An intelligent fault detection method and system for UV pulse power supply
By monitoring the output pulse waveform data of UV pulse power supply in real time and troubleshooting, identifying the fault risk and evaluating the impact of faults, the problem of inaccurate fault traceability in the existing technology is solved, and accurate detection and efficient evaluation of UV pulse power supply failures is achieved.
Patent Information
- Application Number
- CN202411472419.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-22
- Publication Date
- 2025-01-03
- Estimated Expiration
- 2044-10-22
AI Technical Summary
The prior art cannot accurately trace the fault of UV pulse power to the specific component units, resulting in increased maintenance costs and time, and cannot fully consider the complex interaction and fault propagation mechanisms between the components, and lack accuracy and reliability.
Provide an intelligent fault detection method and system for UV pulse power supply. By monitoring the output pulse waveform data in real time, identifying fault risks, troubleshooting each component unit in turn, analyzing the fault risk coefficient, and considering the faults between each component unit Impact, generate internal fault detection report.
It realizes accurate identification and efficient detection of UV pulse power failures, improves the flexibility and convenience of fault detection, and ensures the authenticity, accuracy and reliability of fault probability assessment.
Smart Images
Figure CN119001522B_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of UV pulse power supply fault detection, and in particular relates to an intelligent fault detection method and system for a UV pulse power supply. Background Art
[0002] As an important type of power supply in the power system, UV pulse power supply is widely used in various industrial scenarios, such as semiconductor manufacturing, material processing, medical equipment, etc. However, during the operation of UV pulse power supply, various faults often occur due to various factors, such as environmental factors, equipment aging, improper operation, etc., which affect the normal operation and production efficiency of the equipment. Therefore, it is particularly important to develop an efficient and accurate intelligent fault detection method for UV pulse power supply.
[0003] In the prior art, there are related solutions that can be applied to UV pulse power supply fault detection, such as the pulse response-based switching power supply fault detection method with Chinese patent publication number CN112710963A, which detects the capacitance change of the output capacitor by comparing the pulse response signal of the switching power supply under different conditions, thereby realizing the detection of the switching power supply fault. It has the advantages of non-invasiveness, real-time and accuracy, and is suitable for application scenarios requiring high reliability and stability. However, the prior art still has limitations, specifically: the prior art is often limited to identifying the overall failure risk of the UV pulse power supply, and cannot be accurately traced back to specific components, such as the main circuit, control circuit, output circuit and heat dissipation device. The ambiguity of the fault detection method may lead to blindness when repairing and replacing parts, increasing maintenance costs and time.
[0004] Although there are a few existing technologies that attempt to assess the possibility of failure by checking each component unit one by one, they usually rely on the intervention of external equipment or require physical invasive testing of the equipment, which may not only increase the risk of equipment damage, but also fail to fully consider the complex interactions and fault propagation mechanisms between the components in the actual analysis process, resulting in the traceability results lacking the necessary accuracy and reliability. Summary of the invention
[0005] In view of this, in order to solve the problems raised in the above background technology, an intelligent fault detection method and system for UV pulse power supply is proposed.
[0006] The technical solution adopted by the present invention to solve its technical problems is: in the first aspect, the present invention provides an intelligent fault detection method for a UV pulse power supply, including: S1. recording a target UV pulse power supply as a target device, monitoring the pulse waveform data of a specified load output by the target device in real time, and identifying whether the target device has any fault risk performance.
[0007] S2. If the target device is identified to have a risk of failure, its internal fault detection mechanism is triggered.
[0008] S3. Perform troubleshooting on each component unit of the target device in turn, each component unit including the control circuit, main circuit, output circuit and heat dissipation device, and analyze the failure risk coefficient of the control circuit, main circuit, output circuit and heat dissipation device of the target device.
[0009] S4. Consider the impact of failures between the various components and evaluate the failure probability of the target device's control circuit, main circuit, output circuit, and heat sink.
[0010] S5. Generate and feedback the internal fault inspection report based on the failure probability of each component unit of the target device.
[0011] In a second aspect, the present invention provides an intelligent fault detection system for a UV pulse power supply, comprising: a fault risk manifestation identification module, a fault internal inspection mechanism triggering module, a fault risk coefficient analysis module, a fault probability assessment module, a fault internal inspection report feedback module and a cloud database.
[0012] The fault risk manifestation identification module is connected to the fault internal inspection mechanism triggering module, the fault internal inspection mechanism triggering module is connected to the fault risk coefficient analysis module, the fault risk coefficient analysis module is connected to the fault probability assessment module, the fault probability assessment module is connected to the fault internal inspection report feedback module, and the cloud database is respectively connected to the fault risk manifestation identification module and the fault probability assessment module.
[0013] The fault risk manifestation identification module is used to record the target UV pulse power supply as the target device, monitor the pulse waveform data of the target device outputting the specified load in real time, and identify whether the target device has a fault risk manifestation.
