Chemical centrifugal pump operation scheduling optimization system and method

Abstract

The invention particularly relates to a chemical centrifugal pump operation scheduling optimization system and method, and relates to the technical field of intelligent operation and maintenance of chemical equipment, and the method comprises the following steps: sending various obtained data to a data calculation unit for processing to obtain a characteristic abnormal coefficient, an axle temperature abnormal coefficient and an offset abnormal coefficient corresponding to the various data; and comprehensively processing the obtained three coefficients to obtain a bearing fault evaluation coefficient. According to the invention, the limitation of traditional single parameter monitoring is changed, and the running state information of the bearing is comprehensively captured through multi-dimensional data acquisition; in the aspect of data processing, fault characteristic frequency is calculated by combining bearing structure parameters, details such as frequency conversion sideband spectral lines are deeply analyzed, and a plurality of quantitative indexes are constructed for comprehensive evaluation; compared with a traditional mode, the method not only can accurately distinguish faults of the inner ring, the outer ring and the rolling body of the bearing, but also can recognize complex problems such as shaft system misalignment, improves the fault diagnosis accuracy, effectively avoids missed diagnosis and misdiagnosis, and provides a reliable basis for equipment maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent operation and maintenance of chemical equipment, and in particular to a chemical centrifugal pump operation scheduling optimization system and method. Background Art

[0002] As the core fluid conveying equipment in the chemical production process, the operating status of chemical centrifugal pumps directly affects the stability and energy consumption level of the entire production system. At present, the main technical problems of chemical centrifugal pumps in operation are as follows: Traditional fault monitoring methods rely on single-parameter detection, such as determining equipment status solely through vibration amplitude or temperature changes. This makes it difficult to fully capture the complex fault characteristics of bearings. For example, when monitoring only vibration amplitude, it is impossible to distinguish specific faults in the bearing inner ring, outer ring, or rolling element. It is also difficult to identify vibration modulation caused by shaft misalignment or looseness, resulting in low fault diagnosis accuracy and prone to missed or misdiagnosis. In terms of energy-saving optimization, existing technologies lack a coordinated analysis of centrifugal pump operating parameters and equipment health status. Pump speed or flow is typically adjusted based solely on process requirements, without considering the impact of bearing failures on energy consumption. When bearings exhibit faults such as wear and misalignment, the frictional resistance of the pump increases, significantly increasing energy consumption. However, the failure to promptly detect the fault and adjust the operating strategy results in significant energy waste. Existing scheduling systems lack a hierarchical fault handling mechanism. When a fault occurs, they either adopt overly conservative shutdown strategies, impacting production continuity, or fail to promptly handle serious faults, causing equipment damage or even safety accidents. Furthermore, they are unable to dynamically adjust operating parameters based on fault severity, making it difficult to achieve a balance between energy conservation and production efficiency. At the data processing and analysis level, existing technologies lack the depth to integrate multi-source data. Vibration, temperature, displacement, and other data are analyzed independently, failing to fully explore the relationships between them. This prevents the construction of quantitative indicators that comprehensively reflect the equipment status, making it difficult to accurately assess and predict the operating status of centrifugal pumps.

[0003] Therefore, a chemical centrifugal pump operation scheduling optimization system and method are needed to address the above-mentioned problems. Summary of the Invention

[0004] The purpose of the present invention is to solve the above problems and to propose a chemical centrifugal pump operation scheduling optimization system and method.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions: A chemical centrifugal pump operation scheduling optimization system, comprising: The data collection module is configured to obtain relevant data information of the centrifugal pump bearing part, and pre-process the obtained data information and classify it to obtain bearing characteristic frequency data, bearing temperature data, and shaft dynamic runout data; The data analysis and processing module is configured to send the obtained various data to the data calculation unit for processing to obtain the characteristic abnormality coefficient, shaft temperature abnormality coefficient, and offset abnormality coefficient corresponding to the various data; and to perform comprehensive processing on the obtained three coefficients to obtain the bearing fault assessment coefficient; The evaluation and diagnosis module is configured to match the corresponding fault level based on the fault coefficient of the bearing; The optimization scheduling module is configured to perform corresponding optimization scheduling processing according to the fault level of the bearing.

[0006] Preferably, in the data collection module, various types of data are obtained in the following manner: Bearing characteristic frequency data: Sensors are arranged in the vertical, horizontal, and axial directions of the bearing seat. The sampling frequency is set according to the bearing speed and the expected analysis frequency range to obtain the bearing vibration frequency data. Bearing temperature data: Use an infrared thermal imager to measure temperature and obtain the temperature data of the bearing seat and adjacent pump casing; Axis dynamic runout data: The displacement data of the axis in the preset direction is obtained through the displacement sensor.

[0007] Preferably, the process of obtaining the characteristic anomaly coefficient includes: Consult the bearing model manual to obtain bearing structural parameters, including the number of rollers, roller diameter, bearing pitch diameter, and contact angle. Calculate the outer ring fault frequency, inner ring fault frequency, rolling element fault frequency, and their corresponding frequency band amplitudes based on the bearing fault characteristic frequency calculation formula. Then, perform a difference calculation between the frequency band amplitudes and the corresponding preset reference values ​​to obtain the outer ring fault difference, inner ring fault difference, and rolling element fault difference. Preset the allowable ranges of the corresponding fault differences respectively, and record the fault differences that are not within the corresponding allowable ranges as the outer ring fault difference value, the inner ring fault difference value, and the rolling fault difference value; The circle outlier value is obtained by performing weighted sum calculation on the outer circle fault difference value, the inner circle fault difference value, and the rolling fault difference value.

