Ship equipment monitoring and early warning system based on data analysis

Abstract

The invention relates to the technical field of ship equipment monitoring and early warning, and particularly discloses a ship equipment monitoring and early warning system based on data analysis, and the system comprises a data collection module which is installed on various sensors of an oil separator and is used for carrying out the real-time collection of various state parameters in the operation process of the oil separator; the analysis monitoring module is used for analyzing various state parameters collected in real time in the operation process of the oil separator, and comparing an abnormal risk coefficient curve in the working process of the oil separator within a preset time period with a preset allowable error coefficient curve; according to the method, the abnormal risk coefficient curve in the working process of the oil separator is obtained by analyzing various state parameters collected in real time, and the abnormal frequency, time and abnormal risk reference mean value of the oil separator are compared by comparing the abnormal risk coefficient curve with the preset allowable error coefficient curve; and the maintenance and repair time period of the oil separator is adjusted.

Description

Technical Field

[0001] The present invention relates to the technical field of ship equipment monitoring and early warning, and specifically provides a ship equipment monitoring and early warning system based on data analysis. Background Art

[0002] The centrifugal separator is one of the important ship equipment. It has a relatively complex structure and high operating speed. It is the main equipment that needs to be strengthened in monitoring, maintenance and repair in engine room management. Its function is to separate different components in fuel oil according to their boiling point ranges. The basic principle is to use the tiny gaps between the separating discs and the centrifugal force generated by the high-speed rotation of the centrifugal separator to separate various components in the crude oil for use in different parts of the ship.

[0003] In the prior art, the monitoring of the centrifugal separator equipment during use is mostly carried out by sensors to monitor the relevant state parameters during its operation in real time and to monitor the cumulative usage time since the last maintenance and repair. When the state parameters monitored in real time exceed the preset early warning threshold or the cumulative usage time within its maintenance cycle reaches the preset fixed maintenance time cycle, an early warning is issued to facilitate the management personnel to carry out maintenance and repair. The maintenance time cycle of this kind of monitoring and early warning method is a preset fixed value, and it cannot be intelligently adjusted according to the state during the operation of the centrifugal separator equipment, which may cause an increase in faults and an increase in maintenance costs during the use of the centrifugal separator. Summary of the Invention

[0004] The purpose of the present invention is to provide a ship equipment monitoring and early warning system based on data analysis, and solve the following technical problems:

[0005] How to intelligently adjust the maintenance time cycle of the centrifugal separator equipment.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A ship equipment monitoring and early warning system based on data analysis, the system includes:

[0008] A data acquisition module, various sensors installed on the centrifugal separator, used to collect various state parameters during the operation of the centrifugal separator in real time;

[0009] The analysis and monitoring module is used to analyze various state parameters collected in real time during the operation of the oil separator, obtain the abnormal risk coefficient curve during the operation of the oil separator, compare the abnormal risk coefficient curve during the operation of the oil separator in a preset time period with the preset allowable error coefficient curve, and obtain the abnormal number, time and abnormal risk reference mean during the operation of the oil separator; by analyzing the abnormal number, time, abnormal risk reference mean and cumulative use time, the maintenance and repair time period of the oil separator is adjusted, and an early warning maintenance signal is generated when the maintenance and repair time period arrives;

[0010] The early warning module is used to execute early warning maintenance signals.

[0011] In one embodiment, the process of obtaining the abnormal risk coefficient analysis includes:

[0012]

[0013] The abnormal risk coefficient curve C of the oil separator during operation is obtained by analyzing and calculating the above formula. risk (t);

[0014] Among them, i∈[1,N], N is the number of state parameters monitored during the operation of the oil separator, is the i-th state parameter curve during the operation of the oil separator, is the standard curve of the i-th state parameter during the operation of the oil separator, τ i is the weight coefficient corresponding to the i-th state parameter.

[0015] In one embodiment, the process of obtaining the abnormal number, time and abnormal risk of the oil separator during operation by referring to the mean value analysis includes:

[0016] In the preset time period [t1, t2], the abnormal risk coefficient curve C risk (t) and the preset allowable error coefficient curve C sth (t) is compared, and the curve segments whose abnormal risk coefficient values are greater than or equal to the allowable error coefficient are intercepted. Statistical analysis is performed on all the curve segments intercepted within the preset time period [t1, t2] to obtain the number of all the curve segments intercepted within the preset time period [t1, t2], the accumulated time and the average height of the area formed between the two curves and above the allowable error coefficient curve, wherein the number of curve segments is the number of abnormalities M during the working process of the oil separator within the preset time period [t1, t2], the accumulated time is the abnormal time T during the working process of the oil separator, and the area between the two curves is the reference mean value V of the abnormal risk during the working process of the oil separator.