[0014] The fault internal inspection mechanism triggering module is used to trigger the fault internal inspection mechanism if the target device is identified to have fault risk manifestations.
[0015] The fault risk coefficient analysis module is used to troubleshoot each component unit of the target device in turn, each component unit includes a control circuit, a main circuit, an output circuit and a heat dissipation device, and analyze the fault risk coefficient of the control circuit, main circuit, output circuit and heat dissipation device of the target device.
[0016] The failure probability assessment module is used to consider the impact of failures between various components and assess the failure probability of the target device's control circuit, main circuit, output circuit, and heat dissipation device.
[0017] The fault internal inspection report feedback module is used to generate and feedback the fault internal inspection report according to the fault probability of each component unit of the target device.
[0018] The cloud database is used to store the fault risk factor warning thresholds corresponding to the UV pulse power supply control circuit, main circuit, output circuit and heat dissipation device, store the reasonable parameter range content of the power supply pulse required by the specified load technical specifications, and store the summary table of the fault impact ratio of each component unit of the UV pulse power supply.
[0019] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention uses the rationality index and stability index of the load pulse waveform connected to the target device output as the starting point to achieve accurate identification and efficient detection of the risk manifestations of UV pulse power supply failures, thereby improving the flexibility and convenience of fault detection.
[0020] (2) The present invention generates various test input signals through the built-in signal generator of the target device control circuit, and non-invasively and autonomously tests the all-round working performance of the target device control circuit, main circuit, output circuit and heat dissipation device, accurately understands the failure risk factor of each component unit of the target device, and realizes comprehensive and accurate fault detection of the UV pulse power supply.
[0021] (3) The present invention considers the impact of failures between various components and makes corresponding corrections based on the potential failure probabilities of the target device control circuit, main circuit, output circuit and heat dissipation device, thereby improving the authenticity, accuracy and reliability of the failure probability assessment. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.
[0023] Figure 1 The figure is a flow chart of the method of the present invention.
[0024] Figure 2 It is a schematic diagram of module connection of the present invention.
[0025] Figure 3 For the present invention Figure 1 Schematic diagram of step S3 in . DETAILED DESCRIPTION
[0026] The following will be combined with the 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.
[0027] Reference Figure 1As shown, the first aspect of the present invention provides an intelligent fault detection method for a UV pulse power supply, comprising: S1. recording a target UV pulse power supply as a target device, monitoring the pulse waveform data of a specified load output by the target device in real time, and identifying whether the target device has a fault risk.
[0028] Specifically, the identification of whether the target device has a fault risk performance includes: analyzing the rationality index of the pulse waveform of the current target device output connected to the load based on the pulse waveform data of the specified load output by the current target device, including the proportion of harmonic components of the overall pulse waveform, the pulse voltage peak value, duty cycle, rise time, fall time and pulse period of each pulse and stability indicators , add the two products with their corresponding preset weights to obtain the comprehensive evaluation index of the load pulse waveform of the current target device output connection. If it is less than or equal to the preset comprehensive evaluation index warning threshold, the target device is identified to have a fault risk performance, otherwise it is identified to not exist.
[0029] Specifically, the The analysis process includes: supplying reasonable parameter ranges of power pulses according to the technical specifications of the specified load stored in the WEB cloud, including the reasonable ranges corresponding to the pulse voltage peak, duty cycle, rise time, and fall time, extracting the pulse voltage peak, duty cycle, rise time, and fall time of each pulse of the specified load output by the current target device, comparing each parameter with its corresponding reasonable range, analyzing the overall abnormal deviation of each pulse of the specified load output by the current target device, and taking the inverse of the calculated mean as the rationality indicator of the pulse waveform of the load connected to the current target device output.
[0030] It should be noted that the analysis process of the overall abnormal deviation of each pulse of the specified load output by the current target device is as follows: compare the pulse voltage peak of a pulse of the specified load output by the current target device with its corresponding reasonable interval. If it is within the reasonable interval, set the pulse voltage peak abnormal deviation of the pulse to 0. Otherwise, if it is greater than the upper limit of the reasonable interval, calculate the difference between the pulse voltage peak of the pulse and the upper limit of the reasonable interval, and further use the ratio of the upper limit of the reasonable interval as the pulse voltage peak abnormal deviation of the pulse. If it is less than the lower limit of the reasonable interval, calculate the difference between the lower limit of the reasonable interval and the pulse voltage peak of the pulse, and further use the ratio of the lower limit of the reasonable interval as the pulse voltage peak abnormal deviation of the pulse. Similarly, obtain the pulse voltage peak abnormal deviation of each pulse of the specified load output by the current target device, and obtain the corresponding abnormal deviation of the duty cycle, rise time, and fall time of each pulse of the specified load output by the current target device according to the above calculation method. Accumulate the abnormal deviation of each parameter to obtain the overall abnormal deviation of each pulse of the specified load output by the current target device.
