Emergency shutdown protection device and method for low liquid level of thin oil pump

Abstract

This invention provides a low-level emergency shutdown protection device and method for a thin oil pump, relating to the field of intelligent equipment control. The method includes: analyzing the impact of oil temperature sequences on oil performance to generate an oil performance influence coefficient; analyzing operating load sequences to obtain an oil consumption rate sequence; optimizing the oil level threshold based on an oil level detection device, according to the oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficient, to generate a corrected oil level threshold; compensating the corrected oil level threshold according to an oil level fluctuation tolerance ratio to obtain an adapted oil level threshold, and performing low-level emergency shutdown protection. This invention aims to solve the technical problem that traditional low-level detection methods for thin oil pumps cannot set matching oil level thresholds according to equipment operating conditions, resulting in insufficient accuracy in oil level judgment and thus affecting the accuracy and reliability of emergency shutdown protection. It can significantly improve the accuracy of oil level judgment and enhance the accuracy and reliability of emergency shutdown protection.

Description

Technical Field

[0001] This invention relates to the field of intelligent equipment control, and in particular to an emergency shutdown protection device and method for a thin oil pump at low liquid level. Background Technology

[0002] In the operation of thin oil pumps and other hydraulic systems, the normal supply of oil and accurate monitoring of oil level are crucial. Thin oil pumps are generally used in equipment under high load and high temperature conditions, and are widely used in large machinery, engines, generator sets, and other equipment. Their main function is to reduce friction, improve system operating efficiency, and extend equipment life by providing lubricating oil.

[0003] Traditional low-level detection methods are usually based on a set oil level threshold. These methods mostly use mechanical oil level detectors or static oil level sensors, which simply determine whether the oil level has reached the set standard by detecting the physical height of the oil in the tank. They do not take into account the actual operating conditions of the equipment (such as load, temperature, oil consumption, etc.) on the oil consumption, resulting in insufficient accuracy of oil level judgment, which in turn affects the accuracy and reliability of emergency shutdown protection. Summary of the Invention

[0004] The purpose of this invention is to provide a low-level emergency shutdown protection device and method for a thin oil pump, which solves the technical problem that traditional low-level detection methods for thin oil pumps cannot set a matching oil level threshold according to the equipment's operating conditions, resulting in insufficient accuracy in oil level judgment and thus affecting the accuracy and reliability of emergency shutdown protection. The invention includes:

[0005] In a first aspect, the present invention provides a low-level emergency shutdown protection device for a thin oil pump, comprising: a data monitoring module for continuously monitoring the engine's operating temperature, operating load, and the oil temperature in the thin oil pump tank, generating an operating temperature sequence, an operating load sequence, and an oil temperature sequence; a performance impact analysis module for performing oil performance impact analysis based on the oil temperature sequence, generating an oil performance impact coefficient; an oil consumption rate analysis module for analyzing and obtaining an oil consumption rate sequence based on the operating load sequence; an oil level threshold optimization module for optimizing the oil level threshold based on an oil level detection device, the oil consumption rate sequence, the operating temperature sequence, and the oil performance impact coefficient, generating a corrected oil level threshold; and a low-level shutdown protection module for pre-compensating the corrected oil level threshold according to an oil level fluctuation tolerance ratio to obtain an adapted oil level threshold, and performing low-level emergency shutdown protection in conjunction with the oil level detection device.

[0006] Preferably, the thin oil pump low-level emergency shutdown protection device further includes: a continuous monitoring unit, used to continuously monitor the engine's operating temperature, operating load, and thin oil pump tank temperature using a sensing monitoring device during engine operation, to obtain K operating temperatures, K operating loads, and K oil temperatures at K continuous monitoring time points, where K is an integer greater than 10; and a data sorting unit, used to sort the K operating temperatures, K operating loads, and K oil temperatures respectively to construct an operating temperature sequence, an operating load sequence, and an oil temperature sequence.

[0007] Preferably, the low-level emergency shutdown protection device for a thin oil pump further includes: an oil temperature prediction unit, used to perform oil temperature rise fitting analysis based on the oil temperature sequence, obtain the oil temperature rise rate, and predict the predicted oil temperature at the next monitoring time point; and a viscosity influence analysis unit, used to calculate the average value of the end oil temperature and the predicted oil temperature in the oil temperature sequence, and perform oil viscosity influence analysis based on the average temperature value, and output the oil performance influence coefficient.

[0008] Preferably, the low-level emergency shutdown protection device for a thin oil pump further includes: a data processing unit, used to collect multiple sample operating loads and multiple sample oil consumption rates within a preset time range, and perform noise removal and standardization processing to obtain a standard sample operating load set and a standard sample oil consumption rate set; a load-oil analysis unit, used to analyze the standard sample operating load set and the standard sample oil consumption rate set to construct a load-oil analysis model, wherein the load-oil analysis model is a linear regression model; and an oil consumption rate obtaining unit, used to use the load-oil analysis model to analyze and obtain an oil consumption rate sequence based on the operating load sequence.

[0009] Preferably, the low-level emergency shutdown protection device for a thin oil pump further includes: a detection device configuration unit for configuring an oil level detection device, wherein the oil level detection device includes a float-type oil level switch and a capacitive oil level sensor; a detection feedback duration acquisition unit for analyzing and acquiring the detection feedback duration based on the oil level detection device; an oil level drop prediction unit for predicting the oil level drop based on the detection feedback duration, oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficient, and outputting the predicted drop oil level; and a correction oil level threshold acquisition unit for summing the standard oil level threshold and the predicted drop oil level to obtain the correction oil level threshold.

[0010] Preferably, the low-level emergency shutdown protection device for a thin oil pump further includes: a duration statistics channel, used to separately count historical detection data of the float-type oil level switch and the capacitive oil level sensor within a preset time range, and calculate the average float detection duration, the average capacitive detection duration, the average data fusion duration, and the average feedback consumption duration; an expected detection duration setting channel, used to set the larger value between the average float detection duration and the average capacitive detection duration as the expected detection duration; and a detection feedback duration acquisition channel, used to sum the expected detection duration, the average data fusion duration, and the average feedback consumption duration to obtain the detection feedback duration.

