A method for monitoring the operating status of a power supply under high-temperature conditions and a high-temperature power supply

Abstract

This application relates to the field of power supply fault monitoring technology, specifically to a method for monitoring the operating status of a power supply under high-temperature conditions and a high-temperature power supply. The method includes: determining a first fault factor by comprehensively analyzing the differences between voltage offset values ​​and temperature data across all time periods within a preset time frame, and the fusion results of voltage offset values ​​across all time periods; determining a second fault factor by analyzing the average distribution of high-frequency ripple energy across all time periods, and the similarity between vibration characteristic values ​​and ripple coefficients across all time periods; and combining the first fault factor with the second fault factor to determine the comprehensive fault factor of the high-temperature power supply at each time point, thereby monitoring the operating status of the high-temperature power supply. This application solves the problem that monitoring power system stability solely through the integral value of the ripple signal makes it difficult to accurately capture abnormal operating states of high-temperature power supplies, thus improving the sensitivity of early fault monitoring for high-temperature power supplies.

Description

Technical Field

[0001] This application relates to the field of power supply fault monitoring technology, specifically to a method for monitoring the operating status of a power supply under high temperature conditions and a high temperature power supply. Background Technology

[0002] With the continuous development of industrial technology, the demand for power supplies in high-temperature environments is increasing. In oil and gas drilling platforms, downhole tools, logging-while-drilling equipment, and electronic components used in fracturing operations all require stable DC power supplies. In deep or ultra-deep well environments, temperatures can reach over 150°C, and due to drilling operations, equipment is often subjected to strong vibrations. Compared to ordinary switching power supplies, high-temperature power supplies have lower robustness in these extreme environments, and failures develop more rapidly. Therefore, shutdown actions must be initiated in the early stages of a failure to prevent further damage. Consequently, high sensitivity is required for monitoring the operating status of high-temperature power supplies.

[0003] Existing technologies utilize the integrating circuit of a high-temperature power supply to detect the integral value of the ripple signal over a long period, avoiding the impact of short-term noise on the high-temperature power supply data measurement, thereby reducing the probability of false alarms and improving system reliability. However, in oil and gas drilling platforms, the initial faults of high-temperature power supplies manifest as weak ripple characteristics. Monitoring the stability of the power supply system solely through the integral value of the ripple signal is insufficient to accurately capture abnormal operating conditions, resulting in poor sensitivity for early fault detection of high-temperature power supplies. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a method for monitoring the operating status of a power supply under high-temperature conditions and a high-temperature power supply. The specific technical solution adopted is as follows:

[0005] In a first aspect, embodiments of this application provide a method for monitoring the operating status of a power supply under high-temperature conditions, the method comprising the following steps:

[0006] Intelligent sensors are used to collect voltage data and vibration acceleration data of high-temperature power supply in real time at different times, and to obtain temperature data at the preset start time of each time period as the temperature data for each time period.

[0007] By comparing the average distribution of all voltage data in each time period with the difference between the preset rated output voltage of the high-temperature power supply, the voltage offset value of each time period is determined; by combining the difference between the voltage offset value and the temperature data in all time periods within the preset time period before each moment, and the fusion result of the voltage offset value of all time periods, the first fault factor of the high-temperature power supply at each moment is determined.

[0008] The system acquires the spectral sequence of all voltage data above a preset switching frequency in the frequency domain within each time period. It then determines the high-frequency ripple energy of the high-temperature power supply at each time period by considering the modulus of all elements in the spectral sequence. Based on the distribution of all vibration accelerations within each time period, it determines the vibration characteristic value of the high-temperature power supply at each time period. Based on all voltage data within each time period, it obtains the ripple coefficient for each time period. Within a preset time period before each moment, it analyzes the average distribution of high-frequency ripple energy across all time periods to determine the energy distribution value of the high-temperature power supply at each moment. Finally, it combines the similarity between the vibration characteristic value and the ripple coefficient across all time periods to determine the second fault factor of the high-temperature power supply at each moment.

[0009] The dispersion of temperature data for all time periods within a preset time range before each time point and the sum of vibration characteristic values ​​for all time periods are used as the weights of the first fault factor and the second fault factor, respectively, to determine the comprehensive fault factor of the high-temperature power supply at each time point, so as to monitor the working status of the high-temperature power supply.

[0010] Preferably, the voltage offset value for each time period is the difference between the average of all voltage data within each time period and the preset rated output voltage of the high-temperature power supply.

[0011] Preferably, the expression for the first fault factor of the high-temperature power supply at each time point is: F i =D i ×ΔU i In the formula, F i D represents the first failure factor of the high-temperature power supply at time i; i ΔU represents the DTW distance between the normalized value of the voltage offset and the normalized value of the difference between the temperature data and the normalized value of the voltage offset for all time periods within a preset duration prior to time i; i This represents the cumulative sum of voltage deviations over all time periods within a preset duration prior to time i.