[0031] Specifically, the The analysis process includes: extracting the pulse voltage peak value and pulse period of each pulse, obtaining the amplitude variance and period variance of the pulse waveform of the current target device output connected load through the variance calculation formula, accumulating the harmonic component proportion of the overall pulse waveform, and using the inverse of the accumulated value as the stability indicator of the pulse waveform of the current target device output connected load.
[0032] The embodiment of the present invention uses the rationality index and stability index of the load pulse waveform output by the target device as the starting point to achieve accurate identification and efficient detection of the risk manifestation of UV pulse power supply failure, thereby improving the flexibility and convenience of fault detection.
[0033] S2. If the target device is identified to have a risk of failure, its internal fault detection mechanism is triggered.
[0034] Reference Figure 3 As shown, S3. troubleshoot each component unit of the target device in turn, each component unit includes a control circuit, a main circuit, an output circuit and a heat dissipation device, and analyze the failure risk coefficient of the control circuit, main circuit, output circuit and heat dissipation device of the target device.
[0035] Specifically, the analysis of the failure risk coefficient of the target device control circuit includes: activating the built-in signal generator and signal capturer of the target device control circuit, the signal generator generates various test input signals and the signal capturer captures the corresponding execution control signals, and during the control signal issuance process, the built-in feedback loop continuously monitors the voltage value of each unit time point within a preset time length of the corresponding feedback signal.
[0036] Analyze the expected deviation between various test input signals and their corresponding execution control signals, and obtain the control signal execution correctness of the target device control circuit based on the preset test weights of various test input signals .
[0037] It should be noted that various test input signals are automated test scripts extracted and set by professionals, which include the expected frequency indicators of various test input signals corresponding to the execution control signals. , expected duty cycle indicator and expected amplitude index , The numbers of various test input signals. , collect the actual frequency indicators of various test input signals corresponding to the execution control signals , Actual duty cycle indicator and actual amplitude index , according to the formula Get the expected deviation between various test input signals and their corresponding execution control signals, based on the preset test weights of various test input signals , further by the formula Get the control signal execution accuracy of the target device control circuit, where It is the preset execution control signal expected deviation allowable threshold, which is obtained by accumulating the execution control signal frequency allowable error rate threshold, duty cycle allowable error rate threshold and amplitude allowable error rate threshold set in the automated test script.
[0038] Exemplarily, the automated test script setting requires that the frequency error of the execution control signal does not exceed 0.01, the duty cycle error does not exceed 0.02, and the amplitude error does not exceed 0.05.
[0039] Analyze the voltage standard deviation of the feedback signal corresponding to the control signal sending process of various test input signals , analyze the stability of control signal delivery of the target device control circuit .
[0040] By formula Get the control signal sending stability of the target device control circuit, where It is the preset voltage standard deviation permissible threshold of the feedback signal.
[0041] Activate the logic analyzer to distribute the probes of each key node of the target device control circuit, identify the timing diagrams of the corresponding execution control signals and corresponding feedback signals within the preset time of various test input signals, record them as the timing diagrams of each test signal, check the logical sequence status and signal conflict status of each test signal timing diagram, so as to analyze the normality of the logical function status of the target device control circuit .
[0042] It should be noted that the above-mentioned test signal timing diagrams correspond one-to-one to various test input signals, and the logical sequence status check process of each test signal timing diagram includes: collecting various test input signals and their corresponding execution control signals and their waveform diagrams within a preset time length for feedback signals, respectively extracting the rising edge time and falling edge time of various test input signals and their corresponding execution control signals and their feedback signals, and taking the rising edge time and falling edge time of the test input signal prior to the rising edge time and falling edge time of the execution control signal, and the rising edge time and falling edge time of the execution control signal prior to the rising edge time and falling edge time of the feedback signal as the standard logical order. If a test signal timing diagram does not conform to the standard logical order, the logical sequence status indicator of the test signal timing diagram is output as 0, otherwise it is output as 1, thereby obtaining the logical sequence status indicator of each test signal timing diagram to realize the logical sequence status check.
[0043] The signal conflict status check process of each test signal timing diagram includes: observing various test input signals and their corresponding execution control signals and their waveform diagrams within a preset time length for feedback signals, introducing the WEB cloud high-level threshold straight line and the low-level threshold straight line into the waveform diagram, and searching whether there are two or more signals at a high level or a low level at each unit time point within the preset time length. If the above situation exists at any unit time point, the signal conflict status of each test signal timing diagram is output as 1, otherwise it is output as 0, thereby obtaining the signal conflict status indicator of each test signal timing diagram to realize the signal conflict status check.
