Centrifuge state monitoring system and method thereof

Abstract

The present invention discloses a centrifuge state monitoring system and method thereof, which relates to the field of equipment monitoring technology and solves the technical problems of lack of an effective mechanism for quantitatively calculating risk values ​​based on equipment operation data characteristics, inability to predict the work risk trends in different time periods in advance, inability to provide data support for preventive maintenance, and difficulty in actively responding to potential failure threats. The present invention innovatively introduces risk value calculation through a normal state analysis unit, and substitutes the parameter change value (converted into parameter characteristics) in the time period into the formula calculation in combination with the working condition adaptation weight coefficient to quantify the work risk, and compare the risk values ​​of adjacent periods, so as to gain early insight into the risk rising trend and generate a secondary analysis signal to help operation and maintenance personnel intervene in advance. The abnormal state analysis unit relies on the system to accumulate historical data, and when encountering an abnormality, it quickly traverses and screens historical cases with similar abnormal parameter characteristics to accurately locate the cause of the fault and generate detailed fault information.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment monitoring, and in particular to a centrifuge state monitoring system and method thereof. Background Art

[0002] In the field of industrial production, centrifuges, as key separation equipment, are widely used in many industries such as chemical, pharmaceutical, food, and environmental protection. Their stable and efficient operation plays a vital role in ensuring the continuity of production processes and product quality.

[0003] Traditionally, the operation and maintenance of centrifuges has relied heavily on regular manual inspections and post-fault repairs, a method with numerous drawbacks. On the one hand, manual inspections make it difficult to achieve real-time, uninterrupted monitoring. It can be difficult to detect equipment abnormalities between inspections, which can easily lead to minor faults escalating into major problems and even causing equipment downtime, severely impacting production progress and efficiency. For example, in chemical production, a sudden centrifuge failure can cause an entire batch of materials to be scrapped, resulting in significant economic losses. On the other hand, post-fault repairs often involve diagnosing and repairing the problem only after it occurs. This process takes a long time to troubleshoot, and because the exact moment of failure and its evolution are unclear, repairs are less targeted. Frequent repairs for sudden faults also increase equipment maintenance costs and manpower investment. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a centrifuge status monitoring system and method, which solves the problems of lacking an effective mechanism for quantitatively calculating risk values ​​based on the characteristics of equipment operation data, being unable to predict the working risk trends in different time periods in advance, being unable to provide data support for preventive maintenance, and being difficult to proactively respond to potential failure threats.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A centrifuge state monitoring system includes: a centrifuge parameter acquisition unit, which is used to transmit the acquired working parameters to a parameter analysis and identification unit;

[0006] a parameter analysis and identification unit, configured to analyze the acquired operating parameters, determine the operating status of the centrifuge by periodically monitoring the operating parameters, generate an abnormal state signal and a normal state signal, and transmit the generated abnormal state signal to the abnormal state analysis unit and the generated normal state signal to the normal state analysis unit;

[0007] A normal state analysis unit is used to analyze the acquired normal state signal, extract parameter features of the working parameters, calculate the risk value based on the parameter features, and perform fault monitoring according to the change of the risk value to generate monitoring information, and transmit the monitoring information to the monitoring information output unit;

[0008] The abnormal state analysis unit is used to analyze the acquired abnormal state signal, analyze the abnormal parameters in the working parameters, and determine the cause of the fault in combination with historical data. At the same time, it calculates the corresponding risk priority index based on the fault cause, and then analyzes the change of the risk priority index to generate status monitoring information;

[0009] The monitoring information output unit is used to display the acquired status monitoring information and monitoring information to the corresponding operator.

[0010] As a further solution of the present invention, the operating parameters include the temperature, vibration frequency and vibration amplitude of the centrifuge.

[0011] As a further solution of the present invention, the specific manner in which the parameter analysis and identification unit generates the abnormal state signal and the normal state signal is:

[0012] Obtain the working parameters of the centrifuge, monitor the working parameters with a time period of t, and determine the difference between the change value of the working parameters in the time period and the preset value;

[0013] If the operating parameter change value is greater than the preset value, an abnormal state signal is generated. Conversely, if the operating parameter change value is less than the preset value, a normal state signal is generated.