[0008] Preferably, the method further includes: Determine the rotational frequency of the bearing, determine the amplitude of the sideband spectrum line, and use the center frequency as the origin and obtain the amplitude of each sideband spectrum line in sequence according to the distance from the origin; If the amplitude of two adjacent sideband spectrum lines close to the origin is smaller than the amplitude far from the origin, the amplitude far from the origin is marked as an abnormal amplitude; and the difference between the abnormal amplitude and the amplitude close to the origin is calculated, and the absolute value is taken to obtain the abnormal amplitude difference; Arrange all abnormal amplitude differences in descending order according to their numerical values, extract the maximum abnormal amplitude difference, and the number of amplitudes between the maximum abnormal amplitude difference and the abnormal amplitude differences on both sides of it, and take the reciprocal of the amplitude number to obtain the frequency amplitude; The characteristic anomaly coefficient is obtained by weighting the circle outlier value and the frequency amplitude.

[0009] Preferably, the process of obtaining the shaft temperature anomaly coefficient includes: Acquire the temperatures of the bearing and the adjacent pump casing simultaneously at preset time intervals; extract the maximum bearing temperature value and the maximum pump casing temperature value from the temperatures of the bearing and the adjacent pump casing respectively; and record the positions corresponding to the maximum bearing temperature value and the maximum pump casing temperature value as the bearing high temperature point and the pump casing high temperature point respectively; Calculate the difference between the maximum bearing temperature and the maximum pump casing temperature, and take the absolute value to obtain the shaft-casing temperature difference; obtain the shaft-casing temperature difference corresponding to each time interval in turn, and calculate the average of each shaft-casing temperature difference to obtain the shaft-casing temperature difference average; Preset the allowable range of the shaft-shell temperature difference mean value, and mark the shaft-shell temperature difference value that is not within the allowable range of the shaft-shell temperature difference mean value as the temperature difference abnormal value; Arrange all temperature difference constants in descending order according to their numerical values, and extract the two largest temperature difference constants and their corresponding two groups of bearing high temperature points and pump casing high temperature points; Connect the high-temperature points of the bearing and the high-temperature points of the pump casing with a straight line, and calculate the length of the straight line to obtain the temperature change line length; obtain the temperature change line lengths corresponding to the two groups of high-temperature points of the bearing and the high-temperature points of the pump casing in turn; The two obtained temperature change line lengths are used as the major and minor axes of the ellipse, respectively, to construct an ellipse model, and the area of ​​the ellipse model is calculated and recorded as the axial temperature anomaly coefficient.

[0010] Preferably, the process of obtaining the offset anomaly coefficient includes: After the equipment is running stably, start the data acquisition instrument to obtain the displacement data of the bearing in the X and Y directions in real time; Arrange the obtained X-direction displacements in descending order by numerical value, and extract the two largest X-direction displacements. Connect a marked point on the bearing with a straight line starting from the center of the bearing to obtain a baseline. Obtain the baselines after the two largest X-direction displacements and the change angles between the corresponding baselines to obtain the two angular changes in the X-direction displacement, which are used as the original X-angle value 1 and the original X-angle value 2, respectively. Similarly, according to the above process of analyzing the displacement data of the bearing in the X direction, the displacement data of the bearing in the Y direction is analyzed to obtain the Y angle value of square one and the Y angle value of square two; Obtain the original first Y angle value and the original second Y angle value corresponding to the displacement of the bearing in the Y direction when the original first X angle value and the original second X angle value are obtained; Obtain the first and second Y angle values, which correspond to the displacement of the bearing in the X direction; A total of four displacement changes of the bearing are obtained, and the positions of the four displacement changes corresponding to the marker points in three-dimensional space are obtained respectively to obtain four spatial marker points; Mark four spatial marking points on a plane at the same time, and draw straight lines between the four spatial marking points to obtain a closed figure. Calculate the area of ​​the closed figure and record it as the offset anomaly coefficient.

[0011] Preferably, after normalizing the characteristic anomaly coefficient, the shaft temperature anomaly coefficient, and the offset anomaly coefficient, the characteristic anomaly coefficient and the shaft temperature anomaly coefficient are respectively used as two right-angled sides of a right triangle, the remaining side is connected to form a complete right triangle, the offset anomaly coefficient is used as the height of the right triangle, a triangular pyramid is constructed, and the volume of the triangular pyramid is calculated and recorded as the fault assessment coefficient; Three groups of threshold value ranges are preset, and the value range of each group of threshold values ​​corresponds to a fault level. The bearing fault assessment coefficient is matched with the value range of the three groups of threshold values ​​to obtain the fault level corresponding to the bearing fault assessment coefficient, including minor fault, moderate fault and severe fault.