[0017] Furthermore, the process of obtaining the abnormal risk by referring to the mean analysis includes:

[0018] Obtained the abnormal risk reference mean value V through analysis and calculation by the formula where Δt = t2 - t1.

[0019] Among them, Δt = t2 - t1.

[0020] Furthermore, the process of obtaining the preset allowable error coefficient curve analysis includes:

[0021]

[0022] Obtained the preset allowable error coefficient curve C sth (t) through analysis and calculation by the above formula;

[0023] where t sum (t) is the cumulative usage time of the centrifuge at time point t, A(t) is the cumulative maintenance times of the centrifuge at time point t, σ is the coefficient for converting a single maintenance of the centrifuge into usage time, a is a preset constant and a ∈ (0, 1), and δ is the limit standard value of the allowable error coefficient of the centrifuge.

[0024] In one embodiment, the process of adjusting the maintenance time period of the centrifuge includes:

[0025]

[0026] Obtained the adjusted maintenance time period P s (t) of the centrifuge through analysis and calculation by the above formula;

[0027] where P sth is the standard maintenance time period of the centrifuge, M(t) is the number of analyzed abnormal times at time point t within this maintenance time period, T(t) is the cumulative abnormal time analyzed at time point t within this maintenance time period, and V(t) is the abnormal risk reference mean value analyzed at time point t within this maintenance time period.

[0028] Furthermore, the process of generating the warning maintenance signal includes:

[0029] When the cumulative usage time of the centrifuge within this cycle is greater than or equal to the adjusted maintenance time period of the centrifuge, a warning maintenance signal is generated.

[0030] In one embodiment, the system further includes:

[0031] A data storage module for recording and storing the data collected during the use of the centrifuge, the cumulative usage time, the cumulative maintenance times, and the number of abnormal times, abnormal time, and abnormal risk reference mean value within a preset time period;

[0032] A visual display terminal for visually displaying the various state parameters of the centrifuge and the data analysis results.

[0033] Advantages of the present invention:

[0034] (1) Various sensors installed on the oil separator in the present invention collect various state parameters during the operation of the oil separator in real time. The analysis and monitoring module is used to analyze the various state parameters collected in real time during the operation of the oil separator to obtain the abnormal risk coefficient curve during the working process of the oil separator.

[0035] (2) By comparing the abnormal risk coefficient curve with the preset allowable error coefficient curve in the present invention, the number of abnormalities, time and abnormal risk reference mean value of the oil separator within the preset time period are analyzed, and then combined with the cumulative usage time of the oil separator for comprehensive analysis to adjust the maintenance and overhaul time period of the oil separator. When the cumulative usage time since the last maintenance of the oil separator reaches the adjusted maintenance and overhaul time period, a warning maintenance signal is generated, and the warning module executes this signal. Description of the Drawings

[0036] The present invention will be further described below with reference to the drawings.

[0037] Figure 1 is a schematic block diagram of a ship equipment monitoring and warning system based on data analysis proposed by the present invention. Detailed Embodiments

[0038] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] Please refer to Figure 1 As shown, in one embodiment, a ship equipment monitoring and warning system based on data analysis is provided. The system includes:

[0040] A data acquisition module, various sensors installed on the oil separator, used to collect various state parameters during the operation of the oil separator in real time;

[0041] The analysis and monitoring module is used to analyze various state parameters collected in real time during the operation of the centrifugal separator, obtain the abnormal risk coefficient curve during the operation of the centrifugal separator, compare the abnormal risk coefficient curve with the preset allowable error coefficient curve during the operation of the centrifugal separator within a preset time period, and obtain the number of abnormalities, time and abnormal risk reference mean value during the operation of the centrifugal separator; by analyzing the number of abnormalities, time, abnormal risk reference mean value and cumulative usage time, adjust the maintenance and repair time period of the centrifugal separator, and generate a warning maintenance signal when the maintenance and repair time period arrives;

[0042] The warning module is used to execute the warning maintenance signal.