[0044] If the signal conflict status index of a test signal timing diagram is 0 and the logic sequence status index is 1, then the normal coefficient of the logic function state of the test signal timing diagram is set to On the contrary, the normal coefficient of the logic function state of the test signal timing diagram is set to , thus obtaining the normal coefficient of the logic function state of each test signal timing diagram , and , according to the formula Get the normality of the logic function status of the target device control circuit.
[0045] By formula Get the failure risk factor of the target device control circuit, is a preset constant.
[0046] Specifically, the analysis of the failure risk coefficient of the main circuit of the target device includes: recording the execution control signals corresponding to various test input signals as various test control signals, detecting the working conditions of the built-in rectifier, inverter, transformer and filter after the main circuit receives the various test control signals, analyzing the working abnormality indicators of the built-in rectifier, inverter, transformer and filter in the main circuit of the target device, and accumulating them to obtain the overall working function abnormality coefficient of the main circuit of the target device.
[0047] It should be noted that the analysis process of the working abnormality index of the built-in rectifier, inverter, transformer and filter in the main circuit of the above-mentioned target device is as follows: after the main circuit of the target device receives various test control signals, the voltage and current of the input AC power and the voltage and current of the output DC power of the built-in rectifier are detected, and the voltage and current are multiplied to obtain the input power and output power of the built-in rectifier of the target device after the main circuit receives various test control signals, and the ratio of the input power to the output power is used as the working efficiency of the rectifier to obtain the working efficiency of the built-in rectifier of the target device after the main circuit receives various test control signals. If the rectifier working efficiency is greater than or equal to the preset qualified efficiency threshold of the UV pulse power supply rectifier technical specification, the rectifier working abnormality index is set to 0, otherwise the absolute deviation ratio of the rectifier working efficiency to the preset qualified efficiency threshold of the UV pulse power supply rectifier technical specification is used as the working abnormality index, thereby obtaining the working abnormality index of the built-in rectifier of the target device after the main circuit receives various test control signals, and the working abnormality index of the built-in rectifier of the target device main circuit is obtained after the mean calculation.
[0048] Detect the frequency, amplitude and duty cycle of the built-in inverter of the target device after the main circuit receives various test control signals, and compare them with the frequency, amplitude and duty cycle preset in the inverter high-frequency DC design standard, and calculate the frequency deviation ratio of the built-in inverter of the target device after the main circuit receives various test control signals. , Amplitude Deviation Ratio and duty cycle deviation ratio The calculation method is mainly to make a difference between the absolute value of each parameter and its corresponding high-frequency DC design standard preset value, and use the absolute difference as the numerator and the corresponding high-frequency DC design standard preset value as the denominator for ratio analysis. The formula is Obtain the operating abnormality index of the built-in inverter of the main circuit of the target device, Enter the number of signal types for the test.
[0049] After the target device's main circuit receives various test control signals, the voltage values of the primary and secondary sides of its built-in transformer are detected, and the ratio of the voltage values of the secondary side to the primary side is used as the operating transformation ratio, so as to obtain the operating transformation ratio of the built-in transformer of the target device's main circuit after receiving various test control signals, and perform absolute difference calculation with the corresponding DC design standard preset transformation ratio, and use the ratio of the calculated absolute difference and the DC design standard preset transformation ratio as the operating transformation ratio deviation ratio, so as to obtain the operating transformation ratio deviation ratio of the built-in transformer of the target device's main circuit after receiving various test control signals, and obtain the working abnormality index of the built-in transformer of the target device's main circuit after average calculation.
[0050] The harmonic removal intensity of the built-in filter of the target device before and after the main circuit receives various test control signals is detected. If it is greater than or equal to the preset standard harmonic removal intensity, the filter filtering effect index is set to 1, otherwise it is set to 0, so as to obtain the filtering effect index of the built-in filter of the target device after the main circuit receives various test control signals and the corresponding DC pulse waveform. The calculated mean is inverted to obtain the working abnormality index of the built-in transformer of the main circuit of the target device.
[0051] It is particularly noted that, in the inversion process of the present invention, a preset constant needs to be added to the denominator to prevent the denominator from being zero.
[0052] It should also be noted that if the input source of the UV pulse power supply device is AC power, the working order of its main circuit is rectifier-inverter-transformer-filter. The main function of the rectifier is to convert AC power into DC power, and the main function of the inverter is to convert DC power into high-frequency pulse DC power. If the input source is DC power, the working order of its main circuit is inverter-transformer-filter. Therefore, when the input source is DC power, the working condition analysis of the main circuit rectifier can be abandoned. The various test input signals of the present invention mainly focus on AC signals, and therefore include a rectifier working condition detection step.