[0012] Preferably, when the minor fault occurs: the equipment is maintained in continuous operation, while the fault progression is controlled and energy consumption is reduced; In the event of a moderate fault: Prioritize production continuity by switching equipment or reducing load to prevent the fault from escalating to a severe one; In case of severe fault: immediately stop the operation of the faulty pump and start the emergency shutdown process to prevent equipment damage or safety accidents.

[0013] A method for optimizing operation scheduling of a chemical centrifugal pump comprises the following steps: Multi-dimensional data acquisition: collect bearing-related information, perform denoising and filtering preprocessing, and establish a benchmark database; Abnormal coefficient calculation: Calculate the corresponding abnormal coefficient based on the collected bearing related information; Fault level assessment: Normalize the three obtained abnormal coefficients to obtain the fault assessment coefficient and match the fault level; Hierarchical scheduling execution: take corresponding measures for different fault levels.

[0014] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. This invention overcomes the limitations of traditional single-parameter monitoring and comprehensively captures bearing operating status information through multi-dimensional data collection. In data processing, it combines bearing structural parameters to calculate fault characteristic frequencies, conducts in-depth analysis of details such as the rotational frequency sideband spectrum, and constructs multiple quantitative indicators for comprehensive evaluation. Compared with traditional methods, this method can not only accurately distinguish faults of the bearing inner ring, outer ring, and rolling elements, but also identify complex problems such as shaft misalignment, thereby improving the accuracy of fault diagnosis, effectively avoiding missed diagnoses and misdiagnoses, and providing a reliable basis for equipment maintenance.

[0015] 2. The present invention achieves energy-saving optimization by combining the health status of the equipment with the operating parameters; formulates differentiated scheduling strategies for different fault levels; in the event of a minor fault, accurately reduces energy consumption through variable frequency speed regulation, thereby reducing unnecessary energy waste; in the event of a moderate fault, reasonably switches to a standby pump and optimizes parameters such as flow rate and speed, thereby reducing overall energy consumption while ensuring production. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 It is a system structure diagram of the present invention; Figure 2 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0017] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and for many different purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0018] Unless otherwise defined, all terms (including 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 belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant art and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless expressly defined as such herein.

[0019] Example 1 The specific implementation method is combined with the attached Figure 1 and attached Figure 2 Provide detailed explanation.

[0020] Attachment Figure 1 A structural block diagram of a chemical centrifugal pump operation scheduling optimization system provided by an embodiment of the present invention shows the connection relationship between the data collection module, data analysis and processing module, evaluation and diagnosis module, and optimization and scheduling module, and marks the main functional interaction process of each module.

[0021] Attachment Figure 2 A flow chart of a chemical centrifugal pump operation scheduling optimization method provided by an embodiment of the present invention shows the complete steps from multi-dimensional data collection to closed-loop optimization iteration.