[0014] As a further solution of the present invention, the normal state analysis unit analyzes the normal state signal in the following specific manner:

[0015] Obtain the working parameters corresponding to the normal state signal, and at the same time obtain the working parameter change value within the time period t, and record the change value as the parameter feature, and then substitute the obtained parameter feature into the formula Calculate the working risk value R of the centrifuge, where W T 、W F and W A , respectively represent the temperature risk weight coefficient, vibration frequency risk weight coefficient and vibration amplitude risk weight coefficient, Tcv, Fcv and Acv respectively represent the temperature change value, vibration frequency change value and vibration amplitude change value, Tmax, Fmax and Amax respectively represent the critical temperature change threshold, vibration frequency critical change threshold and vibration amplitude critical change threshold;

[0016] Similarly, the working risk value corresponding to the adjacent time period is obtained and recorded as R1, and the two working risk values ​​are compared. If the working risk value R is less than R1, a secondary analysis signal is generated, and the secondary analysis signal is analyzed to generate fault information. Conversely, if the working risk value R is equal to R1, it means that the working risk value remains unchanged and no processing is performed, and normal monitoring is carried out at the same time.

[0017] As a further solution of the present invention, the specific manner in which the normal state analysis unit analyzes the secondary analysis signal to generate fault information is as follows:

[0018] Acquire the abnormal parameter characteristics and historical data at the same time, and obtain the fault causes that match the abnormal parameter characteristics in the historical data. Then match the parameter characteristics corresponding to the fault cause with the abnormal parameter characteristics to generate fault information, and transmit the fault information to the monitoring information output unit.

[0019] As a further solution of the present invention, the abnormal state analysis unit analyzes the abnormal state signal in the following specific manner:

[0020] Obtaining the operating parameters corresponding to the abnormal state signal, extracting the abnormal parameters from the operating parameters, and obtaining historical data corresponding to the abnormal parameters as data to be analyzed. Then, determining the fault cause corresponding to the abnormal parameters based on the obtained plastic to be analyzed, and obtaining basic information about the fault cause. The basic information includes the number of faults, the fault severity value, and the detection difficulty value, which are recorded as S, O, and D, respectively.

[0021] Substitute the obtained parameters into the formula RPN=S×O×D to calculate the risk priority index RPN corresponding to the fault cause, where S represents the number of faults, O represents the fault severity value, and D represents the detection difficulty value. At the same time, the difference in the risk priority index corresponding to two adjacent time periods is calculated and recorded as RPNc. The calculated difference is compared with the preset value to generate an operation analysis signal and status monitoring information. Then, the operation analysis signal is analyzed to generate the status monitoring information.

[0022] As a further solution of the present invention, the specific manner in which the abnormal state analysis unit analyzes the operation analysis signal to generate the state monitoring information is:

[0023] Get the average time between two adjacent failures of the centrifuge and calculate the failure rate of the centrifuge as λ. The specific calculation formula is: Where MTBF represents the average time between two consecutive failures of the centrifuge. The failure rate is calculated according to the above formula. Then the obtained failure rate λ is substituted into the formula R(t) = e -λt The reliable working value R(t) of the centrifuge is calculated, and the reliable working value here is also expressed as the probability of normal operation, and the condition monitoring information is generated.

[0024] A centrifuge state monitoring method, the method specifically comprising the following steps:

[0025] Step 1: Collect the working parameters of the centrifuge, and periodically monitor the working parameters to determine the working status of the centrifuge and generate a status result;

[0026] Step 2: Analyze the acquired normal state signal, extract the parameter characteristics of the working parameters, calculate the risk value based on the parameter characteristics, and generate monitoring information based on the change of the risk value for fault monitoring;

[0027] Step 3: Analyze the acquired abnormal state signal, analyze the abnormal parameters in the working parameters, and determine the cause of the fault in combination with historical data. At the same time, calculate the corresponding risk priority index based on the fault cause, and then analyze the change of the risk priority index to generate status monitoring information. The processing method here is similar to the processing process of the abnormal state analysis unit in Example 1.

[0028] Step 4: Display the obtained status monitoring information and monitoring information to the corresponding operator.