[0012] Preferably, the high-frequency ripple energy of the high-temperature power supply in each time period is the sum of the moduli of all elements in the spectral sequence of each time period.

[0013] Preferably, the vibration characteristic value of the high-temperature power supply in each time period is the mean square value of all vibration accelerations in each time period.

[0014] Preferably, the energy distribution value of the high-temperature power supply at each moment is the average value of the high-frequency ripple energy at all time periods within a preset time period before each moment.

[0015] Preferably, the expression for the second fault factor of the high-temperature power supply at each time point is: S i =(sim i +δ)×E i In the formula, S i sim represents the second fault factor of the high-temperature power supply at time i;i E represents the similarity between the ripple coefficient and the vibration characteristic value across all time periods within a preset duration prior to time i. i δ represents the energy distribution value of the high-temperature power source at time i; δ represents a preset constant greater than 1.

[0016] Preferably, the expression for the comprehensive failure factor of the high-temperature power supply at each time point is: T i =w1 i ×F i +w2 i ×S i In the formula, T i w1 represents the comprehensive failure factor of the high-temperature power supply at time i; i w2 i F represents the dispersion of temperature data for all time periods within a preset time duration prior to time i, and the sum of vibration characteristic values ​​for all time periods, respectively; i S i Let i and i represent the first fault factor and the second fault factor of the high-temperature power supply at time i, respectively.

[0017] Preferably, controlling the operating state of the high-temperature power supply includes:

[0018] Each time period is used to form a monitoring window. Voltage data, vibration acceleration, and temperature data are acquired within a preset number of monitoring windows when the high-temperature power supply is working normally in oil and gas drilling. For each monitoring window, the comprehensive fault factor within a preset number of monitoring windows is acquired according to the method for acquiring the comprehensive fault factor. The maximum comprehensive fault factor is used as the fault threshold. If the comprehensive fault factor of the high-temperature power supply is greater than the fault threshold at the current time, the working state of the high-temperature power supply is abnormal at the current time. Otherwise, the working state of the high-temperature power supply is normal.

[0019] Secondly, embodiments of this application also provide a high-temperature power supply, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the power supply operating status monitoring method under high-temperature environment described in any one of the above-mentioned methods.

[0020] This application has at least the following beneficial effects:

[0021] First, the substrate material of the high-temperature power supply in this application is lithium oxide, replacing the PCB board in the prior art. The outer shell is made of pure copper plated with gold, and a heat dissipation structure is provided inside the shell to improve the heat dissipation efficiency of the high-temperature power supply, enabling it to maintain efficient and stable power output in high-temperature environments, providing strong protection for the operation of other electrical equipment. Furthermore, this application collects voltage data, vibration acceleration, and temperature data of the high-temperature power supply by installing various intelligent sensors. By combining the differences between voltage offset values ​​and temperature data over all time periods within a preset time frame, and the fusion results of voltage offset values ​​over all time periods, a first fault factor is constructed. This more accurately identifies voltage instability caused by feedback circuit failure, thereby achieving early warning and improving... The sensitivity of early-stage monitoring of high-temperature power supplies is improved. Furthermore, this application constructs a second fault factor by analyzing the high-frequency ripple energy of the high-temperature power supply output voltage, environmental vibration characteristics, and their correlation with the ripple coefficient. This factor can effectively monitor the power supply status and sensitively reflect the potential contact fault risk of the filter circuit due to vibration and other factors, thereby achieving early warning of high-temperature power supplies and improving the sensitivity of early-stage monitoring. This embodiment also utilizes multi-smart sensor fusion to analyze voltage deviation, high-frequency ripple, environmental vibration, and temperature changes, constructing a comprehensive fault factor that reflects potential faults in the feedback circuit and filter circuit. This helps assess the overall fault risk of the power supply and enables early warning in harsh environments such as oil and gas drilling, improving the sensitivity of early-stage monitoring of high-temperature power supplies. Attached Figure Description

[0022] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart illustrating the steps of a power supply operating status monitoring method under high temperature conditions, provided as an embodiment of this application;

[0024] Figure 2 This is a schematic diagram of the comprehensive fault factor extraction process provided in one embodiment of this application. Detailed Implementation

[0025] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a power supply operating status monitoring method and a high-temperature power supply under high-temperature conditions proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0027] The following description, in conjunction with the accompanying drawings, details a method for monitoring the operating status of a power supply under high-temperature conditions and a specific scheme for a high-temperature power supply provided in this application.

[0028] Please see Figure 1 The diagram illustrates a flowchart of a power supply operating status monitoring method under high-temperature conditions according to an embodiment of this application. The method includes the following steps:

[0029] Step S1: Use intelligent sensors to collect voltage data and vibration acceleration data of the high-temperature power supply in real time for each period, and obtain temperature data at the preset start time of each period as the temperature data for each period.