[0022] In this embodiment, it includes: The data collection module is configured to obtain relevant data information of the centrifugal pump bearing part, and pre-process the obtained data information and classify it to obtain bearing characteristic frequency data, bearing temperature data, and shaft dynamic runout data; The specific methods for obtaining various types of data are as follows: Bearing characteristic frequency data: Arrange sensors in the vertical, horizontal, and axial directions of the bearing seat to ensure a close fit between the sensor and the bearing seat. Use magnetic bases or bolts to secure the sensor when necessary. Set the sampling frequency based on the bearing speed and the expected analysis frequency range to obtain bearing vibration frequency data. Bearing temperature data: Using an infrared thermal imager, temperature measurements are taken after the equipment has been running stably for a preset period of time, allowing the bearing and pump casing temperatures to reach thermal equilibrium and preventing temperature instability during the equipment startup phase from affecting the measurement results. The temperature data of the bearing seat and adjacent pump casing are also obtained. Axis dynamic runout data: The displacement data of the axis in the preset direction is obtained through the displacement sensor; The data analysis and processing module is configured to send the obtained various data to the data calculation unit for processing to obtain the characteristic abnormality coefficient, shaft temperature abnormality coefficient, and offset abnormality coefficient corresponding to the various data; and to perform comprehensive processing on the obtained three coefficients to obtain the bearing fault assessment coefficient; The process of obtaining characteristic anomaly coefficients includes: Consult the bearing model manual to obtain bearing structural parameters, including the number of rollers , roller diameter , bearing pitch diameter , contact angle ; According to the calculation formula of bearing fault characteristic frequency, calculate the outer ring fault frequency, inner ring fault frequency, and rolling element fault frequency; The number of rollers directly affects the calculation base of the fault characteristic frequency of each bearing component; For example, the outer ring fault frequency formula needs to be multiplied by the number of rollers to reflect the frequency of contact between the rollers and the outer ring raceway. If the number of rollers is incorrect, the fault frequency calculation will be biased, and the fault location will be misjudged (for example, misjudging an inner ring fault as an outer ring fault). The roller diameter and bearing pitch diameter determine the motion radius and contact mechanical properties of the bearing's rolling elements. The roller diameter affects the rolling element's rotational frequency, while the pitch diameter is related to the bearing's overall rotational dynamics. When the roller diameter wears down, the rolling element's failure frequency shifts. The degree of roller wear can be determined by comparing theoretical values ​​with measured values. The contact angle reflects the distribution ratio of radial and axial loads on the bearing and affects the angle correction term in the fault frequency calculation formula. Abnormal contact angle (such as angle changes caused by installation deviation) will cause uneven distribution of axial force and accelerate wear of the inner or outer ring. The calculation formula for bearing fault characteristic frequency includes: Outer race fault frequency: Inner race fault frequency: Rolling element failure frequency: Calculate the amplitudes of the frequency bands corresponding to the outer ring fault frequency, inner ring fault frequency, and rolling element fault frequency, and perform difference calculations between the frequency band amplitudes and the corresponding preset reference values ​​to obtain the outer ring fault difference, inner ring fault difference, and rolling element fault difference; Preset the allowable ranges of the corresponding fault differences respectively, and record the fault differences that are not within the corresponding allowable ranges as the outer ring fault difference value, the inner ring fault difference value, and the rolling fault difference value; The circle outlier value is obtained by performing weighted sum calculation on the outer circle fault difference value, the inner circle fault difference value, and the rolling fault difference value; By comparing the amplitude difference between the current operating state and the normal state, the severity of the fault can be quantified. For example, if the outer race fault difference exceeds the allowable range, it means that the outer race fault has affected the vibration characteristics. Establishing a baseline value: Usually, vibration data of new equipment or after overhaul is collected as a reference baseline for a fault-free state; Preset weight factors for the outer ring fault difference value, the inner ring fault difference value, and the rolling fault difference value, and calculate the product of the outer ring fault difference value, the inner ring fault difference value, and the rolling fault difference value with their corresponding weight factors, and then sum them to obtain the ring outlier value; Assign weights to the bearing components based on their importance (e.g., the inner ring has a higher weight than the outer ring because it is in direct contact with the shaft), highlighting the impact of failures of key components on the overall bearing. For example, if the weight of the inner ring fault difference value is set to 0.5, the outer ring is set to 0.3, and the rolling element is set to 0.2, when an abnormality occurs in the inner ring, the amplitude difference value will increase significantly, and the early warning will be triggered first; Determine the rotational frequency of the bearing. In the spectrum diagram, the sideband spectrum lines separated by the rotational frequency show a characteristic of being symmetrically distributed around a certain center frequency, with the rotational frequency as the interval on both sides. Specifically, in the spectrum diagram, in addition to the center frequency peak, there will be a series of equally spaced peaks on both sides, with the interval value equal to the rotational frequency. Determine the amplitude of the sideband spectrum line, and use the center frequency as the origin. According to the distance from the origin, the amplitude of each sideband spectrum line is obtained in sequence. The amplitude of the sideband spectrum line in the subsequent content is abbreviated as amplitude. Description of the symmetrical distribution characteristics of the frequency-converted sideband spectrum: Physical nature: When a bearing has faults such as misalignment or looseness, the vibration signal will produce a modulation effect, resulting in the appearance of sidebands in the spectrum at intervals of rotation frequency. Typical case: When the shaft and bearing are loose, the rotating centrifugal force changes periodically, causing the vibration signal frequency to be modulated, forming sideband spectrum lines; If the amplitude of two adjacent sideband spectrum lines close to the origin is smaller than the amplitude far from the origin, the amplitude far from the origin is marked as an abnormal amplitude; and the difference between the abnormal amplitude and the amplitude close to the origin is calculated, and the absolute value is taken to obtain the abnormal amplitude difference; Under normal circumstances, the amplitude of the sideband spectrum should decrease as it moves away from the center frequency (the amplitude is larger near the origin). If the amplitude distribution is "small near the center and large far away", it indicates that the vibration signal has nonlinear characteristics (such as impact load), which may correspond to local bearing defects. The larger the abnormal amplitude difference value, the higher the impact intensity caused by the fault. For example, when the rolling element peels off, it will produce a severe impact, resulting in a sudden increase in the amplitude difference. Arrange all abnormal amplitude differences in descending order according to their numerical values, extract the maximum abnormal amplitude difference, and the number of amplitudes between the maximum abnormal amplitude difference and the abnormal amplitude differences on both sides of it, and take the reciprocal of the amplitude number to obtain the frequency amplitude; The characteristic anomaly coefficient is obtained by weighting the circle outlier value and the frequency amplitude; The weight factors of the circle outlier value and the frequency amplitude are preset, and the circle outlier value and the frequency amplitude are multiplied by their corresponding weight factors respectively, and the sum is obtained to obtain the characteristic anomaly coefficient; The process of obtaining the shaft temperature anomaly coefficient includes: Acquire the temperatures of the bearing and the adjacent pump casing simultaneously at preset time intervals; extract the maximum bearing temperature value and the maximum pump casing temperature value from the temperatures of the bearing and the adjacent pump casing respectively; and record the positions corresponding to the maximum bearing temperature value and the maximum pump casing temperature value as the bearing high temperature point and the pump casing high temperature point respectively; Dynamic monitoring of temperature data is achieved, capturing real-time temperature trends during equipment operation. By synchronously collecting data at fixed time intervals (e.g., every 10 minutes), misjudgment of temperature differences due to time asynchrony can be avoided, ensuring data comparability and analysis effectiveness. For example, when a chemical centrifugal pump is running continuously, the heat generated by the bearings due to poor lubrication and wear may gradually accumulate. By collecting data regularly, abnormal temperature fluctuations can be detected in time to prevent the fault from expanding. Bearing maximum temperature and hot spots: Internal bearing faults (such as increased friction between rollers and raceways, or grease deterioration) can lead to local overheating. The maximum temperature can directly reflect the degree of bearing abnormality; the hot spots can pinpoint the specific location of the fault. For example, a high temperature at the top of the bearing seat may indicate insufficient lubrication on the upper part. Pump