[0053] The maximum temperature value, maximum temperature rise value per unit time and maximum vibration amplitude during the overall working period of the main circuit of the target equipment receiving various test control signals are monitored, and the ratio analysis is performed with the reasonable working temperature threshold, reasonable temperature rise threshold per unit time and reasonable vibration amplitude threshold preset by the main circuit of the UV pulse power supply, and the ratio analysis results are recorded as , according to the formula Obtain the overall operating status abnormality coefficient of the main circuit of the target device.
[0054] The overall working state abnormality coefficient and the overall working function abnormality coefficient are accumulated to obtain the fault risk coefficient of the main circuit of the target device.
[0055] Specifically, the analysis of the failure risk coefficient of the output circuit of the target device includes: outputting pulse waveforms corresponding to various test input signals and executing control signals through the main circuit of the target device, which are recorded as various test pulse waveforms, and transmitting various test pulse waveforms to the specified load through the output circuit of the target device, monitoring the reflection coefficient and insertion loss of the built-in matching network of the output circuit during the transmission of various test pulse waveforms, and performing ratio analysis with the preset reflection coefficient allowable threshold and insertion loss allowable threshold of the built-in matching network of the UV pulse power supply output circuit, respectively, and accumulating the ratio analysis results to obtain the evaluation index of the built-in matching network of the output circuit during the transmission of various test pulse waveforms. , according to the formula Evaluate the degree of abnormality in the matching performance of the built-in matching network of the output network.
[0056] Compare various test pulse waveforms with their corresponding designated load actual received pulse waveforms, collect the frequencies and amplitudes of various harmonics in the spectrum distribution of various test pulse waveforms and their corresponding designated load actual received pulse waveforms, obtain the amplitude differences of the same frequency harmonics of each test pulse waveform and its corresponding designated load actual received pulse waveform, and obtain the average change amplitude of the harmonics of each test pulse waveform corresponding to the designated load actual received pulse waveform through mean calculation.
[0057] Extract the harmonics that do not exist in the frequency of each test pulse waveform but exist in the frequency of the pulse waveform actually received by the specified load, record them as the derived harmonics of the pulse waveform actually received by the specified load corresponding to each test pulse waveform, extract the amplitude of each derived harmonic and calculate the average to obtain the harmonic average derived amplitude of the pulse waveform actually received by the specified load corresponding to each test pulse waveform.
[0058] The harmonic average derivative amplitude and the harmonic average change amplitude are accumulated, and the ratio of the accumulated value to the preset reference harmonic amplitude is used as the harmonic component growth degree, so as to obtain the harmonic component growth degree of the actual received pulse waveform of the specified load corresponding to various test pulse waveforms, and the average calculation is used to evaluate the channel linearity abnormality of the built-in matching network of the output circuit.
[0059] The accumulated value of the matching performance abnormality degree and the channel linearity abnormality degree is used as the fault risk coefficient of the output circuit of the target device.
[0060] Specifically, the analysis of the failure risk coefficient of the heat dissipation device of the target equipment includes: monitoring the internal temperature value and the heat dissipation of the heat dissipation device at each unit time point in each preset time period of the target equipment during the overall test process of various test input signals, evaluating the heat dissipation effect coefficient and the heat dissipation capacity coefficient of the target equipment in each preset time period, and analyzing and obtaining the failure risk coefficient of the heat dissipation device of the target equipment in accordance with the calculation method of the failure risk coefficient of the control circuit of the target equipment.
[0061] It should be noted that the specific evaluation of the heat dissipation effect coefficient and the heat dissipation capacity coefficient of the above-mentioned target equipment in each preset time period is as follows: the internal temperature value of each unit time point in the preset time period is substituted into the rectangular coordinate system to draw the temperature change curve of the target equipment in the preset time period, the slope value of the curve in the preset time period is calculated, and it is used as the exponent of the exp function to obtain the heat dissipation effect coefficient of the preset time period, the heat dissipation of the heat dissipation device at each unit time point in the preset time period is compared with the design standard heat dissipation of the corresponding internal temperature value, the heat dissipation deficiency ratio of the heat dissipation device at each unit time point in the preset time period is analyzed, and the degree of deficiency of heat dissipation of the heat dissipation device in the preset time period is obtained by mean calculation, and its negative value is further used as the exponent of the exp function to obtain the heat dissipation capacity coefficient of the preset time period, thereby obtaining the heat dissipation effect coefficient and heat dissipation capacity coefficient of the target equipment in each preset time period.
[0062] The embodiment of the present invention generates various test input signals through the built-in signal generator of the target device control circuit, and non-invasively and autonomously tests the all-round working performance of the target device control circuit, main circuit, output circuit and heat dissipation device, accurately understands the failure risk factor of each component unit of the target device, and realizes comprehensive and accurate fault detection of the UV pulse power supply.
[0063] S4. Consider the impact of failures between the various components and evaluate the failure probability of the target device's control circuit, main circuit, output circuit, and heat sink.