[0030] The high-temperature power supply proposed in this embodiment includes the following functions:

[0031] The soft-start circuit can slowly increase the input current after the power supply starts at high temperature and the fault is cleared, which facilitates the connection of a large-capacity output filter capacitor and reduces the startup impact.

[0032] The power feedback circuit can isolate the input and output of the high-temperature power supply and enable high-precision and high-efficiency control of the output voltage, ensuring the stability of the high-temperature power supply output voltage.

[0033] The undervoltage and overvoltage shutdown circuit can stop the high-temperature power supply from operating when the input voltage exceeds the range, thus protecting the power supply. In this embodiment, the undervoltage and overvoltage shutdown voltage is within 5V beyond the rated voltage. For example, in an input range of 24 to 72V, its undervoltage shutdown voltage is 21 to 23.9V, and its overvoltage shutdown voltage is 72.1 to 77V.

[0034] The output short-circuit and overload automatic shutdown circuit, in this embodiment, cuts off all outputs when the output exceeds 150% of the rated output power for 0.1s. After the overcurrent fault is cleared, it automatically enters soft-start mode and restores the output voltage. If the output overload lasts for less than 0.1s, the high-temperature power supply does not take any action.

[0035] The shutdown terminal controls the operating status of the high-temperature power supply. When a fault is detected in the high-temperature power supply, it switches to a sleep state to protect the power supply and other electrical equipment. In this embodiment, the shutdown terminal is active high. When the voltage is 3.2–5.3V, the high-temperature power supply enters a sleep state, cutting off all outputs, and the input current is less than 1mA. When the voltage is 0–2.5V or floating, the high-temperature power supply operates normally, and the input voltage of the shutdown terminal must not exceed 12.0V.

[0036] Considering the heat dissipation requirements of high-temperature power supplies, the substrate material of the high-temperature power supply in this embodiment is lithium oxide, and the shell material is pure copper plated with gold. At the same time, a heat dissipation structure is provided inside the shell to improve the heat dissipation efficiency of the high-temperature power supply, so that it can maintain efficient and stable power output in high-temperature environments and provide strong protection for the operation of other electrical equipment.

[0037] The high temperatures and strong vibrations encountered during oil and gas drilling increase the probability of output voltage deviation and excessive ripple voltage in high-temperature power supplies. To protect the high-temperature power supply and electrical equipment used in oil and gas drilling, when the high-temperature power supply is detected to be in the above-mentioned operating state, the high-temperature power supply shutdown terminal should be set to a high level to put it into a sleep state.

[0038] In the high-temperature and high-vibration working environments of oil and gas drilling, on the one hand, temperature changes in high-temperature environments can easily lead to a decrease in the operational stability of electronic components in high-temperature power supplies, causing output voltage deviations; on the other hand, strong vibrations can damage the stability of internal component connections in high-temperature power supplies, causing filter circuit connections to loosen or break, increasing output voltage ripple. Under extreme working conditions, high-temperature power supplies have poor robustness and require timely shutdown actions under abnormal operating conditions to prevent the abnormalities from developing into more serious failures.

[0039] Therefore, this embodiment uses multiple smart sensors to comprehensively monitor the operating status and environmental changes of the high-temperature power supply. Utilizing the correlation between environmental data and operating status data in the early stages of a high-temperature power supply failure, multi-sensor data fusion is employed to improve the sensitivity of monitoring the high-temperature power supply's operating status. Specifically:

[0040] A smart voltage sensor is used to collect the voltage data output by the high-temperature power supply in real time. In this embodiment, the sampling frequency of the voltage data is set to 500kHz to capture the characteristics of high-frequency ripple voltage. A smart accelerometer is used to collect the vibration acceleration of the high-temperature power supply in real time. In this embodiment, the sampling frequency of the vibration acceleration is set to 5kHz. In practical applications, as other implementation methods, implementers can also set the sampling frequency of voltage data and vibration acceleration according to specific circumstances. This embodiment does not impose any special restrictions.

[0041] The collected voltage and acceleration data are segmented. In this embodiment, 500ms is used as the preset length of each time segment, meaning each time segment is 500ms long. In practical applications, as other implementation methods, implementers can set their own lengths according to specific circumstances; this embodiment does not impose any special limitations. Furthermore, considering the impact of random noise in the high-temperature power supply's operating environment on data acquisition, this embodiment applies the 3σ principle to remove voltage and vibration acceleration data exceeding the mean ± 3 times the standard deviation for each time segment, thus completing outlier screening. Further, linear interpolation is used to fill in the data at the screening locations, ensuring that the number of data points in each time segment is equal, avoiding the impact of missing data on subsequent analysis, and finally obtaining the voltage and vibration acceleration data of the high-temperature power supply within each time segment.