[0029] The present invention provides a centrifuge state monitoring system and method. Compared with the prior art, it has the following advantages:

[0030] The present invention innovatively introduces risk value calculation through the normal state analysis unit. Based on the parameter change value within the time period (converted into parameter characteristics) combined with the working condition adaptation weight coefficient, the formula is substituted into the calculation to quantify the work risk and compare the risk values ​​of adjacent periods. It can generate a secondary analysis signal in advance to understand the rising trend of risk and help operation and maintenance personnel to intervene in advance. The abnormal state analysis unit relies on the system to accumulate historical data. When an abnormality occurs, it can quickly traverse and screen historical cases with similar abnormal parameter characteristics to accurately locate the cause of the fault and generate detailed fault information.

[0031] Faults are quantitatively scored based on severity and detection difficulty, and risk priority index and difference are calculated to determine working status risks. MTBF is also accurately calculated to derive failure rate and reliable working value, allowing operation and maintenance to move from experience-driven to data-driven, rationally arranging equipment maintenance cycles and allocating manpower and material resources. Under complex chemical working conditions, maintenance resource investment is more scientific, equipment life cycle management is more optimized, and equipment service life is extended. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a block diagram of the system principle of the present invention;

[0033] Figure 2 It is a diagram of the steps of the present invention. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0035] For example 1, please refer to Figure 1 The present application provides a centrifuge state monitoring system, comprising: a centrifuge parameter acquisition unit, a parameter analysis and identification unit, a normal state analysis unit, an abnormal state analysis unit and a monitoring information output unit, and in combination with the attached Figure 1 It can be known that the functional units are electrically connected in a unidirectional manner.

[0036] The centrifuge parameter acquisition unit is used to collect the working parameters of the centrifuge, and the working parameters collected here are real-time data. At the same time, the collected working parameters are transmitted to the parameter analysis and identification unit. The specific working parameters include temperature, vibration frequency and vibration amplitude.

[0037] The parameter analysis and identification unit is used to analyze the acquired working parameters, and judge the working status of the centrifuge by periodically monitoring the working parameters to generate a status result.

[0038] Obtain the working parameters of the centrifuge, and monitor the working parameters with time t as the period, and judge the size of the working parameter change value in the time period and the preset value. The specific value of the preset value is set by the operator. If the working parameter change value is greater than the preset value, and the preset value represents the preset value corresponding to the temperature, vibration frequency and vibration amplitude, for example, the temperature preset value is 80℃, the vibration frequency preset value is set to 10Hz, and the vibration amplitude preset value is set to 5mm / s 2 , it means that the working state of the centrifuge is abnormal and an abnormal state signal is generated. On the contrary, if the working parameter change value is less than the preset value, it means that the working state of the centrifuge is normal and a normal state signal is generated. During a routine production operation, after a monitoring period of time t (assuming t = 10 minutes), the system detected that the temperature had risen by 15°C compared with the previous period, the vibration frequency had increased by 12Hz, and the vibration amplitude had increased to 8mm / s 2 , considering that the temperature change value of 15℃ is greater than the preset corresponding change threshold of 80℃, the vibration frequency change value of 12Hz is higher than the preset 10Hz, and the vibration amplitude change value is 8mm / s 2 It also exceeds the preset 5mm / s 2 , the above working parameters change, and here any group of working parameters is greater than the preset value, it means that the working status is abnormal.

[0039] The generated abnormal state signal is further transmitted to the abnormal state analysis unit, and the generated normal state signal is transmitted to the normal state analysis unit.

[0040] The normal state analysis unit is used to analyze the acquired normal state signal, extract the parameter characteristics of the working parameters, calculate the risk value based on the parameter characteristics, and perform fault monitoring according to the changes in the risk value to generate monitoring information.