[0011] Preferably, the low-level emergency shutdown protection device for a thin oil pump further includes: a data retrieval channel for retrieving historical operating data of similar thin oil pumps, collecting sample oil consumption rate sequence sets, sample operating temperature sequence sets, and sample oil performance influence coefficient sets, and statistically analyzing the oil level decrease after the same historical time interval of different sample oil consumption rate sequences, sample operating temperature sequences, and sample oil performance influence coefficients, to obtain a sample oil level decrease set; a model training channel for training a BP neural network using the sample oil consumption rate sequence set, sample operating temperature sequence set, sample oil performance influence coefficient set, and sample oil level decrease set until convergence, to obtain an oil level decrease prediction model; and an oil level decrease prediction channel for using the oil level decrease prediction model to predict the oil level decrease based on the oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficients, and outputting the predicted oil level decrease.

[0012] Preferably, the low-level emergency shutdown protection device for a thin oil pump further includes: a fluctuation coefficient mean calculation unit, used to retrieve historical operating data of similar thin oil pumps, obtain multiple sample oil level fluctuation coefficients, and calculate the mean of the sample oil level fluctuation coefficients; a deviation analysis unit, used to perform deviation analysis on the multiple sample oil level fluctuation coefficients based on the mean of the sample oil level fluctuation coefficients, and obtain the deviation ratio of the multiple sample oil level fluctuation coefficients; a fluctuation tolerance ratio obtaining unit, used to select sample oil level fluctuation coefficients with deviation ratios less than a deviation threshold as qualified sample oil level fluctuation coefficients, calculate the mean of multiple qualified sample oil level fluctuation coefficients, and obtain the oil level fluctuation tolerance ratio; and an adaptation oil level threshold obtaining unit, used to set the ratio of the correction oil level threshold to the difference between 1 and the oil level fluctuation tolerance ratio as the adaptation oil level threshold.

[0013] Preferably, the low-level emergency shutdown protection device for a thin oil pump further includes: a physical property acquisition unit, used to acquire the physical properties of the oil in the thin oil pump tank, wherein the physical properties include viscosity, impurity ratio, bubble ratio, and conductivity; a detection error analysis unit, used to retrieve historical operating data of similar thin oil pumps based on the physical properties, and perform detection error analysis on the float-type oil level switch and the capacitive oil level sensor respectively, to obtain the average detection error of the float and the average detection error of the capacitor; a reliable weight ratio configuration unit, used to configure a reliable weight ratio based on the average detection error of the float and the average detection error of the capacitor, wherein the reliable weight is negatively correlated with the average detection error; and a shutdown protection unit, used to perform real-time detection and feedback of the oil in the thin oil pump tank using the oil level detection device according to the reliable weight ratio, and to perform low-level emergency shutdown protection if the oil level detection data is less than or equal to the adapted oil level threshold.

[0014] Secondly, the present invention also provides a method for emergency shutdown protection of a thin oil pump at low liquid level, comprising: continuously monitoring the engine's operating temperature, operating load, and the oil temperature in the thin oil pump tank to generate an operating temperature sequence, an operating load sequence, and an oil temperature sequence; performing an oil performance influence analysis based on the oil temperature sequence to generate an oil performance influence coefficient; analyzing the oil consumption rate sequence based on the operating load sequence to obtain an oil consumption rate sequence; optimizing the oil level threshold based on an oil level detection device, according to the oil consumption rate sequence, the operating temperature sequence, and the oil performance influence coefficient, to generate a corrected oil level threshold; pre-compensating the corrected oil level threshold according to the oil level fluctuation tolerance ratio to obtain an adapted oil level threshold, and performing emergency shutdown protection at low liquid level in conjunction with the oil level detection device.

[0015] The embodiments of the present invention have the following advantages:

[0016] By collecting the physical properties of the oil in the thin oil pump tank, including viscosity, impurity ratio, bubble ratio, and conductivity, and then using these physical properties as constraints, historical operating data of similar thin oil pumps are retrieved. Detection error analysis is performed on both float-type and capacitive-type oil level sensors to obtain the average detection error of the float and the average detection error of the capacitor. Then, a reliable weight is configured based on the average detection error of the float and the average detection error of the capacitor, where the reliable weight is negatively correlated with the average detection error. Finally, the oil level detection device is used to monitor and provide feedback on the oil in the thin oil pump tank in real time. If the oil level detection data is less than or equal to the adapted oil level threshold, a low-level emergency shutdown protection is initiated. In other words, by integrating data monitoring, performance analysis, and oil consumption analysis, the oil level threshold can be dynamically optimized according to the actual operating status of the equipment, thereby significantly improving the accuracy of oil level judgment, enhancing the accuracy and reliability of emergency shutdown protection, and reducing the risk of equipment failure. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure of an emergency shutdown protection device for a low liquid level in a thin oil pump according to the present invention.

[0018] Figure 2 This is a flowchart illustrating the steps of an emergency shutdown protection method for a low liquid level in a thin oil pump according to the present invention.

[0019] Explanation of reference numerals in the attached figures:

[0020] Data monitoring module 11, performance impact analysis module 12, oil consumption rate analysis module 13, oil level threshold optimization module 14, and low liquid level shutdown protection module 15. Detailed Implementation

[0021] This invention provides a low-level emergency shutdown protection device and method for thin oil pumps, solving the technical problem that traditional low-level detection methods for thin oil pumps cannot set matching oil level thresholds according to equipment operating conditions, resulting in insufficient accuracy in oil level judgment and consequently affecting the accuracy and reliability of emergency shutdown protection. By integrating data monitoring, performance analysis, and oil consumption analysis, the oil level threshold can be dynamically optimized according to the actual operating status of the equipment, thereby significantly improving the accuracy of oil level judgment, enhancing the accuracy and reliability of emergency shutdown protection, and reducing the risk of equipment failure.