casing maximum temperature and hot spots: Pump casing temperature is affected by factors such as bearing heat conduction and medium flow. Its maximum temperature value and location can help determine the heat transfer path and the thermal state of the pump casing structure. For example, a high temperature on the side of the pump casing near the bearing may indicate abnormal heat conduction of the bearing. Calculate the difference between the maximum bearing temperature and the maximum pump casing temperature, and take the absolute value to obtain the shaft-casing temperature difference; obtain the shaft-casing temperature difference corresponding to each time interval in turn, and calculate the average of each shaft-casing temperature difference to obtain the shaft-casing temperature difference average; The shaft-to-shell temperature difference reflects the thermal difference between the bearing and the pump casing. Under normal circumstances, the temperature difference between the two is within a stable range. If the temperature difference suddenly increases, it may indicate a bearing failure (such as wear, misalignment causing frictional heat generation) or abnormal heat dissipation in the pump casing. The average temperature difference of the shaft shell is used as a benchmark for long-term temperature differences and is used for subsequent abnormality judgment. For example, by continuously monitoring for a week and calculating the average daily temperature difference, the long-term trend of temperature differences can be discovered. Preset the allowable range of the shaft-shell temperature difference mean value, and mark the shaft-shell temperature difference value that is not within the allowable range of the shaft-shell temperature difference mean value as the temperature difference abnormal value; The preset temperature difference average allowable range (such as ±2°C) is marked as an abnormal temperature difference, which quickly filters out temperature data that significantly deviates from the normal state and narrows the scope of troubleshooting. Arrange all temperature difference constants in descending order according to their numerical values, and extract the two largest temperature difference constants and their corresponding two groups of bearing high temperature points and pump casing high temperature points; Arrange the temperature difference anomaly values ​​in descending order and extract the two largest values ​​to focus on the most serious temperature anomaly event. The corresponding high-temperature points on the bearing and pump casing can locate the key areas of equipment thermal anomaly, providing accurate clues for fault diagnosis. Connect the high-temperature points of the bearing and the high-temperature points of the pump casing with a straight line, and calculate the length of the straight line to obtain the temperature change line length; obtain the temperature change line lengths corresponding to the two groups of high-temperature points of the bearing and the high-temperature points of the pump casing in turn; The length of the straight line connecting the high-temperature points of the bearing and the pump casing quantifies the distance of the heat conduction path between the two points. The longer the line, the more complex the heat transfer path, which may cause heat dissipation obstruction or reduced heat conduction efficiency. The two obtained temperature change line lengths are used as the major and minor semi-axes of the ellipse, respectively, to construct an ellipse model, and the area of ​​the ellipse model is calculated and recorded as the axis temperature anomaly coefficient; The process of obtaining the offset anomaly coefficient includes: After the equipment is running stably, start the data acquisition instrument to obtain the displacement data of the bearing in the X and Y directions in real time; The displacement data during stable operation of the equipment can reflect the shaft runout characteristics under normal operating conditions, avoiding the interference of transient fluctuations during startup and shutdown. The two-dimensional displacement acquisition in the X and Y directions can fully capture the offset trajectory of the shaft in the plane, providing a basis for subsequent spatial analysis. Arrange the obtained X-direction displacements in descending order by numerical value, and extract the two largest X-direction displacements. Connect a marked point on the bearing with a straight line starting from the center of the bearing to obtain a baseline. Obtain the baselines after the two largest X-direction displacements and the change angles between the corresponding baselines to obtain the two angular changes in the X-direction displacement, which are used as the original X-angle value 1 and the original X-angle value 2, respectively. Abnormal shaft runout often manifests as large-amplitude offsets. Extracting the two largest displacement values ​​allows you to focus on the most significant offset events. By analyzing extreme offsets, you can more sensitively identify potential faults (such as shaft misalignment and bearing wear) and avoid interference from small-amplitude fluctuations. Angle changes can help determine the directionality of the offset, and combined with the amplitude, can more accurately locate the fault type (such as radial offset, axial tilt, etc.); Similarly, according to the above process of analyzing the displacement data of the bearing in the X direction, the displacement data of the bearing in the Y direction is analyzed to obtain the Y angle value of square one and the Y angle value of square two; Specifically, the obtained Y-direction displacements are sorted in descending order according to their numerical values, and the two largest Y-direction displacements are extracted; a reference line is obtained by connecting a marked point on the bearing with the marked point with a straight line starting from the center of the bearing; the reference lines after the bearing has the two largest Y-direction displacements and the change angles between the corresponding reference lines are obtained, and the two angular changes in the Y-direction displacement are obtained as the Y-angle value of square one and the Y-angle value of square two respectively; Obtain the original first Y angle value and the original second Y angle value corresponding to the displacement of the bearing in the Y direction when the original first X angle value and the original second X angle value are obtained; Obtain the first and second Y angle values, which correspond to the displacement of the bearing in the X direction; A total of four displacement changes of the bearing are obtained, and the positions of the four displacement changes corresponding to the marker points in three-dimensional space are obtained respectively to obtain four spatial marker points; The four spatial points represent the positions of the axis at different deflection states, covering the direction and magnitude of the maximum deflection; The area of ​​the largest enclosed figure can quantify the "spatial range" of the axis deviation. The larger the area, the higher the randomness or abnormality of the axis runout; Analogy: If the shaft is operating normally, the deviation trajectory should be close to a regular shape (such as an ellipse) and have a small area. If there is a fault, the deviation trajectory may diverge and the area may increase significantly. Mark four spatial marking points on a plane simultaneously, and draw a straight line between the four spatial marking points to obtain a closed figure, wherein the closed figure is the largest closed figure that can be formed by the four spatial marking points; calculate the area of ​​the closed figure and record it as the deviation anomaly coefficient; After normalizing the characteristic anomaly coefficient, shaft temperature anomaly coefficient, and offset anomaly coefficient, the characteristic anomaly coefficient and shaft temperature anomaly coefficient are used as the two right-angled sides of a right triangle, and the remaining side is connected to form a complete right triangle. The offset anomaly coefficient is used as the height of the right triangle to construct a triangular pyramid. The volume of the triangular pyramid is calculated and recorded as the fault assessment coefficient. The evaluation and diagnosis module is configured to match the corresponding fault level based on the fault coefficient of the bearing; Three groups of threshold value ranges are preset. Each threshold value range corresponds to a fault level. The bearing fault assessment coefficient is matched with the three threshold value ranges to obtain the fault level corresponding to the bearing fault assessment coefficient, including minor fault, moderate fault, and severe fault. The optimization scheduling module is configured to perform corresponding optimization scheduling processing according to the fault level of the bearing; In the event of a minor fault: Maintain continuous equipment operation while controlling the fault's progression and reducing energy consumption; reduce pump speed through variable frequency speed regulation to reduce radial load on bearings; increase the frequency of collecting data on bearing vibration, temperature, and displacement; and trigger a workshop-level warning when the daily increase in the characteristic anomaly coefficient or the shaft temperature anomaly coefficient exceeds the preset standard, prompting technicians to conduct on-site inspections. In the event of a moderate fault: Prioritize production continuity by switching equipment or reducing load to prevent the fault from escalating to a severe condition. Start the backup centrifugal pump (make sure the backup pump is in good condition in advance) and implement a "soft switch" through the PLC control system. Gradually open the backup pump outlet valve while reducing the main pump flow to maintain stable system pressure. Once the backup pump stabilizes (vibration ≤ 2.5 mm / s, temperature ≤ 70°C), shut down the main pump and complete the switch. Arrange a vibration analyst with a portable spectrum analyzer to perform offline spectrum analysis on the bearing to identify the faulty component. In case of a serious fault: immediately stop the operation of the faulty pump and start the emergency shutdown process to prevent equipment damage or safety accidents; put a tag on the shut-down pump and lock it, release the residual pressure in the pump (if the pressure drops below 0.1MPa), and detect the concentration of surrounding combustible gas; arrange for maintenance personnel to inspect the centrifugal pump.