[0041] Obtain the working parameters corresponding to the normal state signal, and at the same time obtain the working parameter change value within the time period t, and record the change value as the parameter feature. The parameter feature here is expressed as the temperature change value, the vibration frequency change value and the vibration amplitude change value. Then substitute the obtained parameter feature into the formula Calculate the working risk value R of the centrifuge, where W T 、W F and W A , respectively represent the temperature risk weight coefficient, vibration frequency risk weight coefficient and vibration amplitude risk weight coefficient. The specific values ​​of the three are all between [0, 1]. The specific values ​​are determined according to the actual situation. Tcv, Fcv and Acv represent the temperature change value, vibration frequency change value and vibration amplitude change value respectively. Tmax, Fmax and Amax are the critical temperature change threshold, vibration frequency critical change threshold and vibration amplitude critical change threshold respectively. For example, according to long-term operation and maintenance data and equipment manual, it is determined that: Tmax = 50 ° C, Fmax = 20 Hz, Amax = 15 mm / s 2 , set the weight coefficient W based on the sensitive characteristics of the working condition T =0.35,W F =0.3,W A =0.35. During a certain monitoring period of time t, Tcv = 15°C, Fcv = 8Hz, and Acv = 6mm / s were obtained. 2 , substituting the obtained parameters into the formula, we get R=0.365.

[0042] Similarly, the work risk value corresponding to the adjacent time period is obtained and recorded as R1. The adjacent time period here represents the next time period in the future. The two work risk values ​​are compared. If the work risk value R is less than R1, it means that the work risk of the adjacent time period has an upward trend, and a secondary analysis signal is generated. On the contrary, if the work risk value R is equal to R1, it means that the work risk value remains unchanged and no processing is performed. Normal monitoring is carried out at the same time.

[0043] Then the generated secondary analysis signal is processed, the abnormal parameter characteristics are obtained, and the historical data is obtained at the same time. The fault cause that matches the abnormal parameter characteristics in the historical data is obtained, and then the parameter characteristics corresponding to the fault cause are matched with the abnormal parameter characteristics to generate fault information, and the fault information is transmitted to the monitoring information output unit.

[0044] For example, during the continuous operation of a centrifuge, the current monitoring cycle reported abnormal parameter characteristics: the temperature rose by 20°C in just one hour (under normal conditions, the temperature fluctuation should be within 5°C during the same period), the vibration frequency jumped by 15Hz compared to the stable operating value (the normal fluctuation threshold is 3Hz), and the vibration amplitude reached 12mm / s. 2 (The normal limit is 8mm / s 2 The system immediately reviewed historical data and discovered two similar incidents over the past three years. Both were caused by a blockage in the centrifuge's internal cooling system, resulting in poor heat dissipation and a sudden temperature rise. This also caused equipment imbalance and operational stability to deteriorate, leading to an abnormal increase in vibration frequency and amplitude.

[0045] The monitoring information output unit is used to display the acquired fault information to the corresponding operator.

[0046] Example 2, as Example 2 of the present invention, is implemented on the basis of Example 1, and differs from Example 1 in the following aspects:

[0047] Abnormal state analysis unit, which is used to analyze the acquired abnormal state signal, analyze the abnormal parameters in the working parameters, and determine the cause of the fault in combination with historical data. At the same time, it calculates the corresponding risk priority index based on the cause of the fault, and then analyzes the changes in the risk priority index to generate status monitoring information.

[0048] Obtaining the operating parameters corresponding to the abnormal state signal, extracting the abnormal parameters from the operating parameters, and obtaining historical data corresponding to the abnormal parameters as data to be analyzed, where the data to be analyzed here is historical data with the same change as the abnormal parameters. Then, based on the obtained data to be analyzed, determining the fault cause corresponding to the abnormal parameters, and obtaining basic information about the fault cause, where the basic information includes the number of faults, the fault severity value, and the detection difficulty value, which are recorded as S, O, and D, respectively.

[0049] Specifically, the severity of the fault impact should be quantitatively assessed. A scoring method can be used, for example, the severity can be divided into 1-10 points, with 1 point indicating almost no impact on production and 10 points indicating a serious safety accident or huge economic loss. For a centrifuge imbalance fault, if it is only a slight vibration that affects the separation efficiency but does not cause downtime, it may be rated 3-4 points; if the vibration is severe and causes damage to the centrifuge and production line downtime, it may be rated 7-8 points.

[0050] The same approach is used to analyze the difficulty of detecting the fault by the existing monitoring system. This is also expressed as a score, with 1 being very easy to detect and 10 being almost impossible to detect. If the fault has obvious symptoms, such as a significant increase in vibration amplitude, the detection difficulty is relatively low and may be rated 1-2 points. If the fault is hidden, such as a small seal leak, it may be difficult to detect in the early stages and may be rated 6-8 points.