[0022] The technical solutions of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. It should be understood that the present invention is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. It should also be noted that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, not all of them.

[0023] Example 1, please refer to the appendix. Figure 1 This invention provides an emergency shutdown protection device for a thin oil pump at low liquid level, comprising:

[0024] The data monitoring module 11 is used to continuously monitor the engine's operating temperature, operating load, and the oil temperature of the thin oil pump tank, and generate operating temperature sequence, operating load sequence, and oil temperature sequence.

[0025] Furthermore, the data monitoring module 11 also includes:

[0026] The continuous monitoring unit is used to continuously monitor the engine's operating temperature, operating load, and oil temperature of the thin oil pump tank using sensing monitoring equipment during engine operation, obtaining K operating temperatures, K operating loads, and K oil temperatures at K continuous monitoring time points, where K is an integer greater than 10; the data sorting unit is used to sort the K operating temperatures, K operating loads, and K oil temperatures respectively to construct operating temperature sequences, operating load sequences, and oil temperature sequences.

[0027] Specifically, during engine operation, sensing and monitoring devices (such as temperature sensors and load sensors) are used to continuously monitor the engine's operating temperature, operating load, and the oil temperature in the thin oil pump tank. Multiple data points (K consecutive monitoring time points) are collected and sorted chronologically to construct a continuous sequence of operating temperature, operating load, and oil temperature, resulting in an operating temperature sequence, an operating load sequence, and an oil temperature sequence. This process helps to more accurately analyze and adjust the oil condition, thereby improving the accuracy and reliability of oil level determination.

[0028] The performance impact analysis module 12 is used to perform oil performance impact analysis based on the oil temperature sequence and generate oil performance impact coefficients.

[0029] Furthermore, the performance impact analysis module 12 also includes:

[0030] The oil temperature prediction unit is used to perform oil temperature rise fitting analysis based on the oil temperature sequence, obtain the oil temperature rise rate, and predict the predicted oil temperature at the next monitoring time point; the viscosity influence analysis unit is used to calculate the average value of the end oil temperature and the predicted oil temperature in the oil temperature sequence, and perform oil viscosity influence analysis based on the average temperature value, and output the oil performance influence coefficient.

[0031] Specifically, an oil temperature rise fitting analysis is performed based on the oil temperature sequence. Through fitting (such as linear fitting, exponential fitting, or other curve fitting methods), the trend of oil temperature change over time is analyzed, and the oil temperature rise rate is calculated. The temperature rise rate represents the rate at which the oil temperature rises per unit time, usually expressed in °C / unit of time. The goal of the fitting analysis is to obtain the pattern of temperature change, thus enabling the prediction of future oil temperatures. Then, based on the current oil temperature sequence, the oil temperature at the next time point is predicted. This process involves extrapolating existing temperature data to obtain a predicted future oil temperature value. This predicted value represents the expected temperature of the oil at a future time, providing a reference for oil performance evaluation and adjustment.

[0032] Next, the mean of the end temperature and the predicted temperature in the oil temperature sequence is calculated. The end temperature in the oil temperature sequence refers to the actual oil temperature recorded at the current time point. This mean temperature represents the overall temperature state of the oil at the current and future times. Then, the influence of oil viscosity is analyzed based on the mean temperature. Oil viscosity refers to the resistance to flow within the oil. An increase in temperature will lead to a decrease in oil viscosity because the molecular activity of the oil is more intense at high temperatures, and the interaction forces between molecules are weakened, resulting in a decrease in oil viscosity. There is a certain empirical relationship between oil viscosity and temperature (such as the Arrhenius equation), that is, when the temperature increases, the viscosity of the oil decreases. Based on the mean of the actual and predicted oil temperatures, the change in oil viscosity is calculated using the empirical relationship between viscosity and temperature, and an oil performance influence coefficient is obtained. This coefficient describes the effect of temperature change on oil performance (especially lubrication performance and fluidity). For example, a 2% decrease in viscosity indicates the degree to which oil performance is affected by temperature change. The larger the coefficient, the more significant the effect of oil temperature change on performance.

[0033] The oil consumption rate analysis module 13 is used to analyze the oil consumption rate sequence based on the operating load sequence.

[0034] Furthermore, the oil consumption rate analysis module 13 also includes:

[0035] The data processing unit is used to collect multiple sample operating loads and multiple sample oil consumption rates within a preset time range, and perform noise removal and standardization processing to obtain a standard sample operating load set and a standard sample oil consumption rate set; the load-oil analysis unit is used to analyze the standard sample operating load set and the standard sample oil consumption rate set to construct a load-oil analysis model, wherein the load-oil analysis model is a linear regression model; the oil consumption rate obtaining unit is used to obtain an oil consumption rate sequence based on the operating load sequence using the load-oil analysis model.

[0036] Specifically, firstly, historical operating data of similar thin oil pumps are retrieved, and multiple sample operating loads and multiple sample oil consumption rates are collected within a preset time range (e.g., the most recent month). Operating load refers to the actual load borne by the equipment during operation, usually expressed as a percentage or power; oil consumption rate is usually expressed as oil volume / time (e.g., liters / hour), reflecting the rate at which oil is used during equipment operation. Next, noise removal and standardization are performed on the multiple sample operating loads and multiple sample oil consumption rates. Since various interferences (such as sensor errors, changes in environmental factors, etc.) may occur during data acquisition, noise is present in the data, and therefore needs to be removed. Common noise removal methods include moving average, median filtering, and signal filtering; standardization is to eliminate the influence of data units, ensuring that different sample data have the same units and a balanced range, facilitating analysis. After noise removal and standardization, two standardized datasets are obtained: a standard sample operating load set and a standard sample oil consumption rate set.

