similarity, a first target similarity is determined. If the first target similarity is greater than the first similarity threshold, the arc energy detection result is determined to be abnormal. If the first target similarity is not greater than the first similarity threshold, the arc energy detection result is determined to be normal. The first similarity threshold can be determined according to the actual situation. The embodiments of this application do not limit the first similarity threshold.
[0111] For the electrical energy characteristics and the preset electrical energy characteristics, the second feature similarity of the two in terms of spectrum characteristics, phase characteristics, amplitude characteristics and power characteristics is determined. Based on the second feature similarity, a second target similarity is determined. If the second target similarity is greater than the second similarity threshold, the electrical energy detection result is determined to be abnormal. If the second target similarity is not greater than the second similarity threshold, the electrical energy detection result is determined to be normal. The second similarity threshold can be determined according to the actual situation. The embodiments of this application do not limit the second similarity threshold.
[0112] If both the arc energy detection result and the electrical energy detection result are abnormal (the similarity of the first target is greater than the first similarity threshold, and the similarity of the second target is greater than the second similarity threshold), or if either the arc energy detection result or the electrical energy detection result is abnormal (the similarity of the first target is greater than the first similarity threshold, or the similarity of the second target is greater than the second similarity threshold), then the arc fault result is determined to be abnormal. If both the arc energy detection result and the electrical energy detection result are normal (the similarity of the first target is not greater than the first similarity threshold, and the similarity of the second target is not greater than the second similarity threshold), then the arc fault result is determined to be normal.
[0113] An arc fault result of "abnormal" indicates that an arc fault has occurred on the circuit under test, while an arc fault result of "normal" indicates that no arc fault has occurred on the circuit under test.
[0114] The above-described schemes for determining the arc energy detection results and electrical energy detection results, and for determining the arc fault results based on the arc energy detection results and electrical energy detection results, are only examples. In practical applications, after obtaining the arc energy acoustic wave characteristics and electrical energy characteristics, other methods can also be used to determine the arc fault results.
[0115] In the above embodiments, the arc fault result of the circuit under test is determined based on the arc energy acoustic wave characteristics, preset arc energy acoustic wave characteristics, electrical energy characteristics, and preset electrical energy characteristics. That is, the arc energy acoustic wave characteristics are superimposed on the detected electrical energy characteristics, and the arc fault result of the circuit under test is detected by combining the two, thereby improving the completeness, accuracy and reliability of the arc fault result.
[0116] In one application scenario, an arc fault occurs between the arc fault detection circuit and the load; for example... Figure 6As shown, between the arc fault detection circuit and the load, grounding arc faults, series arc faults, and parallel arc faults may occur. When an arc fault occurs on the circuit under test, there will inevitably be a breakdown of the insulating medium and electrode vibration between the two electrodes that generate the arc. According to the theory of physics that vibration generates mechanical waves, at the same time as the breakdown of the insulating medium and electrode vibration occur, there will inevitably be propagation and conduction of sound wave signals between the two electrodes. Propagation occurs in the air, while conduction occurs in the circuit under test. The sound wave signal and electrical energy signal generated when an arc fault occurs have... It has specific characteristics; accordingly, by detecting the sound wave signal transmitted by the circuit under test through a solid-state conductive microphone, and using the MCU embedded technology that combines hardware and software, it can sense, receive, process, calculate, compare and judge the specific sound wave spectrum characteristics, phase characteristics, amplitude characteristics and power spectrum characteristics generated by the arc fault in the energized conductor. Based on the superimposed detection of the arc fault electrical energy signal, the detection of the arc fault is completed. When the arc fault result is abnormal, the action unit can be controlled to cut off the power supply through the circuit breaker contact to realize the circuit breaker protection function.
[0117] In another application scenario, the arc fault occurs between the arc fault detection circuit and the power supply; for example... Figure 7 As shown, between the arc fault detection circuit and the power supply, grounding arc faults, series arc faults, and parallel arc faults may occur. A solid-state conductive microphone detects the acoustic signal transmitted through the circuit under test. Using a hardware-software integrated MCU embedded technology, the specific acoustic spectrum characteristics, phase characteristics, amplitude characteristics, and power spectrum characteristics generated by the arc fault in the energized conductor can be sensed, received, processed, calculated, compared, and judged. Based on the superimposed detection of the arc fault electrical signal, the arc fault detection is completed. When the arc fault result is abnormal, the communication unit can remotely communicate to control the action unit to cut off the power supply through the circuit breaker contacts, thereby achieving the circuit breaker protection function.
[0118] In some embodiments, a solid-state conductive microphone can be selected according to the actual application scenario. For example, a MEMS sensor, a piezoelectric ceramic sensor, or a laser sensor can be selected. This can achieve reliable measurement of the acoustic wave signal conducted in the solid while reducing the false judgment rate, improving reliability, and taking into account economy and practicality. This application does not make specific limitations on the type of solid-state conductive microphone to be selected. It should be understood that any solid-state conductive microphone is within the scope of this application.