[0023] Example 2 See also Figure 2 , a chemical centrifugal pump operation scheduling optimization method, comprising the following steps: Multi-dimensional data acquisition: Comprehensively collect information such as bearing characteristic frequency, temperature, and shaft dynamic runout, and perform pre-processing such as denoising and filtering to establish a benchmark database; Abnormal coefficient calculation: Obtain structural parameters based on the bearing model manual, calculate the fault characteristic frequency, compare the measured amplitude with the reference value, and combine the rotation frequency sideband spectrum line analysis to obtain the characteristic abnormal coefficient; calculate the shaft temperature abnormal coefficient based on the shaft shell temperature difference and the location of the high temperature point; construct a spatial model based on the maximum displacement and angle change in the X and Y directions of the shaft to obtain the offset abnormal coefficient; Fault level assessment: The three coefficients of characteristic abnormality, shaft temperature abnormality, and offset abnormality are normalized to obtain the fault assessment coefficient, which is then compared with the preset threshold to classify the fault levels into mild, moderate, and severe. Hierarchical scheduling execution: Take corresponding measures for different fault levels. For minor faults, use frequency conversion to reduce speed, increase data collection frequency, and set early warnings. For moderate faults, start the backup pump for soft switching, and arrange offline spectrum analysis to confirm the faulty component. For severe faults, immediately shut down the machine, perform safety operations such as lockout and pressure relief, and arrange for maintenance. Closed-loop optimization iteration: Record the effectiveness data of each fault assessment and scheduling measure, analyze and optimize the thresholds and weighting factors for calculating each coefficient, formulate preventive maintenance strategies based on historical fault data, and dynamically adjust operating parameters to achieve continuous optimization of energy saving and fault prevention.