[0037] Then, the standard sample operating load set and the standard sample oil consumption rate set are used for analysis. By analyzing the relationship between the standardized operating load and oil consumption rate, a linear regression model is constructed to describe their relationship. The dataset is used for regression training, and the model's fit is evaluated to construct a load-oil analysis model, in which operating load and oil consumption rate are positively correlated, i.e., the higher the operating load, the higher the oil consumption rate. Finally, the operating load sequence is input into the load-oil analysis model for analysis to obtain the corresponding oil consumption rate sequence.

[0038] The oil level threshold optimization module 14 is used to optimize the oil level threshold based on the oil level detection device, the oil consumption rate sequence, the operating temperature sequence, and the oil performance influence coefficient, and generate a corrected oil level threshold.

[0039] Furthermore, the oil level threshold optimization module 14 also includes:

[0040] The detection device configuration unit is used to configure the oil level detection device, which includes a float-type oil level switch and a capacitive oil level sensor.

[0041] Specifically, an oil level detection device is configured, which includes a float-type oil level switch and a capacitive oil level sensor. The float-type oil level switch is a common oil level monitoring device, operating on the principle of buoyancy. Its main components include a float and a switching mechanism. The float is typically a sealed and lightweight structure that floats with changes in oil level. When the oil level rises, the float rises as well. If the oil level exceeds the set height, the float triggers the switch, sending a signal indicating that the oil level is too high or too low. When the oil level drops, the float sinks, triggering the switch and providing a signal indicating that the oil level is too low. The capacitive oil level sensor is a more accurate oil level detection device, operating on the principle of capacitance. A capacitor consists of two conductors and an insulating medium in between. In a capacitive oil level sensor, the oil acts as the medium, and the capacitance between the oil and the electrodes changes with the oil level. A typical capacitive oil level sensor has two electrodes filled with oil. Changes in oil level directly affect the capacitance between the electrodes; this change in capacitance is converted into an electrical signal by the sensor, which is then used by the control system to display the oil level in real time. In this way, capacitive sensors can measure oil levels very accurately. Depending on specific needs (such as accuracy requirements and operating environment), these two different types of oil level detection devices can be combined for use.

[0042] The detection feedback duration acquisition unit is used to analyze and acquire the detection feedback duration based on the oil level detection device.

[0043] Furthermore, the detection feedback duration acquisition unit also includes:

[0044] The duration statistics channel is used to statistically analyze historical detection data of float-type oil level switches and capacitive oil level sensors within a preset time range, and calculate the average detection duration of float, average detection duration of capacitor, average data fusion duration, and average feedback consumption duration. The expected detection duration setting channel is used to set the larger of the average detection duration of float and average detection duration of capacitor as the expected detection duration. The detection feedback duration acquisition channel is used to sum the expected detection duration, the average data fusion duration, and the average feedback consumption duration to obtain the detection feedback duration.

[0045] Specifically, historical detection data of float-type oil level switches and capacitive oil level sensors for similar thin oil pumps within a preset time range (e.g., the most recent month) are collected. Then, based on the historical detection data, the following are calculated: average float detection time (average duration of each detection operation for float-type oil level switches), average capacitive detection time (average duration of each detection operation for capacitive oil level sensors), average data fusion time (in the case of multiple oil level detection devices, data from multiple sensors needs to be fused; data fusion time represents the time required from data acquisition to data synthesis. This time depends on the complexity of data processing and the efficiency of the algorithm), and average feedback consumption time (feedback consumption time refers to the time required from the generation of the detection result to the final feedback to the control system, including signal transmission, calculation, and response time).

[0046] Next, the average values ​​of the two detection methods are compared, and the larger value is selected as the expected detection time of the system. This ensures that a longer detection time is used as the standard to accommodate possible delays. Finally, the expected detection time, the average data fusion time, and the average feedback consumption time are summed to obtain the detection feedback time. The detection feedback time represents the total time from the start of detection to the completion of feedback, and it can be used to evaluate the timeliness of the entire oil level detection process.

[0047] The oil level drop prediction unit is used to predict the oil level drop based on the detection feedback time, oil consumption rate sequence, operating temperature sequence and oil performance influence coefficient, and output the predicted oil level drop.

[0048] Furthermore, the oil level drop prediction unit also includes:

[0049] The data retrieval channel is used to retrieve historical operating data of similar thin oil pumps, collect sample oil consumption rate sequence sets, sample operating temperature sequence sets, and sample oil performance influence coefficient sets, and statistically analyze the oil level decrease after the same historical time interval of the detection feedback duration for different sample oil consumption rate sequences, sample operating temperature sequences, and sample oil performance influence coefficients to obtain a sample oil level decrease set; the model training channel is used to train a BP neural network using the sample oil consumption rate sequence set, sample operating temperature sequence set, sample oil performance influence coefficient set, and sample oil level decrease set until convergence, to obtain an oil level decrease prediction model; the oil level decrease prediction channel is used to use the oil level decrease prediction model to predict the oil level decrease based on the oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficients, and output the predicted oil level decrease.

[0050] Specifically, firstly, historical operating data of thin oil pumps of the same model or operating principle as the current thin oil pump are retrieved. This historical data includes a large amount of sensor data, covering information such as oil consumption rate, operating temperature, and oil performance influence coefficients during multiple runs. Next, sample oil consumption rate sequences, sample operating temperature sequences, and sample oil performance influence coefficient sets are collected. Then, the oil level decrease after the same historical time interval for different sample oil consumption rate sequences, sample operating temperature sequences, and sample oil performance influence coefficients is statistically analyzed. To ensure the comparability of the results, the data must be analyzed within the same historical time interval to obtain a sample oil level decrease set.