[0064] Specifically, the evaluation of the failure probability of the control circuit, main circuit, output circuit and heat sink of the target device includes: extracting the corresponding fault risk coefficient warning thresholds of the UV pulse power supply control circuit, main circuit, output circuit and heat sink stored in the WEB cloud, and performing ratio analysis on the failure risk coefficients of the control circuit, main circuit, output circuit and heat sink of the target device with their corresponding warning thresholds to obtain the potential failure probability of the control circuit, main circuit, output circuit and heat sink of the target device, and based on the summary table of the failure impact ratio of each component unit of the UV pulse power supply stored in the WEB cloud, find the failure impact ratio of each component unit involving other components, so as to correct the potential failure probability of each component unit of the target device, thereby evaluating and obtaining the failure probability of the control circuit, main circuit, output circuit and heat sink of the target device.
[0065] It should be noted that the above-mentioned summary table of the impact of failures of each component unit of the UV pulse power supply is set based on the following: the failure of each component unit will directly lead to abnormal performance of its downstream component unit, that is, the control circuit is the nerve center of the UV pulse power supply, and the control circuit is responsible for receiving external instructions, accurately regulating the working status of the main circuit and the output circuit, and monitoring and managing the operation of the heat dissipation device to ensure the overall optimization of the system performance. Once the control circuit fails, it will directly lead to the loss of control of the working status of the main circuit and the output circuit, which may cause problems such as output waveform distortion and power instability. At the same time, due to the interruption or error of the control signal, the heat dissipation device may not be able to adjust the heat dissipation strategy according to actual needs, resulting in an increased risk of overheating. Therefore, the failure of the control circuit will directly affect the abnormal performance of the main circuit, the output circuit, and the heat dissipation device, making the corresponding potential failure probability of the main circuit, the output circuit, and the heat dissipation device higher.
[0066] As the core conversion unit of the UV pulse power supply, the main circuit is responsible for efficiently converting the input electrical energy into pulse electrical energy of a specific frequency and amplitude, providing a stable and reliable energy supply for the load. The failure of the main circuit will directly affect the output circuit performance of the UV pulse power supply. In addition, it may also indirectly affect the heat dissipation effect of the heat sink by changing the power loss distribution. Therefore, the failure of the main circuit will directly affect the abnormal performance of the output circuit and the heat sink, making the probability of potential failure of the output circuit and the heat sink higher.
[0067] The output circuit is directly connected to the load and is responsible for safely and efficiently transmitting the pulse power generated by the main circuit to the load end to ensure the normal operation of the load. The failure of the output circuit will directly affect the quality of the power received by the load. Since there may be a thermal coupling relationship between the output circuit and the heat sink, the failure of the output circuit may also indirectly affect the heat dissipation effect of the heat sink. Therefore, the failure of the output circuit will directly affect the abnormal performance of the heat sink, making the corresponding potential failure probability of the heat sink higher.
[0068] However, when a component unit exhibits a serious fault, it will also indirectly and reversely affect its upstream component unit. Usually, the proportion of the reverse fault impact is smaller than the proportion of the forward fault impact.
[0069] For example, the summary table of the failure impact ratio of each component unit of the UV pulse power supply is specifically referred to the following Table 1.
[0070] Table 1 Summary of the impact of failures on each component of UV pulse power supply
[0071]
[0072] The above correction of the potential failure probability of each component unit of the target device includes: recording the potential failure probability of the target device control circuit, main circuit, output circuit and heat dissipation device as , the proportion of the control circuit affected by the failure of the main circuit, output circuit and heat sink is recorded as , then by the formula The failure probability of the control unit of the target device is obtained, and the failure probability of the main circuit, output circuit and heat dissipation device of the target device is analyzed similarly.
[0073] The embodiment of the present invention considers the impact of failures between various components and performs corresponding correction processing based on the potential failure probabilities of the target device control circuit, main circuit, output circuit and heat dissipation device, thereby improving the authenticity, accuracy and reliability of failure probability assessment.
[0074] S5. Generate and feedback the internal fault inspection report based on the failure probability of each component unit of the target device.
[0075] Reference Figure 2 As shown, the second aspect of the present invention provides an intelligent fault detection system for a UV pulse power supply, comprising: a fault risk manifestation identification module, a fault internal inspection mechanism triggering module, a fault risk coefficient analysis module, a fault probability assessment module, a fault internal inspection report feedback module and a cloud database.
[0076] The fault risk manifestation identification module is connected to the fault internal inspection mechanism trigger module, the fault internal inspection mechanism trigger module is connected to the fault risk coefficient analysis module, the fault risk coefficient analysis module is connected to the fault probability assessment module, the fault probability assessment module is connected to the fault internal inspection report feedback module, and the cloud database is respectively connected to the fault risk manifestation identification module and the fault probability assessment module.