[0051] Substitute the obtained parameters into the formula RPN = S × O × D to calculate the risk priority index RPN corresponding to the fault cause, where S represents the number of faults, O represents the fault severity value, and D represents the detection difficulty value. At the same time, calculate the difference in the risk priority index corresponding to two adjacent time periods, record it as RPNc, and compare the calculated difference with the preset value;

[0052] If the difference is greater than the preset value, it means that the working state corresponding to the current time period is at risk, and status monitoring information is generated. Conversely, if the difference is less than the preset value, an operation analysis signal is generated and processed at the same time;

[0053] Get the average time between two adjacent failures of the centrifuge and calculate the failure rate of the centrifuge as λ. The specific calculation formula is: Where MTBF represents the average time between two consecutive failures of the centrifuge. The failure rate is calculated according to the above formula. Then the obtained failure rate λ is substituted into the formula R(t) = e -λt The reliable operating value R(t) of the centrifuge is calculated, which is also expressed as the probability of normal operation, and condition monitoring information is generated. For example, if the failure rate of a centrifuge is statistically analyzed to be λ = 0.001 times / hour, and the reliable operating value R(t) after 1000 hours of operation is calculated by substituting the obtained parameters into the formula, the calculated value is 0.368, indicating that the probability that the centrifuge will still function normally after 1000 hours of operation is approximately 0.368.

[0054] The monitoring information output unit is used to display the acquired status monitoring information to the corresponding operator.

[0055] Embodiment 3, as the third embodiment of the present invention, focuses on combining the implementation processes of embodiment 1 and embodiment 2.

[0056] For example 4, please refer to Figure 2 The present application provides a centrifuge state monitoring method, which specifically includes the following steps:

[0057] Step 1: Collect the working parameters of the centrifuge, and periodically monitor the working parameters to determine the working status of the centrifuge, and generate a status result. The processing method here is similar to the processing process of the parameter analysis and identification unit in Example 1;

[0058] Step 2: Analyze the acquired normal state signal, extract parameter features of the working parameters, calculate the risk value based on the parameter features, and perform fault monitoring and generate monitoring information based on the change of the risk value. The processing method here is similar to the processing process of the normal state analysis unit in Example 1.

[0059] Step 3: Analyze the acquired abnormal state signal, analyze the abnormal parameters in the working parameters, and determine the cause of the fault in combination with historical data. At the same time, calculate the corresponding risk priority index based on the fault cause, and then analyze the change of the risk priority index to generate status monitoring information. The processing method here is similar to the processing process of the abnormal state analysis unit in Example 1.

[0060] Step 4: Display the obtained status monitoring information and monitoring information to the corresponding operator.

[0061] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0062] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A centrifuge state monitoring system, characterized in that: include: a centrifuge parameter acquisition unit, used to transmit the acquired working parameters to the parameter analysis and identification unit; a parameter analysis and identification unit, configured to analyze the acquired operating parameters, determine the operating status of the centrifuge by periodically monitoring the operating parameters, generate an abnormal state signal and a normal state signal, and transmit the generated abnormal state signal to the abnormal state analysis unit and the generated normal state signal to the normal state analysis unit; A normal state analysis unit is used to analyze the acquired normal state signal, extract parameter features of the working parameters, calculate the risk value based on the parameter features, and perform fault monitoring according to the change of the risk value to generate monitoring information, and transmit the monitoring information to the monitoring information output unit; The abnormal state analysis unit is used to analyze the acquired abnormal state signal, analyze the abnormal parameters in the working parameters, and determine the cause of the fault in combination with historical data. At the same time, it calculates the corresponding risk priority index based on the fault cause, and then analyzes the change of the risk priority index to generate status monitoring information. The specific analysis method is as follows: Obtaining the operating parameters corresponding to the abnormal status signal, extracting the abnormal parameters from the operating parameters, and obtaining historical data corresponding to the abnormal parameters as data to be analyzed. Then, determining the fault cause corresponding to the abnormal parameters based on the obtained data to be analyzed, and obtaining basic information about the fault cause. The basic information includes the number of faults, the fault severity value, and the detection difficulty value, which are recorded as S, O, and D, respectively. Substitute the obtained parameters into the formula RPN=S×O×D to calculate the risk priority index RPN corresponding to the fault cause, where S represents the number of faults, O represents the fault severity value, and D represents the detection difficulty value. At the same time, the difference in the risk priority index corresponding to two adjacent time periods is calculated and recorded as RPNc. The calculated difference is compared with the preset value to generate an operation analysis signal and status monitoring information. Then, the operation analysis signal is analyzed to generate the status monitoring information. Get the average time between two consecutive failures of the centrifuge and calculate the failure rate of the centrifuge as , and the specific calculation formula is , where MTBF represents the average time between two adjacent failures of the centrifuge. The failure rate is calculated according to the above formula, and then the obtained failure rate is Substitute into the formula The reliable working value R(t) of the centrifuge is calculated, and the reliable working value here is also expressed as the probability of normal operation, and the condition monitoring information is generated; The monitoring information output unit is used to display the acquired status monitoring information and monitoring information to the corresponding operator.

