Centrifuge state monitoring system and method thereof

Abstract

The invention discloses a centrifuge state monitoring system and a method thereof, relates to the technical field of equipment monitoring, and solves the problems that an effective mechanism for quantitatively calculating a risk value based on equipment operation data characteristics is lacked, working risk trends in different time periods cannot be estimated in advance, data support cannot be provided for preventive maintenance, and the working efficiency is low. Risk value calculation is innovatively introduced through a normal state analysis unit, a working condition adaptive weight coefficient is substituted into a formula for operation based on a parameter change value (converted into a parameter feature) in a time period, working risks are quantified, and risk values of adjacent periods are compared, so that the risk value calculation accuracy is improved. A secondary analysis signal is generated by insight of a risk rising trend in advance, operation and maintenance personnel are helped to perform pre-intervention, and an abnormal state analysis unit accumulates historical data by means of a system, quickly traverses, screens and matches similar abnormal parameter characteristic historical cases when abnormal conditions occur, accurately locates fault causes and generates 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 the production process and ensuring product quality.

[0003] Traditionally, the operation and maintenance of centrifuges rely on regular manual inspections and post-fault repairs, which have many disadvantages. On the one hand, manual inspections are difficult to achieve real-time, uninterrupted monitoring, and it is difficult to detect abnormal conditions in the equipment during the interval between two inspections, which can easily lead to small faults turning into big problems, and even cause equipment shutdowns, seriously affecting production progress and efficiency. For example, in chemical production, sudden failures and shutdowns of centrifuges may cause the entire batch of materials to be scrapped, resulting in huge economic losses. On the other hand, post-fault repairs are often carried out only after the fault occurs. The troubleshooting process takes a long time. Because the exact time of the fault and the evolution process are unclear, the maintenance is not targeted, and frequent sudden fault repairs also increase equipment maintenance costs and manpower investment. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a centrifuge state monitoring system and method thereof, which solves the problems of lack of an effective mechanism for quantitatively calculating risk values ​​based on the characteristics of equipment operation data, inability to predict the trend of work risks in different time periods in advance, inability to provide data support for preventive maintenance, and difficulty in proactively responding 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 is used to analyze the acquired working parameters, and determine the working state of the centrifuge by periodically monitoring the working 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 transmit 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 characteristics of the working parameters, calculate the risk value based on the parameter characteristics, 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, and calculate the corresponding risk priority index based on the cause of the fault, and then analyze the change of the risk priority index to generate state 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 working 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 time t as a period, and determine the size of the working parameter change value during 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 specific manner in which the normal state analysis unit analyzes the normal state signal is:

[0015] Obtain the working parameters corresponding to the normal state signal, and at the same time obtain the change value of the working parameter 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 work risk value corresponding to the adjacent time period is obtained and recorded as R1, and the sizes of the two work risk values ​​are compared. If the work 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 work risk value R is equal to R1, it means that the work risk value remains unchanged, and no processing is performed, and normal monitoring is performed 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:

[0018] The abnormal parameter characteristics are acquired, and the historical data is acquired at the same time, and the fault causes matching the abnormal parameter characteristics in the historical data are acquired, and then the parameter characteristics corresponding to the fault causes are matched with the abnormal parameter characteristics to generate fault information, and the fault information is transmitted to the monitoring information output unit.

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

[0020] The working parameters corresponding to the abnormal state signal are obtained, and the abnormal parameters in the working parameters are extracted, and the historical data corresponding to the abnormal parameters are obtained and recorded as the data to be analyzed. Then, the fault cause corresponding to the abnormal parameters is determined according to the obtained plastic to be analyzed, and the basic information of the fault cause is obtained, wherein the basic information includes the number of faults, the fault severity value and the detection difficulty value, and 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 risk priority index difference 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 centrifuge failures, and calculate the failure rate of the centrifuge as λ. 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. 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 state monitoring information is generated.

[0024] A centrifuge state monitoring method, the method specifically comprises 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 status results;

[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 perform fault monitoring to generate monitoring information according to the change of the risk value;

[0027] Step three, analyzing the acquired abnormal state signal, analyzing the abnormal parameters in the working parameters, and determining the cause of the fault in combination with historical data, and calculating the corresponding risk priority index based on the cause of the fault, and then analyzing the change of the risk priority index to generate state monitoring information, and the processing method here is the same as 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 thereof. Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention innovatively introduces risk value calculation through the 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, quantifies the work risk, and compares the risk values ​​of adjacent periods, and generates secondary analysis signals in advance to gain insight into the rising trend of risk, helping operation and maintenance personnel to 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;

[0031] The faults are quantitatively scored based on severity and detection difficulty, and the risk priority index and difference are calculated to determine the working status risk. The MTBF is also accurately calculated to derive the failure rate and reliable working value. This allows operation and maintenance to move from experience-driven to data-driven, and to reasonably arrange equipment maintenance cycles and allocate manpower and material resources. Under complex chemical working conditions, maintenance resource investment can be more scientific, equipment life cycle management can be more optimized, and equipment service life can be 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 be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0035] For example, see Figure 1 The present application provides a centrifuge state monitoring system, including: 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 above 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 status results.

[0038] Obtain the working parameters of the centrifuge, 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°C, 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; in a routine production operation, after a monitoring period of t (assuming t = 10 minutes), the system detected that the temperature rose by 15°C compared with the previous cycle, the vibration frequency increased by 12Hz, and the vibration amplitude 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 to generate monitoring information according to the change of the risk value.