[0043] Through the above technical solution, a ship equipment monitoring and warning system based on data analysis is provided in this embodiment. Specifically, various sensors that can be installed on the centrifugal separator collect various state parameters in real time during the operation of the centrifugal separator. Among them, the various state parameters include but are not limited to the inlet and outlet flow rates of the centrifugal separator, internal pressure, internal temperature, rotation speed, quality of the separated oil product, etc. Then, the analysis and monitoring module is used to analyze various state parameters collected in real time during the operation of the centrifugal separator, obtain the abnormal risk coefficient curve during the operation of the centrifugal separator, and then compare this curve with the preset allowable error coefficient curve to analyze and obtain the number of abnormalities, time and abnormal risk reference mean value of the centrifugal separator within a preset time period. Then, combined with the cumulative usage time of the centrifugal separator for comprehensive analysis, adjust the maintenance and repair time period of the centrifugal separator. When the cumulative usage time since the last maintenance of the centrifugal separator reaches the adjusted maintenance and repair time period, generate a warning maintenance signal, and the warning module executes this signal to notify the management personnel that the centrifugal separator needs to be maintained and repaired.

[0044] In one embodiment, the process of obtaining the abnormal risk coefficient analysis includes:

[0045]

[0046] Obtain the abnormal risk coefficient curve C risk (t) of the centrifugal separator during operation through the above formula analysis and calculation;

[0047] where i ∈ [1, N], N is the number of monitored state parameters during the operation of the centrifugal separator, is the curve of the i-th state parameter during the operation of the centrifugal separator, is the standard curve of the i-th state parameter during the operation of the centrifugal separator, and τ i is the weight coefficient corresponding to the i-th state parameter.

[0048] Through the above technical solution, a method for obtaining the abnormal risk coefficient during the operation of the centrifugal separator is provided in this embodiment. Specifically, it can be obtained through the formula Calculation and analysis to obtain the abnormal risk coefficient curve C risk (t) during the operation of the oil separator. Among them, there are N state parameters monitored during the operation of the oil separator, and i ∈ [1, N]. is the curve of the i-th state parameter during the operation of the oil separator, which can be obtained by the linear regression algorithm based on the real-time monitoring values of each sensor installed on the oil separator. is the standard curve of the i-th state parameter during the operation of the oil separator, which can be obtained by experimental analysis of the monitoring of various parameters during the operation of the oil separator, τ i is the weight coefficient corresponding to the i-th state parameter, which can be obtained by fitting the experimental analysis of the abnormal risk coefficient of the oil separator.

[0049] In one embodiment, the process of obtaining the abnormal times, time, and abnormal risk reference mean during the operation of the oil separator by referring to the mean analysis includes:

[0050] Within the preset time period [t1, t2], compare the abnormal risk coefficient curve C risk (t) with the preset allowable error coefficient curve C sth (t), intercept the curve segments where the abnormal risk coefficient values are greater than or equal to the allowable error coefficient, and conduct statistical analysis on all the intercepted curve segments within the preset time period [t1, t2] to obtain the number of all intercepted curve segments, the cumulative time, and the average height of the area formed between the two curves and above the allowable error coefficient curve within the preset time period [t1, t2]. Among them, the number of all curve segments is the number of abnormal times M during the operation of the oil separator within the preset time period [t1, t2], the cumulative time is the abnormal time T during the operation of the oil separator, and the area between the two curves is the abnormal risk reference mean V during the operation of the oil separator.

[0051] The process of obtaining the abnormal risk reference mean by referring to the mean analysis includes:

[0052] Through the formula Analyze and calculate to obtain the abnormal risk reference mean V;

[0053] where Δt = t2 - t1.

[0054] Through the above technical solution, this embodiment provides a method for analyzing and obtaining the number of anomalies, anomaly time, and anomaly risk reference mean value during the operation of a separator. During a preset time period, the anomaly risk coefficient curve is compared with a preset allowable error coefficient curve, and the curve segment of the anomaly risk coefficient curve when the anomaly risk coefficient value is greater than or equal to the allowable error coefficient is intercepted. Statistical analysis is performed on the intercepted curve segment. Among them, the number of intercepted curve segments is the number of anomalies M that occur during the operation of the separator within the preset time period, the cumulative length of the X-axis of the intercepted curve segment is the cumulative anomaly time T during the operation of the separator within the preset time period, and the average height of the area formed between the intercepted curve segment and the preset allowable error coefficient curve is the anomaly risk reference mean value V during the operation of the separator within the preset time period. Specifically, it can be obtained through the formula Analysis and calculation are performed to obtain Δt = t2 - t1.