2. A centrifuge state monitoring system according to claim 1, characterized in that: The operating parameters include the temperature, vibration frequency and vibration amplitude of the centrifuge.

3. A centrifuge state monitoring system according to claim 1, characterized in that: The specific manner in which the parameter analysis and identification unit generates abnormal state signals and normal state signals is as follows: Obtain the working parameters of the centrifuge, monitor the working parameters with a time period of t, and determine the difference between the change value of the working parameters in the time period and the preset value; If the operating parameter change value is greater than the preset value, an abnormal state signal is generated. Conversely, if the operating parameter change value is less than the preset value, a normal state signal is generated.

4. A centrifuge state monitoring system according to claim 1, characterized in that: The specific manner in which the normal state analysis unit analyzes the normal state signal is as follows: Obtain the working parameters corresponding to the normal state signal, and at the same time obtain the working parameter change value within the time period t, and record the change value as the parameter feature, and then substitute the obtained parameter feature into the formula Calculate the working risk value R of the centrifuge, where W T 、W F and W A , respectively represent the temperature risk weight coefficient, vibration frequency risk weight coefficient and vibration amplitude risk weight coefficient, Tcv, Fcv and Acv respectively represent the temperature change value, vibration frequency change value and vibration amplitude change value, Tmax, Fmax and Amax respectively represent the critical temperature change threshold, vibration frequency critical change threshold and vibration amplitude critical change threshold; Similarly, the working risk value corresponding to the adjacent time period is obtained and recorded as R1, and the two working risk values ​​are compared. If the working risk value R is less than R1, a secondary analysis signal is generated, and the secondary analysis signal is analyzed to generate fault information. Conversely, if the working risk value R is equal to R1, it means that the working risk value remains unchanged and no processing is performed, and normal monitoring is carried out at the same time.

5. A centrifuge state monitoring system according to claim 4, characterized in that: The specific manner in which the normal state analysis unit analyzes the secondary analysis signal to generate fault information is as follows: Acquire the abnormal parameter characteristics and historical data at the same time, and obtain the fault causes that match the abnormal parameter characteristics in the historical data. Then match the parameter characteristics corresponding to the fault cause with the abnormal parameter characteristics to generate fault information, and transmit the fault information to the monitoring information output unit.

6. A centrifuge state monitoring method, applied to a centrifuge state monitoring system according to any one of claims 1 to 5, characterized in that: The method specifically comprises the following steps: Step 1: Collect the working parameters of the centrifuge, and periodically monitor the working parameters to determine the working status of the centrifuge and generate a status result; Step 2: Analyze the acquired normal state signal, extract the parameter characteristics of the working parameters, calculate the risk value based on the parameter characteristics, and generate monitoring information based on the change of the risk value for fault monitoring; Step 3: Analyze the acquired abnormal status signal, analyze the abnormal parameters in the working parameters, and determine the cause of the fault in combination with historical data. At the same time, calculate the corresponding risk priority index based on the fault cause, and then analyze the changes in the risk priority index to generate status monitoring information; Step 4: Display the obtained status monitoring information and monitoring information to the corresponding operator.

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