[0042] Furthermore, in this embodiment, an intelligent temperature sensor is used to collect the operating ambient temperature of the high-temperature power supply once at the beginning of each time period, which is used as the temperature data for each time period.

[0043] Furthermore, in order to eliminate the influence of data dimensions, the collected voltage data, vibration acceleration, and temperature data are normalized respectively. In this embodiment, the maximum-minimum value normalization method is used to normalize the data. In practical applications, as other implementation methods, implementers may also use the z-score normalization method to normalize the data according to specific circumstances. This embodiment does not impose any special restrictions on the selection of normalization methods.

[0044] In this embodiment, all content involving normalization processing adopts the maximum-minimum value normalization method.

[0045] Step S2: Compare the average distribution of all voltage data in each time period with the difference between the preset rated output voltage of the high-temperature power supply to determine the voltage offset value in each time period; combine the differences between the voltage offset value and the temperature data in all time periods within the preset time period before each moment, and the fusion result of the voltage offset values ​​in all time periods to determine the first fault factor of the high-temperature power supply at each moment.

[0046] For early fault monitoring of high-temperature power supplies, data from a single time period can only reflect the state of the power supply at a specific point in time, lacking dynamic trend information. Furthermore, during normal operation of the high-temperature power supply, voltage data will fluctuate within a certain range, and these fluctuations are numerically similar to the characteristics of early faults in the high-temperature power supply. Data from a single time period is insufficient to effectively distinguish between the two, leading to a decrease in monitoring sensitivity.

[0047] The core function of the power feedback circuit in a high-temperature power supply is to maintain the stability of the output voltage. It monitors the output voltage in real time and compares the monitored voltage signal with the rated output voltage of the high-temperature power supply, thereby adjusting the control circuit to keep the output voltage within the target range. This closed-loop control mechanism is crucial to the performance of the high-temperature power supply, especially in the harsh working environment of oil and gas drilling.

[0048] When the electronic components inside a high-temperature power supply are working, temperature has a significant impact on them. For example, the resistance of a resistor may deviate due to temperature changes, which in turn affects the output voltage. The input bias current or offset voltage of an operational amplifier may change due to temperature, causing the output voltage to deviate from the rated voltage. Therefore, when the temperature changes, a fault in the power supply feedback circuit can prevent the high-temperature power supply from accurately adjusting the output voltage.

[0049] Therefore, this embodiment determines the voltage offset value for each time period by comparing the average distribution of all voltage data within each time period with the difference between the preset rated output voltage of the high-temperature power supply; it also determines the first fault factor of the high-temperature power supply at each time period by combining the differences between the voltage offset value and the temperature data for all time periods within the preset duration before each moment, and the fusion result of the voltage offset values ​​for all time periods, thus eliminating the interference of temperature changes of the high-temperature power supply on the fault monitoring of the high-temperature power supply. Specifically:

[0050] First, this embodiment determines the voltage offset value for each time period by comparing the average distribution of all voltage data within each time period with the difference between the preset rated output voltage of the high-temperature power supply. Specifically:

[0051] In this embodiment, the difference between the average of all voltage data in each time period and the preset rated output voltage of the high-temperature power supply is used as the voltage offset value for each time period, wherein the difference is the absolute value of the difference.

[0052] It should be noted that the preset rated output voltage of the high-temperature power supply is set manually. The preset rated voltage is generally determined by the properties of the high-temperature power supply. In this embodiment, the preset rated output voltage is 12V. In actual applications, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0053] Based on the voltage deviation values ​​at different time periods, it can be understood that the larger the voltage deviation value, the more serious the deviation of the high-temperature power supply's output voltage from its rated output voltage, indicating a decrease in the stability of the high-temperature power supply; conversely, the larger the voltage deviation value, the closer the high-temperature power supply's output voltage is to its rated output voltage, indicating better stability of the high-temperature power supply.

[0054] Furthermore, this embodiment determines the first fault factor of the high-temperature power supply at each moment by comprehensively considering the differences between the voltage offset values ​​and temperature data in all time periods within a preset time range prior to each moment, as well as the fusion results of the voltage offset values ​​in all time periods. Specifically:

[0055] As one implementation method, in this embodiment, the first fault factor F of the high-temperature power supply at time i is... i The expression is: F i =D i ×ΔU i In the formula, D i ΔU represents the DTW distance between the normalized value of the voltage offset and the normalized value of the difference between the temperature data and the normalized value of the voltage offset for all time periods within a preset duration prior to time i; i This represents the cumulative sum of voltage deviations over all time periods within a preset duration prior to time i.

[0056] The method for calculating the DTW distance is a well-known technique, and its specific calculation process will not be elaborated here.