[0077] The fault risk manifestation identification module is used to record the target UV pulse power supply device as the target device, monitor the pulse waveform data of the target device outputting the specified load in real time, and identify whether the target device has a fault risk manifestation.
[0078] The fault internal inspection mechanism triggering module is used to trigger the fault internal inspection mechanism if the target device is identified to have fault risk manifestations.
[0079] The fault risk coefficient analysis module is used to troubleshoot each component unit of the target device in turn, each component unit includes a control circuit, a main circuit, an output circuit and a heat dissipation device, and analyze the fault risk coefficient of the control circuit, main circuit, output circuit and heat dissipation device of the target device.
[0080] The failure probability assessment module is used to consider the impact of failures between various components and assess the failure probability of the target device's control circuit, main circuit, output circuit, and heat dissipation device.
[0081] The fault internal inspection report feedback module is used to generate and feedback the fault internal inspection report according to the fault probability of each component unit of the target device.
[0082] The cloud database is used to store the fault risk factor warning thresholds corresponding to the target equipment control circuit, main circuit, output circuit and heat dissipation device, store the reasonable parameter range content of the power supply pulse required by the specified load technical specifications, and store the summary table of the fault impact ratio of each component unit of the UV pulse power supply.
[0083] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.
Claims
1. An intelligent fault detection method for UV pulse power supply, characterized in that: The method includes: S1. Record the target UV pulse power supply as the target device, monitor the pulse waveform data of the target device outputting the specified load in real time, and identify whether the target device has a fault risk performance; S2. If the target device is identified as having a risk of failure, its internal fault detection mechanism is triggered; S3. Perform troubleshooting on each component unit of the target device in turn, each component unit includes a control circuit, a main circuit, an output circuit and a heat sink, and analyze the failure risk coefficient of the control circuit, the main circuit, the output circuit and the heat sink of the target device; S4. Consider the impact of failures between the various components and evaluate the failure probability of the target device's control circuit, main circuit, output circuit, and heat sink; S5. Generate and feedback the internal fault inspection report based on the failure probability of each component unit of the target device.
2. The intelligent fault detection method of a UV pulse power supply according to claim 1, characterized in that: The identification of whether the target device has a fault risk performance includes: analyzing the rationality index of the pulse waveform of the load connected to the current target device output according to the pulse waveform data of the specified load output by the current target device, including the proportion of harmonic components of the overall pulse waveform, the pulse voltage peak value, duty cycle, rise time, fall time and pulse period of each pulse, and stability indicators , add the two products with their corresponding preset weights to obtain the comprehensive evaluation index of the load pulse waveform of the current target device output connection. If it is less than or equal to the preset comprehensive evaluation index warning threshold, the target device is identified to have a fault risk performance, otherwise it is identified to not exist.
3. The intelligent fault detection method of a UV pulse power supply according to claim 2 is characterized in that: Said The analysis process includes: supplying reasonable parameter ranges of power pulses according to the technical specifications of the specified load stored in the WEB cloud, including the reasonable ranges corresponding to the pulse voltage peak, duty cycle, rise time, and fall time, extracting the pulse voltage peak, duty cycle, rise time, and fall time of each pulse of the specified load output by the current target device, comparing each parameter with its corresponding reasonable range, analyzing the overall abnormal deviation of each pulse of the specified load output by the current target device, and taking the inverse of the calculated mean as the rationality indicator of the pulse waveform of the load connected to the current target device output.
4. The intelligent fault detection method of a UV pulse power supply according to claim 2 is characterized in that: Said The analysis process includes: extracting the pulse voltage peak value and pulse period of each pulse, calculating the amplitude variance and period variance of the pulse waveform of the current target device output connected load respectively, accumulating them in combination with the proportion of harmonic components of the overall pulse waveform, and using the inverse of the accumulated value as the stability indicator of the pulse waveform of the current target device output connected load.
5. The intelligent fault detection method of a UV pulse power supply according to claim 1, characterized in that: The analysis of the failure risk coefficient of the target device control circuit includes: activating a built-in signal generator and a signal capturer of the target device control circuit, generating various test input signals by the signal generator and capturing the corresponding execution control signals by the signal capturer, and continuously monitoring the voltage value of each unit time point within a preset time length of the corresponding feedback signal by the built-in feedback loop during the control signal issuance process; Analyze the expected deviation between various test input signals and their corresponding execution control signals, and obtain the control signal execution correctness of the target device control circuit based on the preset test weights of various test input signals ; Analyze the voltage standard deviation of the feedback signal corresponding to the control signal sending process of various test input signals, and analyze the control signal sending stability of the target device control circuit ; Activate the logic analyzer to distribute the probes of each key node of the target device control circuit, identify the timing diagrams of the corresponding execution control signals and corresponding feedback signals within the preset time of various test input signals, record them as the timing diagrams of each test signal, check the logical sequence status and signal conflict status of each test signal timing diagram, so as to analyze the normality of the logical function status of the target device control circuit ; By formula Get the failure risk factor of the target device control circuit, is a preset constant.