[0055] In one embodiment, the process of analyzing and obtaining the preset allowable error coefficient curve includes:

[0056]

[0057] The preset allowable error coefficient curve C sth (t) is obtained through analysis and calculation using the above formula;

[0058] where t sum (t) is the cumulative usage time of the separator at time point t, A(t) is the cumulative number of repairs of the separator at time point t, σ is the coefficient for converting a single repair of the separator into usage time, a is a preset constant, and a ∈ (0, 1), and δ is the limit standard value of the allowable error coefficient of the separator.

[0059] Through the above technical solution, this embodiment provides a method for analyzing and obtaining a preset allowable error coefficient curve. Specifically, the preset allowable error coefficient curve C is obtained through analysis and calculation using the formula sth (t), where t sum(t) is the cumulative usage time of the purifier at time point t, which can be specifically obtained by accumulating the historical usage time of the purifier. A(t) is the cumulative maintenance times of the purifier at time point t, which can be obtained by counting the maintenance records during the use of the purifier. σ is the coefficient for converting a single maintenance of the purifier into usage time, which can be obtained through experimental analysis of the impact of a single maintenance of the purifier on its service life. a is a preset constant, and a ∈ (0, 1), which can be obtained through experimental analysis of the impact of the cumulative usage time of the purifier on its allowable error. δ is the limit standard value of the allowable error coefficient of the purifier, which can be obtained by selecting through experimental analysis of the allowable error of the abnormal risk coefficient during the use of the purifier. No matter how long the purifier is used and how many times it is maintained, when the abnormal risk coefficient during its use is greater than this value, it is determined that the state of the purifier during operation is abnormal.

[0060] In one embodiment, the process of adjusting the maintenance time period of the purifier includes:

[0061]

[0062] The adjusted maintenance time period P s (t) of the purifier is obtained through the above formula analysis and calculation;

[0063] where P sth is the standard maintenance time period of the purifier, M(t) is the number of analyzed abnormalities at time point t within this maintenance time period, T(t) is the cumulative abnormal time analyzed at time point t within this maintenance time period, and V(t) is the abnormal risk reference mean analyzed at time point t within this maintenance time period.

[0064] The process of generating the warning maintenance signal includes:

[0065] When the cumulative usage time of the purifier within this cycle is greater than or equal to the adjusted maintenance time period of the purifier, a warning maintenance signal is generated.

[0066] Through the above technical solution, this embodiment provides a method for generating a warning maintenance signal. Specifically, first, the adjusted maintenance time period P of the purifier is obtained through formula analysis and calculation, where P s (t), where P sthIt is the standard maintenance time cycle of the oil separator, which can be obtained by analyzing the maintenance manual of the oil separator. M(t) is the number of anomalies obtained by analysis at time point t within this maintenance time cycle, T(t) is the cumulative anomaly time obtained by analysis at time point t within this maintenance time cycle, and V(t) is the anomaly risk reference mean obtained by analysis at time point t within this maintenance time cycle. M(t), T(t), and V(t) are all time intervals from the initial time point of this maintenance time cycle to the latest time point t within the preset time period, and can be specifically obtained by analyzing the number of anomalies, anomaly time, and anomaly risk reference mean within the preset time period during the working process of the oil separator as described above.

[0067] In one embodiment, the system further includes:

[0068] A data storage module for recording and storing the data collected during the use of the oil separator, the cumulative usage time, the cumulative number of repairs, and the number of anomalies, anomaly time, and anomaly risk reference mean within the preset time period.

[0069] A visual display terminal for visually displaying the status parameters and data analysis results of the oil separator.

[0070] Through the above technical solution, this embodiment provides a method for facilitating data analysis and visualization during the working process of the oil separator. The data storage module can record and store the status parameters during the operation of the oil separator collected by the data acquisition module during the working process of the oil separator, the cumulative usage time and cumulative number of repairs in the historical data of the oil separator, and the number of anomalies, anomaly time, and anomaly risk reference mean obtained by the analysis and monitoring module within the preset time period, so as to facilitate the analysis and mining and invocation by the analysis and monitoring module. The visual display terminal can visually display the status parameters and data analysis results of the oil separator to the management personnel for viewing, so that the management personnel can understand the operation status and abnormal conditions of the oil separator and control and adjust the operation of the oil separator as needed.