[0057] It should be noted that the preset duration is set manually. In this embodiment, the preset duration is 10 seconds. In actual applications, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0058] Based on the first fault factor of the high-temperature power supply at each time point, it can be understood that the DTW distance between the normalized value of the voltage offset and the normalized value of the difference between the temperature data at all time periods reflects the correlation between temperature change and voltage offset, and reflects the ability of the high-temperature power supply feedback circuit to adjust the output voltage in response to temperature changes. If the DTW distance is larger, the corresponding first fault factor is also larger. This means that when the temperature changes, the voltage offset mode of the output of the high-temperature power supply feedback circuit is not strongly correlated with the temperature change mode, the adjustment behavior may be chaotic or lagging, the adjustment performance is poor, and the possibility of failure is greater. At the same time, if the cumulative sum of the voltage offset values ​​is larger, it indicates that the voltage regulation performance of the high-temperature power supply is poor and the output voltage is unstable. In this case, the possibility of failure of the high-temperature power supply is greater, and therefore, the corresponding first fault factor is larger.

[0059] Conversely, the smaller the DTW distance, the smaller the corresponding first fault factor. This means that when the temperature changes, the voltage offset mode of the high-temperature power supply feedback circuit is more strongly correlated with the temperature change mode. At the same time, the smaller the sum of the voltage offset values, the better the voltage regulation performance of the high-temperature power supply and the more stable the output voltage. In this case, the possibility of a fault in the high-temperature power supply is smaller, and therefore, the corresponding first fault factor is smaller.

[0060] Thus, this embodiment effectively monitors the health status of the high-temperature power supply feedback circuit by analyzing the voltage deviation value and its correlation with temperature changes. It not only considers the degree of voltage deviation but also combines the matching degree between voltage deviation and temperature fluctuation patterns, which can eliminate temperature interference and more accurately identify voltage instability caused by feedback circuit failure, thereby achieving early warning and improving the sensitivity of monitoring the early working status of the high-temperature power supply.

[0061] Step S3: Obtain the spectrum sequence of all voltage data above the preset switching frequency in the frequency domain within each time period. Combine the modulus of all elements in the spectrum sequence to determine the high-frequency ripple energy of the high-temperature power supply in each time period. Based on the distribution of all vibration accelerations within each time period, determine the vibration characteristic value of the high-temperature power supply in each time period. Based on all voltage data within each time period, obtain the ripple coefficient of each time period. Within a preset time period before each moment, analyze the average distribution of high-frequency ripple energy in all time periods to determine the energy distribution value of the high-temperature power supply at each moment. Combine the similarity between the vibration characteristic value and the ripple coefficient in all time periods to determine the second fault factor of the high-temperature power supply at each moment.

[0062] Since ripple is unavoidable in the output voltage of a high-temperature power supply, the high-frequency components in the ripple will increase when the filter circuit fails. Therefore, this embodiment obtains the spectral sequence of all voltage data above a preset switching frequency in the frequency domain within each time period, and determines the high-frequency ripple energy of the high-temperature power supply in each time period by combining the magnitudes of all elements in the spectral sequence. Specifically:

[0063] In this embodiment, the Fast Fourier Transform algorithm is used to obtain the spectral sequence of all voltage data in each time period above a preset switching frequency in the frequency domain. The preset switching frequency is 200kHz. The implementer can also set the switching frequency according to the specific situation. This embodiment does not impose any special restrictions.

[0064] The Fast Fourier Transform algorithm is a well-known technique, and the specific process of obtaining the spectrum sequence using it will not be elaborated here.

[0065] Furthermore, in this embodiment, the sum of the moduli of all elements in the spectrum sequence of each time period is used as the high-frequency ripple energy of the high-temperature power supply in each time period.

[0066] Based on the high-frequency ripple energy of the high-temperature power supply at different time periods, it can be understood that high-frequency ripple energy is used to measure the voltage energy contained in the frequency band above the switching frequency in the output voltage of the high-temperature power supply. It reflects the intensity of high-frequency ripple in the output voltage of the high-temperature power supply. If the high-frequency ripple energy is larger, it indicates that the high-temperature power supply may have faults such as poor contact, which weakens its ability to suppress high-frequency ripple. Conversely, if the high-frequency ripple energy is smaller, it indicates that the power supply's filtering circuit is working properly and can effectively suppress high-frequency ripple, resulting in a higher purity of the output voltage. In addition, if the difference between the vibration acceleration and voltage data is too large, the acceleration data needs to be preprocessed in advance. Therefore, this embodiment determines the vibration characteristic value of the high-temperature power supply at each time period based on the distribution of all vibration accelerations in each time period, specifically:

[0067] In this embodiment, the mean square value of all vibration accelerations in each time period is used as the vibration characteristic value of the high-temperature power supply in each time period.

[0068] The method for calculating the mean square value is a well-known technique, and its specific calculation process will not be elaborated here.