[0051] Backpropagation (BP) neural networks are a common type of feedforward neural network. Their training optimizes network weights through backpropagation. First, an oil level drop prediction model is constructed based on the BP neural network. This model is an iteratively optimized BP neural network model used in machine learning, consisting of an input layer, multiple hidden layers, and an output layer. The input layer receives oil consumption rate sequences, operating temperature sequences, and oil performance influence coefficients as feature inputs. These features reflect the key factors affecting oil consumption and oil level changes. The target output is the amount of oil level drop, i.e., predicting the change in oil level through the input features. Further, using the sample oil consumption rate sequence, sample operating temperature sequence, and sample oil performance influence coefficient as inputs, and the sample oil level drop as supervision, the oil level drop prediction model is trained under supervision using the sample oil consumption rate sequence set, sample operating temperature sequence set, sample oil performance influence coefficient set, and sample oil level drop set. The key step in the training process is to adjust the network weights through error backpropagation. The error is the difference between the predicted oil level drop and the actual oil level drop. The network continuously adjusts the weights to make the output value gradually approach the actual value, such as using gradient descent or Adam optimization algorithms. The network is optimized by minimizing the loss function (such as mean squared error). The training process continues until the network error converges, indicating that the model has learned the relationship between the input features and the oil level drop, resulting in a successfully trained oil level drop prediction model.

[0052] Finally, the oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficient are input into the oil level drop prediction model to predict the oil level drop, and the predicted drop oil level is output. By training and constructing the oil level drop prediction model using a BP neural network, the oil level drop can be accurately predicted using the oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficient, significantly improving the accuracy and efficiency of oil level drop prediction.

[0053] The corrected oil level threshold acquisition unit is used to sum the standard oil level threshold and the predicted drop in oil level to obtain the corrected oil level threshold.

[0054] Specifically, the standard oil level threshold is typically a preset value set according to the equipment's design and operating conditions. It is used to determine whether the oil level has reached the safe operating range. During equipment operation, it serves as a baseline safety threshold for the oil level. For example, it can be set to 70% of the oil level, indicating that a warning will be issued or protective measures will be taken when the oil level drops to this level. The standard oil level threshold and the predicted oil level drop are then summed, and the sum is used as a correction oil level threshold. This correction threshold dynamically adjusts the oil level monitoring standard during actual operation to adapt to the current operating state of the equipment.

[0055] By adding the standard oil level threshold to the predicted oil level drop, the corrected oil level threshold is obtained. This method not only takes into account the historical design and standard values ​​of the equipment, but also dynamically reflects the status of the equipment in actual operation. It can more accurately determine the oil level and ensure that the equipment operates stably within a safe range. This method improves the intelligence of the oil level monitoring system, enabling it to flexibly respond to changes under different operating conditions and provide more accurate and reliable emergency shutdown protection.

[0056] The low liquid level shutdown protection module 15 is used to pre-compensate the corrected oil level threshold according to the oil level fluctuation tolerance ratio to obtain an adapted oil level threshold, and to perform low liquid level emergency shutdown protection in conjunction with the oil level detection device.

[0057] Furthermore, the low liquid level shutdown protection module 15 also includes:

[0058] The unit calculates the average fluctuation coefficient, which retrieves historical operating data of similar thin oil pumps, obtains multiple sample oil level fluctuation coefficients, and calculates the average of the sample oil level fluctuation coefficients. The unit performs deviation analysis on the multiple sample oil level fluctuation coefficients based on the average of the sample oil level fluctuation coefficients, obtaining the deviation ratio of the multiple sample oil level fluctuation coefficients. The unit obtains the fluctuation tolerance ratio, which filters sample oil level fluctuation coefficients with deviation ratios less than a deviation threshold as qualified sample oil level fluctuation coefficients, calculates the average of multiple qualified sample oil level fluctuation coefficients, and obtains the oil level fluctuation tolerance ratio. The unit obtains the adaptive oil level threshold, which sets the ratio of the corrected oil level threshold to the difference between 1 and the oil level fluctuation tolerance ratio as the adaptive oil level threshold.

[0059] Specifically, firstly, historical operating data of similar thin oil pumps are retrieved to collect oil level fluctuation data during operation of different equipment. This data records the changes in oil level over different time periods, reflecting the amplitude of oil level fluctuations. The oil level fluctuation coefficient of each equipment represents the relative degree of oil level fluctuation. Multiple sample oil level fluctuation coefficients are obtained, and their average values ​​are calculated to obtain the mean value of the sample oil level fluctuation coefficients. Next, using the mean value of the sample oil level fluctuation coefficients as a benchmark, deviation analysis is performed on the multiple sample oil level fluctuation coefficients to calculate the deviation ratio. This deviation ratio represents the relative difference between each sample oil level fluctuation coefficient and the mean value, reflecting the stability of oil level fluctuations. Then, sample oil level fluctuation coefficients with deviation ratios less than the deviation threshold (set empirically or determined according to the actual requirements of the equipment) are selected as qualified sample oil level fluctuation coefficients. Qualified sample oil level fluctuation coefficients have higher stability, representing equipment or operating conditions with relatively regular oil level fluctuations. Finally, the mean value of multiple qualified sample oil level fluctuation coefficients is calculated to obtain the oil level fluctuation tolerance ratio, i.e., the average level of qualified sample oil level fluctuation coefficients. This ratio reflects the allowable range of oil level fluctuations during equipment operation.

[0060] Finally, the ratio of the corrected oil level threshold to the difference between 1 and the oil level fluctuation tolerance ratio is calculated to obtain the adapted oil level threshold. This adapted oil level threshold is dynamically adjusted based on the actual oil level fluctuations, thus preventing unnecessary alarms or shutdowns caused by excessive oil level fluctuations. By analyzing and screening the deviation of the oil level fluctuation coefficient, the oil level fluctuation tolerance ratio is calculated and combined with the corrected oil level threshold to obtain the adapted oil level threshold. This allows for dynamic adjustment of the oil level warning line during equipment operation. This method not only improves the accuracy of oil level judgment but also avoids overreaction in cases of large oil level fluctuations, thereby improving equipment operating efficiency and safety.