6. The intelligent fault detection method of a UV pulse power supply according to claim 5, characterized in that: The analysis of the failure risk coefficient of the main circuit of the target device includes: recording the execution control signals corresponding to various test input signals as various test control signals, detecting the working conditions of the built-in rectifier, inverter, transformer and filter of the main circuit after the main circuit receives the various test control signals, analyzing the working abnormality indicators of the built-in rectifier, inverter, transformer and filter of the main circuit of the target device, and accumulating them to obtain the overall working function abnormality coefficient of the main circuit of the target device; Monitor the maximum temperature value, maximum temperature rise value per unit time and maximum vibration amplitude during the overall working period of the main circuit of the target equipment receiving various test control signals, and analyze the abnormal coefficient of the overall working state of the main circuit of the target equipment; The overall working state abnormality coefficient and the overall working function abnormality coefficient are accumulated to obtain the fault risk coefficient of the main circuit of the target device.
7. The intelligent fault detection method of a UV pulse power supply according to claim 5, characterized in that: The analysis of the failure risk coefficient of the output circuit of the target device includes: outputting pulse waveforms corresponding to various test input signals and executing control signals through the main circuit of the target device, which are recorded as various test pulse waveforms, transmitting the various test pulse waveforms to the specified load through the output circuit of the target device, monitoring the reflection coefficient and insertion loss of the built-in matching network of the output circuit during the transmission of the various test pulse waveforms, and evaluating the abnormality of the matching performance of the built-in matching network of the output network; Compare various test pulse waveforms with the actual received pulse waveforms of the corresponding specified loads to evaluate the channel linearity anomaly of the built-in matching network of the output circuit; The fault risk coefficient of the output circuit of the target device is obtained by accumulating the abnormal degree of the matching performance and the abnormal degree of the channel linearity.
8. The intelligent fault detection method of a UV pulse power supply according to claim 5, characterized in that: The analysis of the failure risk coefficient of the heat dissipation device of the target device includes: monitoring the internal temperature value and the heat dissipation of the heat dissipation device at each unit time point in each preset time period of the target device during the overall test process of various test input signals, evaluating the heat dissipation effect coefficient and the heat dissipation capacity coefficient of the target device in each preset time period, and analyzing and obtaining the failure risk coefficient of the heat dissipation device of the target device in accordance with the calculation method of the failure risk coefficient of the control circuit of the target device.
9. The intelligent fault detection method of a UV pulse power supply according to claim 1, characterized in that: The evaluation of the failure probability of the control circuit, main circuit, output circuit and heat sink of the target device includes: extracting the warning threshold values of the failure risk coefficients corresponding to the control circuit, main circuit, output circuit and heat sink of the UV pulse power supply stored in the WEB cloud, performing ratio analysis on the failure risk coefficients of the control circuit, main circuit, output circuit and heat sink of the target device and the corresponding warning threshold values, so as to obtain the potential failure probability of the control circuit, main circuit, output circuit and heat sink of the target device, and finding the failure influence proportion of each component unit involving other components based on the summary table of the failure influence proportion of each component unit of the UV pulse power supply stored in the WEB cloud, so as to correct the potential failure probability of each component unit of the target device, so as to evaluate and obtain the failure probability of the control circuit, main circuit, output circuit and heat sink of the target device.
10. An intelligent fault detection system for UV pulse power supply, characterized in that: The system includes: A fault risk manifestation identification module is used to record the target UV pulse power supply as the target device, monitor the pulse waveform data of the target device outputting the specified load in real time, and identify whether the target device has fault risk manifestations; A fault internal inspection mechanism triggering module is used to trigger the fault internal inspection mechanism of the target device if it is identified that the target device has a fault risk. A fault risk coefficient analysis module is used to sequentially troubleshoot each component unit of the target device, each component unit includes a control circuit, a main circuit, an output circuit and a heat sink, and analyze the fault risk coefficients of the control circuit, the main circuit, the output circuit and the heat sink of the target device; Failure probability assessment module, which is used to consider the impact of failures between various components and assess the failure probability of the target device's control circuit, main circuit, output circuit, and heat sink; A fault internal inspection report feedback module is used to generate and feedback a fault internal inspection report according to the fault probability of each component unit of the target device; The cloud database is used to store the fault risk factor warning thresholds corresponding to the UV pulse power supply control circuit, main circuit, output circuit and heat dissipation device, store the reasonable parameter range content of the power supply pulse required by the specified load technical specifications, and store the summary table of the fault impact ratio of each component unit of the UV pulse power supply.