[0069] Based on the vibration characteristic values ​​of the high-temperature power supply at different time periods, it can be understood that the vibration characteristic values ​​quantify the intensity of vibration of the high-temperature power supply and its surrounding environment. If the vibration characteristic value is larger, it indicates that the vibration of the high-temperature power supply is more intense, and conversely, if the vibration characteristic value is smaller, it indicates that the high-temperature power supply is more stable.

[0070] Furthermore, the ripple coefficient for each time period is calculated based on all voltage data within each time period. The magnitude of the ripple coefficient reflects the proportion of residual components in the DC voltage. The smaller the ripple coefficient, the higher the stability of the high-temperature power supply within the corresponding time period. The calculation method for the ripple coefficient is a well-known technique, and its specific calculation process will not be elaborated here.

[0071] Furthermore, this embodiment analyzes the average distribution of high-frequency ripple energy across all time periods within a preset time interval before each moment to determine the energy distribution value of the high-temperature power supply at each moment. Combined with the similarity between the vibration characteristic values ​​and ripple coefficients across all time periods, the second fault factor of the high-temperature power supply at each moment is determined, specifically:

[0072] As one implementation method, in this embodiment, the average value of the high-frequency ripple energy during all time periods within a preset time period before each time moment is taken as the energy distribution value of the high-temperature power supply at each time moment.

[0073] In this embodiment, the second fault factor S of the high-temperature power supply at time i i The expression is: S i =(sim i +δ)×E i In the formula, sim iE represents the similarity between the ripple coefficient and the vibration characteristic value across all time periods within a preset duration prior to time i. i The value represents the energy distribution of the high-temperature power source at time i; δ represents a preset constant greater than 1, used to prevent simultaneous changes. i +δ is a negative number, and the value of δ is set manually. In this embodiment, the value of δ is 2, while ensuring sim i Provided that +δ is not negative and does not excessively affect the calculation result, the implementer may set it according to the specific situation. This embodiment does not impose any special restrictions.

[0074] It should be noted that there are many methods to measure the similarity between data groups. In this embodiment, the cosine similarity between the ripple coefficient and the vibration characteristic value in all time periods within the preset duration before time i is taken as the similarity between the ripple coefficient and the vibration characteristic value in all time periods within the preset duration before time i. In practical applications, as other implementation methods, implementers may also use other methods to measure the similarity between data groups, such as the reciprocal of the Euclidean distance, depending on the specific circumstances. This embodiment does not impose any special restrictions on the selection of methods to measure the similarity between data.

[0075] The method for calculating cosine similarity is a well-known technique, and its specific calculation process will not be elaborated here.

[0076] Based on the second fault factor of the high-temperature power supply at each time point, it can be understood that if the similarity between the ripple coefficient and the vibration characteristic value is greater in all time periods within the preset duration before time i, it indicates that the change patterns of the ripple coefficient and the vibration characteristic value are more similar. This means that the change patterns of the voltage ripple of the high-temperature power supply and the intensity of environmental vibration are closer, implying a greater possibility of vibration-induced filter circuit failure. Therefore, the corresponding second fault factor is larger. At the same time, if the average value of the high-frequency ripple energy is larger, that is, the energy distribution value is larger, it further indicates a greater possibility of contact failure in the filter circuit. Therefore, the second fault factor is also larger.

[0077] Conversely, if the similarity between the ripple coefficient and the vibration characteristic value is smaller in all time periods within the preset duration before time i, it indicates that the change patterns of the ripple coefficient and the vibration characteristic value are less similar. This suggests that the correlation between the change patterns of the high-temperature power supply voltage ripple magnitude and the environmental vibration intensity is weak, implying that the possibility of vibration-induced filter circuit failure is relatively small. Therefore, the corresponding second fault factor is relatively small. At the same time, if the mean value of the high-frequency ripple energy is smaller, that is, the energy distribution value is smaller, it further indicates that the possibility of contact fault in the filter circuit is relatively small. Therefore, the second fault factor is also relatively small.

[0078] Thus, this embodiment constructs a second fault factor by analyzing the high-frequency ripple energy of the high-temperature power supply output voltage, environmental vibration characteristics, and their correlation with the ripple coefficient. This factor can effectively monitor the power supply status and sensitively reflect the potential contact fault risk of the filter circuit due to factors such as vibration, thereby achieving early warning of the high-temperature power supply.

[0079] Step S4: The dispersion of temperature data for all time periods within the preset time period before each time point and the sum of vibration characteristic values ​​for all time periods are used as the weights of the first fault factor and the second fault factor, respectively, to determine the comprehensive fault factor of the high-temperature power supply at each time point, so as to monitor the working status of the high-temperature power supply.