[0061] Furthermore, the low liquid level shutdown protection module 15 also includes:

[0062] The system includes a physical property acquisition unit for acquiring the physical properties of the oil in the thin oil pump tank, including viscosity, impurity ratio, bubble ratio, and conductivity; a detection error analysis unit for retrieving historical operating data of similar thin oil pumps based on the physical properties, and performing detection error analysis on the float-type oil level switch and the capacitive oil level sensor to obtain the average detection error of the float and the average detection error of the capacitor; a trusted weight allocation configuration unit for configuring a trusted weight allocation based on the average detection error of the float and the average detection error of the capacitor, wherein the trusted weight is negatively correlated with the average detection error; and a shutdown protection unit for real-time detection and feedback of the oil in the thin oil pump tank using the oil level detection device based on the trusted weight allocation. If the oil level detection data is less than or equal to the adapted oil level threshold, an emergency shutdown protection is performed for low liquid level.

[0063] Specifically, firstly, the physical properties of the oil in the thin oil pump tank are collected. These physical properties include viscosity, impurity ratio, bubble ratio, and conductivity. Viscosity affects the resistance to oil flow; higher viscosity may lead to poor oil flow, thus affecting the monitoring of oil level changes. Impurities may affect the conductivity or resistance of the oil, thereby interfering with the detection accuracy of the oil level sensor. The presence of bubbles may cause changes in oil density, affecting the fluidity of the oil and thus affecting the reading of the oil level sensor. Conductivity affects the working principle of capacitive oil level sensors, because capacitive sensors rely on the conductivity of the oil to sense the oil level. By collecting these physical parameters in real time, basic data can be provided for subsequent detection error analysis.

[0064] Next, using the aforementioned physical properties as constraints, historical operating data of similar thin oil pumps are retrieved. This historical operating data provides information on the actual performance of the equipment under different operating conditions. Then, based on the historical operating data, detection error analysis is performed on float-type oil level switches and capacitive oil level sensors to obtain the average detection error of the float and the average detection error of the capacitive sensor. That is, for each type of oil level monitoring device, the average detection error under the same oil conditions is calculated. This average error reflects the average error of the equipment under different operating conditions, helping to assess the reliability of the equipment.

[0065] Then, a reliability weight ratio is configured based on the average float detection error and the average capacitor detection error. The reliability weight is used to quantify the reliability of different oil level detection devices and reflect the reliability of each device under specific conditions. The reliability weight is allocated based on the average detection error of the device. The reliability weight is negatively correlated with the average detection error, that is, the smaller the error, the higher the reliability of the device and the greater the weight given; conversely, devices with larger errors will be given lower weights.

[0066] Finally, the oil level detection device is used to monitor the oil level in the thin oil pump tank in real time. Then, based on the weight ratio of the reliable weight, the weight of each detection device is dynamically adjusted according to the average error of each device. That is, when judging the oil level, the device with the smaller error is given a higher weight. The weighted oil level detection data is obtained and fed back. If the oil level detection data is less than or equal to the adapted oil level threshold, the low liquid level emergency shutdown protection is performed. The low liquid level emergency shutdown protection is to prevent the thin oil pump from running dry or overheating due to the oil level being too low, thereby avoiding equipment damage.

[0067] By dynamically adjusting the reliability weight of the oil level detection equipment, combined with real-time monitored oil level data and an appropriate oil level threshold, it is possible to more accurately determine oil level changes and automatically trigger low-level emergency shutdown protection when the oil level is too low, ensuring the normal operation and safety of equipment such as thin oil pumps.

[0068] In summary, the low-level emergency shutdown protection device for a thin oil pump provided by this invention has the following technical effects:

[0069] By collecting the physical properties of the oil in the thin oil pump tank, including viscosity, impurity ratio, bubble ratio, and conductivity, and then using these physical properties as constraints, historical operating data of similar thin oil pumps are retrieved. Detection error analysis is performed on both float-type and capacitive-type oil level sensors to obtain the average detection error of the float and the average detection error of the capacitor. Then, a reliable weight is configured based on the average detection error of the float and the average detection error of the capacitor, where the reliable weight is negatively correlated with the average detection error. Finally, the oil level detection device is used to monitor and provide feedback on the oil in the thin oil pump tank in real time. If the oil level detection data is less than or equal to the adapted oil level threshold, a low-level emergency shutdown protection is initiated. In other words, by integrating data monitoring, performance analysis, and oil consumption analysis, the oil level threshold can be dynamically optimized according to the actual operating status of the equipment, thereby significantly improving the accuracy of oil level judgment, enhancing the accuracy and reliability of emergency shutdown protection, and reducing the risk of equipment failure.

[0070] Example 2: Based on the same inventive concept as the low-level emergency shutdown protection device for a thin oil pump in the previous examples, this invention also provides a low-level emergency shutdown protection method for a thin oil pump. Please refer to the appendix. Figure 2 This includes: continuously monitoring the engine's operating temperature, operating load, and the oil temperature in the thin oil pump tank to generate operating temperature, operating load, and oil temperature sequences; performing oil performance impact analysis based on the oil temperature sequences to generate oil performance impact coefficients; analyzing the oil consumption rate sequence based on the operating load sequence to obtain an oil consumption rate sequence; optimizing the oil level threshold based on the oil level detection device, the oil consumption rate sequence, operating temperature sequence, and oil performance impact coefficients to generate a corrected oil level threshold; pre-compensating the corrected oil level threshold according to the oil level fluctuation tolerance ratio to obtain an adapted oil level threshold; and combining the oil level detection device to perform low-level emergency shutdown protection.

[0071] Furthermore, the method for emergency shutdown protection of a thin oil pump at low liquid level also includes: during engine operation, using a sensing and monitoring device to continuously monitor the engine's operating temperature, operating load, and oil temperature in the thin oil pump tank, obtaining K operating temperatures, K operating loads, and K oil temperatures at K consecutive monitoring time points, where K is an integer greater than 10; sorting the K operating temperatures, K operating loads, and K oil temperatures respectively to construct an operating temperature sequence, an operating load sequence, and an oil temperature sequence.