[0071] The above has described a detailed description of an embodiment of the present invention, but the content described is only the preferred embodiment of the present invention and cannot be considered as used to limit the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A ship equipment monitoring and early warning system based on data analysis, characterized in that, The system includes: A data acquisition module, various sensors installed on the oil separator, which are used to collect various state parameters during the operation of the oil separator in real time; An analysis and monitoring module, which is used to analyze the various state parameters collected in real time during the operation of the oil separator, obtain the abnormal risk coefficient curve during the operation of the oil separator, compare the abnormal risk coefficient curve during the operation of the oil separator within a preset time period with the preset allowable error coefficient curve, and obtain the number of abnormalities, time and abnormal risk reference mean value during the operation of the oil separator; By analyzing the number of abnormalities, time, abnormal risk reference mean value and cumulative usage time, adjust the maintenance time period of the oil separator, and generate a warning maintenance signal when the maintenance time period arrives; A warning module, which is used to execute the warning maintenance signal.

2. The ship equipment monitoring and early warning system based on data analysis according to claim 1, characterized in that, The process of obtaining the abnormal risk coefficient analysis includes: The abnormal risk coefficient curve C of the centrifuge during operation is obtained through the above formula analysis and calculation risk (t); where \(i\in[1,N]\), and \(N\) is the number of state parameters monitored during the operation of the centrifuge. is the curve of the \(i\)-th state parameter during the operation of the centrifuge. is the standard curve of the \(i\)-th state parameter during the operation of the centrifuge, and \(\tau\) i is the weight coefficient corresponding to the \(i\)-th state parameter.

3. A ship equipment monitoring and early warning system based on data analysis according to claim 2, characterized in that, The process of obtaining the analysis of the number of abnormalities, time and abnormal risk reference mean value during the operation of the oil separator includes: Within a preset time period [t1, t2], the abnormal risk coefficient curve C risk (t) is compared with the preset allowable error coefficient curve C sth (t). The curve segments with abnormal risk coefficient values greater than or equal to the allowable error coefficient are intercepted, and statistical analysis is performed on all the intercepted curve segments within the preset time period [t1, t2] to obtain the number of all intercepted curve segments, the cumulative time, and the average height of the area formed between the two curves and above the allowable error coefficient curve within the preset time period [t1, t2]. Among them, the number of all curve segments is the number of abnormalities M during the operation of the centrifugal separator within the preset time period [t1, t2], the cumulative time is the abnormal time T during the operation of the centrifugal separator, and the area between the two curves is the abnormal risk reference mean value V during the operation of the centrifugal separator.

4. A ship equipment monitoring and early warning system based on data analysis according to claim 3, characterized in that, The process of obtaining the analysis of the abnormal risk reference mean value includes: Obtained by the formula Analyze and calculate to obtain the abnormal risk reference mean value V; Where, Δt = t2 - t1.

5. A ship equipment monitoring and warning system based on data analysis according to claim 4, characterized in that, The process of obtaining the analysis of the preset allowable error coefficient curve includes: The preset allowable error coefficient curve C sth (t); where t sum (t) is the cumulative operating time of the centrifuge at time point t, A(t) is the cumulative repair times of the centrifuge at time point t, σ is the coefficient for converting a single repair of the centrifuge into operating time, a is a preset constant and a ∈ (0, 1), and δ is the limit standard value of the allowable error coefficient of the centrifuge.

6. The ship equipment monitoring and early warning system based on data analysis according to claim 5, characterized in that, The process of adjusting the maintenance time period of the oil separator includes: The maintenance time period P after the adjustment of the purifier is obtained through the above formula analysis and calculation s (t); Among them, P sth is the standard maintenance time cycle of the purifier, M(t) is the number of analyzed anomalies at time point t within this maintenance time cycle, T(t) is the cumulative anomaly time analyzed at time point t within this maintenance time cycle, and V(t) is the reference mean of the anomaly risk analyzed at time point t within this maintenance time cycle.

7. The ship equipment monitoring and early warning system based on data analysis according to claim 6, characterized in that, The process of generating the warning maintenance signal includes: When the cumulative usage time of the oil separator in this cycle is greater than or equal to the adjusted maintenance time period of the oil separator, a warning maintenance signal is generated.

8. A ship equipment monitoring and early warning system based on data analysis according to claim 1, characterized in that, The system further includes: A data storage module, which is used to record and store the data collected during the use of the oil separator, the cumulative usage time, the cumulative number of repairs, and the number of abnormalities, abnormal time, and abnormal risk reference mean value within a preset time period; A visual display terminal, which is used to visually display the various state parameters and data analysis results of the oil separator.

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