[0080] Considering the variability of the working environment of high-temperature power sources in oil and gas drilling, different weights need to be assigned to the first fault factor and the second fault factor to further improve the sensitivity of monitoring the working status of high-temperature power sources. Therefore, this embodiment determines the comprehensive fault factor of the high-temperature power source at each time point by summing the dispersion of temperature data for all time periods within a preset time period before each time point and the sum of vibration characteristic values ​​for all time periods, respectively, as the weights of the first fault factor and the second fault factor, so as to control the working status of the high-temperature power source. Specifically:

[0081] As one implementation method, in this embodiment, the comprehensive failure factor T of the high-temperature power supply at time i is... i The expression is: T i =w1 i ×F i +w2 i ×S i In the formula, w1 i w2 i F represents the dispersion of temperature data for all time periods within a preset time duration prior to time i, and the sum of vibration characteristic values ​​for all time periods, respectively; i S i Let i and i represent the first fault factor and the second fault factor of the high-temperature power supply at time i, respectively.

[0082] Preferably, the schematic diagram of the comprehensive fault factor extraction process provided in this embodiment is as follows: Figure 2 As shown.

[0083] It should be noted that there are many methods to measure the dispersion of a set of data. In this embodiment, the dispersion coefficient of the temperature data of all time periods within the preset time period before time i is taken as the dispersion of the temperature data of all time periods within the preset time period before time i. In practical applications, as other implementation methods, implementers may also use other methods such as variance or standard deviation to measure the dispersion of data in combination with specific circumstances. This embodiment does not impose any special restrictions on the selection of methods to measure the dispersion of data.

[0084] The method for calculating the coefficient of variation is a well-known technique, and its specific calculation process will not be elaborated here.

[0085] Based on the comprehensive fault factor of the high-temperature power supply at each time point, it can be understood that the comprehensive fault factor quantifies the probability of the high-temperature power supply failing as a whole after comprehensively considering the voltage stability, temperature influence, vibration influence, and ripple situation of the power supply. If the first fault factor at time i is larger, and the dispersion of temperature data in all time periods within the preset time period before time i is larger, it indicates that the feedback circuit of the high-temperature power supply is more likely to fail, and the current ambient temperature fluctuation is more severe. Therefore, the corresponding comprehensive fault factor is larger, indicating that the risk of the high-temperature power supply failing due to feedback circuit problems or drastic temperature changes has significantly increased. At the same time, if the second fault factor at time i is larger, and the sum of vibration characteristic values ​​in all time periods within the preset time period before time i is larger, it indicates that the potential for contact failure in the filter circuit of the high-temperature power supply is greater, and the current vibration level of the high-temperature power supply is more severe. Therefore, the corresponding comprehensive fault factor is larger, indicating that the risk of the high-temperature power supply failing due to contact problems in the filter circuit has significantly increased.

[0086] Conversely, if the first fault factor at time i is smaller, and the dispersion of temperature data for all time periods within the preset duration before time i is smaller, it indicates that the feedback circuit of the high-temperature power supply is less likely to fail, and the current ambient temperature fluctuation is more stable. Therefore, the corresponding comprehensive fault factor is smaller, indicating that the risk of the high-temperature power supply failing due to feedback circuit problems or drastic temperature changes is lower. At the same time, if the second fault factor at time i is smaller, and the sum of vibration characteristic values ​​for all time periods within the preset duration before time i is smaller, it indicates that the filter circuit of the high-temperature power supply is less likely to fail, and the current vibration level of the high-temperature power supply is more stable. Therefore, the corresponding comprehensive fault factor is smaller, indicating that the risk of the high-temperature power supply failing due to filter circuit contact problems is lower.

[0087] Furthermore, a monitoring window is formed by pre-set durations before each moment. Voltage data, vibration acceleration, and temperature data are acquired within a pre-set number of monitoring windows when the high-temperature power supply is working normally in oil and gas drilling. For each monitoring window, the comprehensive fault factor within the pre-set number of monitoring windows is acquired according to the method for acquiring the comprehensive fault factor. The maximum comprehensive fault factor is used as the fault threshold. If the comprehensive fault factor of the high-temperature power supply at the current moment is greater than the fault threshold, the working state of the high-temperature power supply at the current moment is abnormal. The shutdown terminal of the high-temperature power supply at the current moment is set to a high level, so that the high-temperature power supply enters a dormant state to prevent the abnormal working state from developing further and causing more serious faults. Conversely, if the comprehensive fault factor of the high-temperature power supply at the current moment is less than or equal to the fault threshold, it indicates that the working state of the high-temperature power supply is normal.

[0088] It should be noted that the preset quantity is set manually. In this embodiment, the preset quantity is 5000. In actual applications, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0089] Thus, this embodiment, through the fusion of multiple intelligent sensors, analyzes voltage deviation, high-frequency ripple, environmental vibration, and temperature changes to construct a comprehensive fault factor that can reflect potential faults in the feedback circuit and filter circuit. This helps to assess the overall power supply failure risk, enabling early warning in harsh environments such as oil and gas drilling, timely power shutdown, and ensuring equipment safety.