[0072] Furthermore, the method for emergency shutdown protection of a thin oil pump at low liquid level also includes: performing an oil temperature rise fitting analysis based on the oil temperature sequence to obtain the oil temperature rise rate and predicting the predicted oil temperature at the next monitoring time point; calculating the mean of the end oil temperature and the predicted oil temperature in the oil temperature sequence, and performing an oil viscosity influence analysis based on the mean temperature to output the oil performance influence coefficient.

[0073] Furthermore, the method for emergency shutdown protection of a thin oil pump at low liquid level also includes: collecting multiple sample operating loads and multiple sample oil consumption rates within a preset time range, and performing noise removal and standardization processing to obtain a standard sample operating load set and a standard sample oil consumption rate set; using the standard sample operating load set and the standard sample oil consumption rate set for analysis to construct a load-oil analysis model, wherein the load-oil analysis model is a linear regression model; using the load-oil analysis model, an oil consumption rate sequence is obtained based on the operating load sequence.

[0074] Furthermore, the method for emergency shutdown protection of a thin oil pump at low liquid level also includes: configuring an oil level detection device, wherein the oil level detection device includes a float-type oil level switch and a capacitive oil level sensor; analyzing and obtaining the detection feedback time based on the oil level detection device; predicting the oil level drop based on the detection feedback time, oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficient, and outputting the predicted drop oil level; summing the standard oil level threshold and the predicted drop oil level to obtain the corrected oil level threshold.

[0075] Furthermore, the method for emergency shutdown protection of a thin oil pump at low liquid level also includes: statistically analyzing historical detection data of the float-type oil level switch and the capacitive oil level sensor within a preset time range, calculating the average float detection time, the average capacitive detection time, the average data fusion time, and the average feedback consumption time; setting the larger of the average float detection time and the average capacitive detection time as the expected detection time; and summing the expected detection time, the average data fusion time, and the average feedback consumption time to obtain the detection feedback time.

[0076] Furthermore, the method for emergency shutdown protection of a thin oil pump at low liquid level also includes: retrieving historical operating data of similar thin oil pumps, collecting a sample oil consumption rate sequence set, a sample operating temperature sequence set, and a sample oil performance influence coefficient set, and statistically analyzing the oil level decrease after the same historical time interval of the detection feedback duration for different sample oil consumption rate sequences, sample operating temperature sequences, and sample oil performance influence coefficients, to obtain a sample oil level decrease set; using the sample oil consumption rate sequence set, sample operating temperature sequence set, sample oil performance influence coefficient set, and sample oil level decrease set, training a BP neural network until convergence to obtain an oil level decrease prediction model; using the oil level decrease prediction model, predicting the oil level decrease based on the oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficient, and outputting the predicted oil level decrease.

[0077] Furthermore, the method for emergency shutdown protection of a thin oil pump at low liquid level further includes: retrieving historical operating data of similar thin oil pumps to obtain multiple sample oil level fluctuation coefficients, and calculating the average value of the sample oil level fluctuation coefficients; using the average value of the sample oil level fluctuation coefficients as a benchmark, performing deviation analysis on the multiple sample oil level fluctuation coefficients to obtain the deviation ratio of the multiple sample oil level fluctuation coefficients; selecting the sample oil level fluctuation coefficients with deviation ratios less than a deviation threshold as qualified sample oil level fluctuation coefficients, calculating the average value of multiple qualified sample oil level fluctuation coefficients to obtain the oil level fluctuation tolerance ratio; and setting the ratio of the correction oil level threshold to the difference between 1 and the oil level fluctuation tolerance ratio as the adaptation oil level threshold.

[0078] Furthermore, the method for emergency shutdown protection of a thin oil pump at low liquid level also includes: collecting the physical properties of the oil in the thin oil pump tank, wherein the physical properties include viscosity, impurity ratio, bubble ratio, and conductivity; using the physical properties as constraints, retrieving historical operating data of similar thin oil pumps, and performing detection error analysis on the float-type oil level switch and the capacitive oil level sensor respectively, to obtain the average detection error of the float and the average detection error of the capacitor; configuring a reliable weight ratio based on the average detection error of the float and the average detection error of the capacitor, wherein the reliable weight is negatively correlated with the average detection error; and using the oil level detection device to perform real-time detection and feedback on the oil in the thin oil pump tank according to the reliable weight ratio, and if the oil level detection data is less than or equal to the adapted oil level threshold, then performing emergency shutdown protection at low liquid level.

[0079] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. The emergency shutdown protection device and specific examples for a low-level thin oil pump in Embodiment 1 described above are also applicable to the emergency shutdown protection method for a low-level thin oil pump in this embodiment. Through the foregoing detailed description of the emergency shutdown protection device for a low-level thin oil pump, those skilled in the art can clearly understand the emergency shutdown protection method for a low-level thin oil pump in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here. As for the system disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and relevant parts can be referred to in the method section.

[0080] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0081] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of this invention and its equivalents, this invention also intends to include these modifications and variations.

Claims

1. A low-level emergency shutdown protection device for a thin oil pump, characterized in that, The low-level emergency shutdown protection device for the thin oil pump includes: The data monitoring module is used to continuously monitor the engine's operating temperature, operating load, and the oil temperature in the thin oil pump tank, generating operating temperature sequences, operating load sequences, and oil temperature sequences. The performance impact analysis module is used to perform oil performance impact analysis based on the oil temperature sequence and generate oil performance impact coefficients. The oil consumption rate analysis module is used to analyze the operating load sequence to obtain the oil consumption rate sequence. An oil level threshold optimization module is used to optimize the oil level threshold based on the oil level detection device, according to the oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficient, and generate a corrected oil level threshold. The oil level threshold optimization module includes: a detection device configuration unit for configuring the oil level detection device, which includes a float-type oil level switch and a capacitive oil level sensor; a detection feedback duration acquisition unit for analyzing and acquiring the detection feedback duration based on the oil level detection device; an oil level drop prediction unit for predicting the oil level drop based on the detection feedback duration, oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficient, and outputting the predicted drop oil level; and a corrected oil level threshold acquisition unit for summing the standard oil level threshold and the predicted drop oil level to obtain the corrected oil level threshold. The low liquid level shutdown protection module is used to pre-compensate the corrected oil level threshold according to the oil level fluctuation tolerance ratio to obtain an adapted oil level threshold, and to perform low liquid level emergency shutdown protection in conjunction with the oil level detection device.