[0024] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The influencing weight factors and specific coefficient values ​​in the formula are set by technical personnel in this field according to actual conditions, and can be adjusted and modified later.

[0025] The above embodiments can be implemented in whole or in part through software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0026] The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0027] The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that contains one or more available media. The available medium can be magnetic media, optical media, or semiconductor media. The semiconductor medium can be a solid-state drive.

[0028] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0029] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways.

[0030] For example, the device embodiments described above are merely illustrative. For example, the division of units described herein is merely a logical functional division. Actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through an interface, or indirect coupling or communication connection between devices or units, which may be electrical, mechanical, or other.

[0031] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0032] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0033] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0034] The aforementioned storage media include: USB flash drives, mobile hard disks, read-only memories, random access memories, magnetic disks, optical disks, and other media that can store program codes.

[0035] The above description of the embodiments is intended to enable one skilled in the art to implement or use the present 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 present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A chemical centrifugal pump operation scheduling optimization system, characterized in that: include: The data collection module is configured to obtain relevant data information of the centrifugal pump bearing part, and pre-process the obtained data information and classify it to obtain bearing characteristic frequency data, bearing temperature data, and shaft dynamic runout data; The data analysis and processing module is configured to send the obtained various data to the data calculation unit for processing to obtain the characteristic abnormality coefficient, shaft temperature abnormality coefficient, and offset abnormality coefficient corresponding to the various data; and to perform comprehensive processing on the obtained three coefficients to obtain the bearing fault assessment coefficient; Among them, the amplitude difference value corresponding to the fault frequency of each bearing component is calculated and weighted to obtain the circle abnormal value, combined with the frequency amplitude obtained by sideband spectrum analysis, and the characteristic abnormality coefficient is obtained after weighted calculation; By obtaining the maximum temperature and position of the bearing and pump casing, the temperature difference between the shaft and the casing is calculated and the abnormal value is marked. The length of the line connecting the high-temperature points corresponding to the two largest abnormal values ​​is taken as the semi-axis of the ellipse, and the area of ​​the ellipse is calculated to obtain the shaft temperature abnormality coefficient. By obtaining the bearing displacement data in the X and Y directions and analyzing the change in the reference line angle corresponding to the maximum displacement, four spatial marker points are obtained. After connecting them into a closed figure, the area is calculated to obtain the deviation anomaly coefficient. After normalizing the characteristics, shaft temperature, and offset anomaly coefficients, a right triangle is constructed with the characteristics and shaft temperature anomaly coefficient as right-angled sides, and the offset anomaly coefficient is constructed as a triangular pyramid. The volume of the pyramid is calculated to obtain the bearing fault assessment coefficient. The evaluation and diagnosis module is configured to match the corresponding fault level based on the fault coefficient of the bearing; The optimization scheduling module is configured to perform corresponding optimization scheduling processing according to the fault level of the bearing.

2. A chemical centrifugal pump operation scheduling optimization system according to claim 1, characterized in that: In the data collection module, the specific methods for obtaining various types of data are as follows: Bearing characteristic frequency data: Sensors are arranged in the vertical, horizontal, and axial directions of the bearing seat. The sampling frequency is set according to the bearing speed and the expected analysis frequency range to obtain the bearing vibration frequency data. Bearing temperature data: Use an infrared thermal imager to measure temperature and obtain the temperature data of the bearing seat and adjacent pump casing; Axis dynamic runout data: The displacement data of the axis in the preset direction is obtained through the displacement sensor.

3. A chemical centrifugal pump operation scheduling optimization system according to claim 2, characterized in that: The process of obtaining characteristic anomaly coefficients includes: Consult the bearing model manual to obtain bearing structural parameters, including the number of rollers, roller diameter, bearing pitch diameter, and contact angle. Calculate the outer ring fault frequency, inner ring fault frequency, rolling element fault frequency, and their corresponding frequency band amplitudes based on the bearing fault characteristic frequency calculation formula. Then, perform a difference calculation between the frequency band amplitudes and the corresponding preset reference values ​​to obtain the outer ring fault difference, inner ring fault difference, and rolling element fault difference. Preset the allowable ranges of the corresponding fault differences respectively, and record the fault differences that are not within the corresponding allowable ranges as the outer ring fault difference value, the inner ring fault difference value, and the rolling fault difference value; The circle outlier value is obtained by performing weighted sum calculation on the outer circle fault difference value, the inner circle fault difference value, and the rolling fault difference value.

4. A chemical centrifugal pump operation scheduling optimization system according to claim 3, characterized in that: Also includes: Determine the rotational frequency of the bearing, determine the amplitude of the sideband spectrum line, and use the center frequency as the origin and obtain the amplitude of each sideband spectrum line in sequence according to the distance from the origin; If the amplitude of two adjacent sideband spectrum lines close to the origin is smaller than the amplitude far from the origin, the amplitude far from the origin is marked as an abnormal amplitude; and the difference between the abnormal amplitude and the amplitude close to the origin is calculated, and the absolute value is taken to obtain the abnormal amplitude difference; Arrange all abnormal amplitude differences in descending order according to their numerical values, extract the maximum abnormal amplitude difference, and the number of amplitudes between the maximum abnormal amplitude difference and the abnormal amplitude differences on both sides of it, and take the reciprocal of the amplitude number to obtain the frequency amplitude; The characteristic anomaly coefficient is obtained by weighting the circle outlier value and the frequency amplitude.