[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, it is determined based on long-term operation and maintenance data and equipment manual: Tmax=50℃, Fmax=20Hz, Amax=15mm / 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. In a monitoring period of time t, Tcv = 15°C, Fcv = 8Hz, 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, and the adjacent time period here represents the next time period in the future, and 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, and normal monitoring is performed at the same time;

[0043] Then the generated secondary analysis signal is processed, the abnormal parameter characteristics are acquired, and the historical data is acquired at the same time, and the fault cause matching the abnormal parameter characteristics in the historical data is acquired, 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 feedbacks abnormal parameter characteristics: the temperature rises 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 jumps by 15Hz compared to the stable operation value (the normal fluctuation threshold is 3Hz), and the vibration amplitude reaches 12mm / s. 2 (The normal limit is 8mm / s 2 ). The system immediately went through the historical data and found that there were two similar situations in the past three years. Both were caused by the blockage of the cooling system inside the centrifuge, which resulted in poor heat dissipation and caused a sharp rise in temperature. At the same time, it caused the equipment to become unbalanced and the operational stability to be destroyed, resulting in an abnormal increase in the vibration frequency and amplitude.

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

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

[0047] 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 cause of the fault, and then analyzes the change of the risk priority index to generate status monitoring information.

[0048] The working parameters corresponding to the abnormal state signal are obtained, and the abnormal parameters in the working parameters are extracted, and the historical data corresponding to the abnormal parameters are obtained and recorded as the data to be analyzed, and the data to be analyzed here is represented as the historical data with the same change as the abnormal parameters, and then the fault cause corresponding to the abnormal parameters is determined according to the obtained data to be analyzed, and the basic information of the fault cause is obtained, wherein the basic information includes the number of faults, the fault severity value and the detection difficulty value, and are recorded as S, O and D respectively;

[0049] Specific quantitative assessment of the severity of the impact of the failure. A scoring method can be used, for example, the severity can be divided into 1-10 points, 1 point means almost no impact on production, 10 points means causing serious safety accidents or huge economic losses. For a centrifuge imbalance failure, 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 detection difficulty value is processed in the same way to analyze the difficulty of the fault being detected by the existing monitoring system. It is also expressed in a score, with 1 point indicating that it is very easy to detect and 10 points indicating that it is 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 is difficult to detect in the early stage 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, the risk priority index difference corresponding to two adjacent time periods is calculated and recorded as RPNc, and the calculated difference is compared with the preset value;

[0052] If the difference is greater than the preset value, it means that there is a risk in the working state corresponding to the current time period, and the state monitoring information is generated. Otherwise, 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 centrifuge failures, and calculate the failure rate of the centrifuge as λ. 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. 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 status monitoring information is generated. For example, the failure rate of a centrifuge is λ=0.001 times / hour after statistical analysis. To calculate the reliable working value R(t) after 1000 hours of operation, the obtained parameters are substituted into the formula and the calculated value is 0.368, which means that the probability that the centrifuge can still work normally after 1000 hours of operation is about 0.368.

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

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

[0056] 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 state of the centrifuge, and generate a state result. The processing method here is the same as 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 to generate monitoring information according to the change of the risk value. The processing method here is the same as the processing process of the normal state analysis unit in Example 1.

[0059] Step three, analyzing the acquired abnormal state signal, analyzing the abnormal parameters in the working parameters, and determining the cause of the fault in combination with historical data, and calculating the corresponding risk priority index based on the cause of the fault, and then analyzing the change of the risk priority index to generate state monitoring information, and the processing method here is the same as 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 rather than to limit it. 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 for transmitting the acquired working parameters to a parameter analysis and identification unit; A parameter analysis and identification unit is used to analyze the acquired working parameters, and determine the working state of the centrifuge by periodically monitoring the working 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 transmit 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 characteristics of the working parameters, calculate the risk value based on the parameter characteristics, 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, and calculate the corresponding risk priority index based on the cause of the fault, and then analyze the change of the risk priority index to generate state monitoring information; 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 the abnormal state signal and the normal state signal is: Obtain the working parameters of the centrifuge, monitor the working parameters with time t as a period, and determine the size of the working parameter change value during 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: Obtain the working parameters corresponding to the normal state signal, and at the same time obtain the change value of the working parameter 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 work risk value corresponding to the adjacent time period is obtained and recorded as R1, and the sizes of the two work risk values ​​are compared. If the work 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 work risk value R is equal to R1, it means that the work risk value remains unchanged, and no processing is performed, and normal monitoring is performed 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: The abnormal parameter characteristics are acquired, and the historical data is acquired at the same time, and the fault causes matching the abnormal parameter characteristics in the historical data are acquired, and then the parameter characteristics corresponding to the fault causes are matched with the abnormal parameter characteristics to generate fault information, and the fault information is transmitted to the monitoring information output unit.

6. A centrifuge state monitoring system according to claim 1, characterized in that: The specific method in which the abnormal state analysis unit analyzes the abnormal state signal is as follows: The working parameters corresponding to the abnormal state signal are obtained, and the abnormal parameters in the working parameters are extracted, and the historical data corresponding to the abnormal parameters are obtained and recorded as the data to be analyzed. Then, the fault cause corresponding to the abnormal parameter is determined according to the obtained data to be analyzed, and the basic information of the fault cause is obtained, wherein the basic information includes the number of faults, the fault severity value and the detection difficulty value, and 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 risk priority index difference 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.

7. A centrifuge state monitoring system according to claim 6, characterized in that: The specific method in which the abnormal state analysis unit analyzes the operation analysis signal to generate the state monitoring information is: Get the average time between two adjacent centrifuge failures, and calculate the failure rate of the centrifuge as λ. 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. 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 state monitoring information is generated.

8. A centrifuge state monitoring method, applied to a centrifuge state monitoring system according to any one of claims 1 to 7, 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 status results; 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 perform fault monitoring to generate monitoring information according to the change of the risk value; 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 cause of the fault, and then analyze the change of 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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