2. The low-level emergency shutdown protection device for a thin oil pump according to claim 1, characterized in that, The data monitoring module includes: The continuous monitoring unit is used to continuously monitor the engine's operating temperature, operating load, and oil temperature in the thin oil pump tank using sensing monitoring equipment during engine operation, and obtain K operating temperatures, K operating loads, and K oil temperatures at K continuous monitoring time points, where K is an integer greater than 10; The data sorting unit is used to sort the K operating temperatures, K operating loads and K oil temperatures respectively, and construct the operating temperature sequence, operating load sequence and oil temperature sequence.

3. The low-level emergency shutdown protection device for a thin oil pump according to claim 1, characterized in that, The performance impact analysis module includes: The oil temperature prediction unit is used to perform oil temperature rise fitting analysis based on the oil temperature sequence, obtain the oil temperature rise rate, and predict the predicted oil temperature at the next monitoring time point. The viscosity influence analysis unit is used to calculate the mean values ​​of the end oil temperature and the predicted oil temperature in the oil temperature sequence, and to perform oil viscosity influence analysis based on the temperature mean values, outputting the oil performance influence coefficient.

4. The low-level emergency shutdown protection device for a thin oil pump according to claim 1, characterized in that, The oil consumption rate analysis module includes: The data processing unit is used to collect the operating load of multiple samples and the oil consumption rate of multiple samples within a preset time range, and to perform noise removal and standardization processing to obtain a standard sample operating load set and a standard sample oil consumption rate set. The load-oil analysis unit is used to analyze the standard sample running load set and the standard sample oil consumption rate set to construct a load-oil analysis model, wherein the load-oil analysis model is a linear regression model. The oil consumption rate obtaining unit is used to obtain the oil consumption rate sequence by analyzing the operating load sequence using the load-oil analysis model.

5. The low-level emergency shutdown protection device for a thin oil pump according to claim 1, characterized in that, The detection feedback duration acquisition unit includes: The duration statistics channel is used to separately collect historical detection data of float-type oil level switches and capacitive oil level sensors within a preset time range, and calculate the average detection duration of float, the average detection duration of capacitive, the average data fusion duration, and the average feedback consumption duration. The expected detection time setting channel is used to set the larger of the average float detection time and the average capacitor detection time as the expected detection time; The detection feedback time channel is used to sum the expected detection time, the average data fusion time, and the average feedback consumption time to obtain the detection feedback time.

6. The low-level emergency shutdown protection device for a thin oil pump according to claim 1, characterized in that, The oil level drop prediction unit includes: The data retrieval channel is used to retrieve historical operating data of similar thin oil pumps, collect sample oil consumption rate sequence sets, sample operating temperature sequence sets, and sample oil performance influence coefficient sets, and statistically analyze the oil level drop after the same historical time interval of different sample oil consumption rate sequences, sample operating temperature sequences, and sample oil performance influence coefficients, to obtain the sample oil level drop set. The model training channel is used to train a BP neural network using the sample oil consumption rate sequence set, sample operating temperature sequence set, sample oil performance influence coefficient set, and sample oil level drop set until convergence, thereby obtaining an oil level drop prediction model. The oil level drop prediction channel is used to predict the oil level drop based on the oil consumption rate sequence, operating temperature sequence, and oil performance influence coefficient using the oil level drop prediction model, and outputs the predicted oil level drop.

7. The low-level emergency shutdown protection device for a thin oil pump according to claim 1, characterized in that, The low liquid level shutdown protection module includes: The physical property acquisition unit is used to acquire the physical properties of the oil in the thin oil pump tank, including viscosity, impurity ratio, bubble ratio and conductivity. The detection error analysis unit is used to retrieve historical operating data of similar thin oil pumps based on the physical properties, and to perform detection error analysis on float-type oil level switches and capacitive oil level sensors respectively, so as to obtain the average detection error of float and the average detection error of capacitor. A trusted weight ratio configuration unit is used to configure a trusted weight ratio based on the average float detection error and the average capacitor detection error, wherein the trusted weight is negatively correlated with the average detection error. The shutdown protection unit is used to detect and provide feedback on the oil level in the thin oil pump tank in real time using the oil level detection device according to the trusted weight ratio. If the oil level detection data is less than or equal to the adapted oil level threshold, then low liquid level emergency shutdown protection is performed.

8. A method for emergency shutdown protection of a thin oil pump at low liquid level, characterized in that, The low-level emergency shutdown protection device for the thin oil pump as described in any one of claims 1 to 7 is executed, including: Continuously monitor the engine's operating temperature, operating load, and the oil temperature in the thin oil pump tank to generate operating temperature sequence, operating load sequence, and oil temperature sequence; Based on the oil temperature sequence, an analysis of the impact on oil performance is performed to generate an oil performance impact coefficient. The oil consumption rate sequence is obtained based on the operating load sequence analysis. Based on the oil level detection device, the oil level threshold is optimized according to the oil consumption rate sequence, operating temperature sequence and oil performance influence coefficient to generate a corrected oil level threshold. The corrected oil level threshold is pre-compensated according to the oil level fluctuation tolerance ratio to obtain an adapted oil level threshold, and then combined with the oil level detection device to perform low liquid level emergency shutdown protection.

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