5. A chemical centrifugal pump operation scheduling optimization system according to claim 4, characterized in that: The process of obtaining the shaft temperature anomaly coefficient includes: Acquire the temperatures of the bearing and the adjacent pump casing simultaneously at preset time intervals; extract the maximum bearing temperature value and the maximum pump casing temperature value from the temperatures of the bearing and the adjacent pump casing respectively; and record the positions corresponding to the maximum bearing temperature value and the maximum pump casing temperature value as the bearing high temperature point and the pump casing high temperature point respectively; Calculate the difference between the maximum bearing temperature and the maximum pump casing temperature, and take the absolute value to obtain the shaft-casing temperature difference; obtain the shaft-casing temperature difference corresponding to each time interval in turn, and calculate the average of each shaft-casing temperature difference to obtain the shaft-casing temperature difference average; Preset the allowable range of the shaft-shell temperature difference mean value, and mark the shaft-shell temperature difference value that is not within the allowable range of the shaft-shell temperature difference mean value as the temperature difference abnormal value; Arrange all temperature difference constants in descending order according to their numerical values, and extract the two largest temperature difference constants and their corresponding two groups of bearing high temperature points and pump casing high temperature points; Connect the high-temperature points of the bearing and the high-temperature points of the pump casing with a straight line, and calculate the length of the straight line to obtain the temperature change line length; obtain the temperature change line lengths corresponding to the two groups of high-temperature points of the bearing and the high-temperature points of the pump casing in turn; The two obtained temperature change line lengths are used as the major and minor axes of the ellipse, respectively, to construct an ellipse model, and the area of ​​the ellipse model is calculated and recorded as the axial temperature anomaly coefficient.

6. A chemical centrifugal pump operation scheduling optimization system according to claim 5, characterized in that: The process of obtaining the offset anomaly coefficient includes: After the equipment is running stably, start the data acquisition instrument to obtain the displacement data of the bearing in the X and Y directions in real time; Arrange the obtained X-direction displacements in descending order by numerical value, and extract the two largest X-direction displacements. Connect a marked point on the bearing with a straight line starting from the center of the bearing to obtain a baseline. Obtain the baselines after the two largest X-direction displacements and the change angles between the corresponding baselines to obtain the two angular changes in the X-direction displacement, which are used as the original X-angle value 1 and the original X-angle value 2, respectively. Similarly, according to the above process of analyzing the displacement data of the bearing in the X direction, the displacement data of the bearing in the Y direction is analyzed to obtain the Y angle value of square one and the Y angle value of square two; Obtain the original first Y angle value and the original second Y angle value corresponding to the displacement of the bearing in the Y direction when the original first X angle value and the original second X angle value are obtained; Obtain the first and second Y angle values, which correspond to the displacement of the bearing in the X direction; A total of four displacement changes of the bearing are obtained, and the positions of the four displacement changes corresponding to the marker points in three-dimensional space are obtained respectively to obtain four spatial marker points; Mark four spatial marking points on a plane at the same time, and draw straight lines between the four spatial marking points to obtain a closed figure. Calculate the area of ​​the closed figure and record it as the offset anomaly coefficient.

7. A chemical centrifugal pump operation scheduling optimization system according to claim 6, characterized in that: After normalizing the characteristic anomaly coefficient, shaft temperature anomaly coefficient, and offset anomaly coefficient, the characteristic anomaly coefficient and shaft temperature anomaly coefficient are used as the two right-angled sides of a right triangle, and the remaining side is connected to form a complete right triangle. The offset anomaly coefficient is used as the height of the right triangle to construct a triangular pyramid. The volume of the triangular pyramid is calculated and recorded as the fault assessment coefficient. Three groups of threshold value ranges are preset, and the value range of each group of threshold values ​​corresponds to a fault level. The bearing fault assessment coefficient is matched with the value range of the three groups of threshold values ​​to obtain the fault level corresponding to the bearing fault assessment coefficient, including minor fault, moderate fault and severe fault.

8. A chemical centrifugal pump operation scheduling optimization system according to claim 7, characterized in that: In case of minor faults: maintain continuous operation of the equipment, control the development of the fault and reduce energy consumption; In the event of a moderate fault: Prioritize production continuity by switching equipment or reducing load to prevent the fault from escalating to a severe one; In case of severe fault: immediately stop the operation of the faulty pump and start the emergency shutdown process to prevent equipment damage or safety accidents.

9. A method for optimizing operation and scheduling of a chemical centrifugal pump, according to a system for optimizing operation and scheduling of a chemical centrifugal pump according to any one of claims 1 to 8, characterized in that: The following steps are involved: Multi-dimensional data acquisition: collect bearing-related information, perform denoising and filtering preprocessing, and establish a benchmark database; Abnormal coefficient calculation: Calculate the corresponding abnormal coefficient based on the collected bearing related information; Fault level assessment: Normalize the three obtained abnormal coefficients to obtain the fault assessment coefficient and match the fault level; And take corresponding measures for different fault levels.

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