[0119] Figure 8 This is a schematic diagram of the arc fault detection device provided in this application, as shown below. Figure 8 As shown, the arc fault detection device 80 provided in this embodiment includes:
[0120] The acoustic wave detection module 801 is used to detect the acoustic wave signal transmitted by the circuit under test through a solid conductive microphone installed on the circuit under test, and convert the acoustic wave signal into an acoustic-electric signal for output.
[0121] The power wave detection module 802 is used to detect the power signal of the circuit under test.
[0122] The result determination module 803 is also used to extract arc energy acoustic wave characteristics based on acoustic and electrical signals, determine electrical energy characteristics based on electrical energy signals, and determine the arc fault result of the circuit under test based on the arc energy acoustic wave characteristics and electrical energy characteristics.
[0123] In one possible implementation, the result determination module is further used to compare and analyze the arc energy acoustic wave characteristics and the preset arc energy acoustic wave characteristics to obtain the arc energy detection result; compare and analyze the electrical energy characteristics and the preset electrical energy characteristics to obtain the electrical energy detection result; and determine the arc fault result of the circuit under test based on the arc energy detection result and the electrical energy detection result.
[0124] The arc fault detection device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.
[0125] Figure 9 This is a schematic diagram of the arc fault detection equipment provided in this application. Figure 9 As shown, the electronic device 90 provided in this embodiment includes at least one processor 901 and a memory 902. Optionally, the device 90 further includes a communication component 903. The processor 901, memory 902, and communication component 903 are connected via a bus 904.
[0126] In a specific implementation, at least one processor 901 executes computer execution instructions stored in memory 902, causing at least one processor 901 to perform the above-described method.
[0127] The specific implementation process of processor 901 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.
[0128] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.
[0129] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.
[0130] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.
[0131] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.
[0132] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.
[0133] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.
[0134] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.
[0135] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.
[0136] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0137] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
[0138] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0139] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.
[0140] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.
Claims
1. An arc fault detection circuit, characterized in that, include: A solid-state conductive microphone is used to detect acoustic wave signals conducted by the circuit under test and convert the acoustic wave signals into acoustic-electric signals for output. The solid-state conductive microphone is installed on the circuit under test and is connected to the processing module. The power wave detection module is used to detect the power signal of the circuit under test; The power wave detection module is connected to the processing module; The processing module is used to extract arc energy acoustic wave features based on the acoustic and electrical signals, determine electrical energy features based on the electrical energy signals, and determine the arc fault result of the circuit under test based on the arc energy acoustic wave features and the electrical energy features.
2. The circuit according to claim 1, characterized in that, The circuit under test includes the power supply line between the power source and the load, and connected to the power source output terminal.
3. The circuit according to claim 2, characterized in that, The circuit under test also includes a return line between the power supply and the load, and connected to the power supply return terminal.
4. The circuit according to any one of claims 1-3, characterized in that, The solid-state conductive microphone is connected to the connection terminal of the circuit under test, and the connection terminal is the terminal for connecting the load; or, The solid-state conductive microphone is disposed in contact with the conductor surface of the circuit under test.
5. A method for detecting electric arc faults, characterized in that, include: A solid-state conductive microphone is installed on the circuit under test to detect the sound wave signal transmitted by the circuit under test, and the sound wave signal is converted into an acoustic-electric signal for output. Detect the electrical signal of the circuit under test; Arc energy acoustic wave characteristics are extracted based on the acoustic and electrical signals, electrical energy characteristics are determined based on the electrical energy signals, and the arc fault result of the circuit under test is determined based on the arc energy acoustic wave characteristics and the electrical energy characteristics.
6. The method according to claim 5, characterized in that, The determination of the arc fault result of the circuit under test based on the arc energy acoustic wave characteristics and the electrical energy characteristics includes: The arc energy acoustic wave characteristics and the preset arc energy acoustic wave characteristics are compared and analyzed to obtain the arc energy detection results; The electrical energy characteristics are compared and analyzed with the preset electrical energy characteristics to obtain the electrical energy detection results; Based on the arc energy detection results and the electrical energy detection results, the arc fault result of the circuit under test is determined.
7. An arc fault detection device, characterized in that, include: The acoustic wave detection module is used to detect the acoustic wave signal transmitted by the circuit under test through a solid conductive microphone installed on the circuit under test, and to convert the acoustic wave signal into an acoustic-electric signal for output. The power wave detection module is used to detect the power signal of the circuit under test; The result determination module is also used to extract arc energy acoustic wave features based on the acoustic and electrical signals, determine electrical energy features based on the electrical energy signals, and determine the arc fault result of the circuit under test based on the arc energy acoustic wave features and the electrical energy features.
8. An arc fault detection device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in claim 5 or 6.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in claim 5 or 6.
10. A computer program product comprising a computer program that, when executed by a processor, implements the method of claim 5 or 6.