[0090] Based on the same inventive concept as the above method, this application embodiment also provides a high-temperature power supply, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described methods for monitoring the operating status of a power supply under high-temperature conditions.

[0091] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0092] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0093] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for monitoring the operating status of a power supply under high-temperature conditions, characterized in that, The method includes the following steps: Intelligent sensors are used to collect voltage data and vibration acceleration of the high-temperature power supply in real time, and to obtain temperature data at the start time of each preset time period, which is used as the temperature data for each time period. By comparing the average distribution of all voltage data in each time period with the difference between the preset rated output voltage of the high-temperature power supply, the voltage offset value of each time period is determined; by combining the difference between the voltage offset value and the temperature data in all time periods within the preset time period before each moment, and the fusion result of the voltage offset value of all time periods, the first fault factor of the high-temperature power supply at each moment is determined. The system acquires the spectral sequence of all voltage data above a preset switching frequency in the frequency domain within each time period. It then determines the high-frequency ripple energy of the high-temperature power supply at each time period by considering the modulus of all elements in the spectral sequence. Based on the distribution of all vibration accelerations within each time period, it determines the vibration characteristic value of the high-temperature power supply at each time period. Based on all voltage data within each time period, it obtains the ripple coefficient for each time period. Within a preset time period before each moment, it analyzes the average distribution of high-frequency ripple energy across all time periods to determine the energy distribution value of the high-temperature power supply at each moment. Finally, it combines the similarity between the vibration characteristic value and the ripple coefficient across all time periods to determine the second fault factor of the high-temperature power supply at each moment. The dispersion of temperature data for all time periods within a preset time period before each time point and the sum of vibration characteristic values ​​for all time periods are used as the weights of the first fault factor and the second fault factor, respectively, to determine the comprehensive fault factor of the high-temperature power supply at each time point, so as to monitor the working status of the high-temperature power supply. The expression for the first fault factor of the high-temperature power supply at each time point is: In the formula, This represents the first fault factor of the high-temperature power supply at time i. The DTW distance represents the difference between the normalized value of the voltage offset and the normalized value of the temperature data for all time periods within a preset time period before time i. This represents the cumulative sum of voltage deviation values ​​for all time periods within a preset duration prior to time i; The expression for the second fault factor of the high-temperature power supply at each time point is: In the formula, This represents the second fault factor of the high-temperature power supply at time i; This represents the similarity between the ripple coefficient and the vibration characteristic value across all time periods within a preset duration prior to time i. This represents the energy distribution value of the high-temperature power source at time i; This indicates a preset constant greater than 1.

2. The method for monitoring the operating status of a power supply under high-temperature conditions as described in claim 1, characterized in that, The voltage offset value for each time period is the difference between the average of all voltage data within each time period and the preset rated output voltage of the high-temperature power supply.

3. The method for monitoring the operating status of a power supply under high-temperature conditions as described in claim 1, characterized in that, The high-frequency ripple energy of the high-temperature power supply in each time period is the sum of the moduli of all elements in the spectral sequence of each time period.

4. The power supply operating status monitoring method under high temperature environment as described in claim 1, characterized in that, The vibration characteristic value of the high-temperature power supply in each time period is the mean square value of all vibration accelerations in each time period.

5. The power supply operating status monitoring method under high temperature environment as described in claim 1, characterized in that, The energy distribution value of the high-temperature power supply at each time point is the average value of the high-frequency ripple energy during all time periods within a preset time period prior to each time point.

6. The power supply operating status monitoring method under high temperature environment as described in claim 1, characterized in that, The expression for the comprehensive failure factor of the high-temperature power supply at each time point is: In the formula, The comprehensive failure factor of the high-temperature power supply at time i is represented. , These represent the dispersion of temperature data for all time periods within a preset time duration prior to time i, and the sum of vibration characteristic values ​​for all time periods, respectively. , Let i and i represent the first fault factor and the second fault factor of the high-temperature power supply at time i, respectively.

7. The method for monitoring the operating status of a power supply under high-temperature conditions as described in claim 1, characterized in that, The monitoring of the operating status of the high-temperature power supply includes: Each time period is used to form a monitoring window. Voltage data, vibration acceleration, and temperature data are acquired within a preset number of monitoring windows when the high-temperature power supply is working normally in oil and gas drilling. For each monitoring window, the comprehensive fault factor within a preset number of monitoring windows is acquired according to the method for acquiring the comprehensive fault factor. The maximum comprehensive fault factor is used as the fault threshold. If the comprehensive fault factor of the high-temperature power supply is greater than the fault threshold at the current time, the working state of the high-temperature power supply is abnormal at the current time. Otherwise, the working state of the high-temperature power supply is normal.

8. A high-temperature power supply, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the power supply operating status monitoring method under high temperature environment as described in any one of claims 1-7.

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