Status monitoring system and data analysis device

Abstract

The condition monitoring system (100) includes a data measurement device (20), a data analysis device (30), and a diagnostic device (40). The data measurement device (20) acquires measurement data from sensor detection signals based on provided measurement conditions. The data analysis device (30) performs analysis processing on the measurement data acquired by the data measurement device (20). The diagnostic device (40) performs diagnostic processing to assess the facility's condition based on the analysis results obtained through the analysis processing. The data analysis device (30) sets the measurement conditions and analysis conditions for the analysis processing based on the time required for the analysis processing and diagnostic processing.

Description

Technical Field

[0001] This invention relates to a status monitoring system and a data analysis device. Background Technology

[0002] A known condition monitoring system uses measurement data collected by sensors installed on a facility to perform analytical processing, such as RMS calculation and frequency analysis, and monitors the condition of the facility based on the results of the analytical processing.

[0003] For example, Japanese Patent Application Publication No. 2019-173706 (Patent Document 1) discloses a monitoring system for a wind power station. In this monitoring system, each wind turbine is equipped with a status monitoring device that monitors its own status using measurement data collected by the wind turbine itself (first data) and measurement data obtained from another wind turbine via a communication device (second data). When the operating status of the other wind turbine is consistent with the operating status of the wind turbine itself, the status monitoring device obtains the second data synchronized with the first data from the other wind turbine, and monitors the status of the wind turbine itself based on the degree of deviation in the set of data including the first and second data (see Patent Document 1).

[0004] Existing technical documents

[0005] Patent documents

[0006] Patent Document 1: Japanese Patent Application Publication No. 2019-173706 Summary of the Invention

[0007] Technical issues

[0008] In some cases, real-time status monitoring systems are required to monitor the condition of facilities. For example, in production sites, when analyzing facility measurement data (e.g., vibration data) using methods such as frequency analysis, and diagnosing the facility based on the results of this analysis, any unresponsive diagnostic results will lead to delays in the detection of facility anomalies and in the response to anomalies. In such cases, both the analysis of measurement data and the diagnostic processing based on the analysis results must be performed in real time. However, Patent Document 1 does not specifically consider this real-time processing.

[0009] The present invention aims to solve the above-mentioned problems. The purpose of the present invention is to ensure real-time processing of the status monitoring system for monitoring facilities.

[0010] Technical solutions to solve technical problems

[0011] The condition monitoring system according to the present invention is a condition monitoring system for monitoring the condition of a facility. The condition monitoring system includes sensors attached to the facility, a data measurement device, a data analysis device, and a diagnostic device. The data measurement device receives detection signals from the sensors and acquires measurement data from the sensor detection signals according to provided measurement conditions. The data analysis device receives the measurement data from the data measurement device and performs analysis processing on the measurement data. The diagnostic device performs diagnostic processing to determine the condition of the facility based on the analysis results obtained through the analysis processing. The data analysis device sets the measurement conditions and the analysis conditions for the analysis processing based on the time required for the analysis processing and diagnostic processing.

[0012] The data analysis apparatus according to the present invention is a data analysis apparatus that performs analysis processing on measurement data received from a data measurement device. The data measurement device is configured to acquire measurement data from detection signals of sensors attached to a facility based on provided measurement conditions. The data analysis apparatus includes a calculator and a calculation controller. The calculator performs analysis processing on the measurement data. The calculation controller sets the measurement conditions and the analysis conditions for the analysis processing based on the time required for the analysis processing and for diagnostic processing to diagnose the condition of the facility based on the analysis results obtained through the analysis processing.

[0013] In the aforementioned condition monitoring system and data analysis device, the measurement conditions of the data measurement device and the analysis conditions of the analysis processing are set based on the time required for analyzing and processing the measurement data and for performing diagnostic processing based on the results of the analysis and processing. Therefore, the measurement and analysis conditions can be set so that the time required for analysis and diagnostic processing does not exceed the measurement interval of the measurement data. Thus, the condition monitoring system and data analysis device can ensure real-time processing.

[0014] Preferably, the data analysis device (computation controller) sets the measurement conditions based on the measurement efficiency, which represents the relationship between the measurement interval of the measurement data in the data measurement device and the time required for analysis, processing, and diagnostic processing.

[0015] More preferably, the data analysis device (computation controller) sets the measurement conditions based on the measurement efficiency, which represents the relationship between the measurement interval of the measurement data in the data measurement device and the time required for analysis, processing, and diagnostic processing, as well as the communication time.

[0016] More preferably, the data analysis device (computation controller) sets the analysis conditions based on measurement efficiency.

[0017] More preferably, the data analysis device (computation controller) sets the analysis conditions based on the measurement efficiency and the results of the diagnostic processing.

[0018] Preferably, the data analysis device (computation controller) sets the analysis conditions when the measurement conditions set based on measurement efficiency are not included in the prescribed adjustment range.

[0019] Preferably, the sensor includes at least one of a vibration sensor, a temperature sensor, a pressure sensor, a strain sensor, and a load sensor.

[0020] Invention Effects

[0021] According to the present invention, real-time processing of the status monitoring system for monitoring facilities can be ensured. Attached Figure Description

[0022] Figure 1 This is a block diagram schematically illustrating the overall configuration of a status monitoring system according to an embodiment of the present invention.

[0023] Figure 2 Show in detail Figure 1 The structure of the status monitoring system is shown.

[0024] Figure 3 This shows an example of a measurement condition setting table included in the calculation condition file.

[0025] Figure 4 This shows an example of an analysis level setting table included in the calculation conditions file.

[0026] Figure 5 This shows an example of an analysis processing settings table included in the calculation conditions file.

[0027] Figure 6 This is a first flowchart illustrating an exemplary process of the handling performed in a status monitoring system.

[0028] Figure 7 This is a second flowchart illustrating an exemplary process of the handling performed in a status monitoring system. Detailed Implementation

[0029] Embodiments of the present invention will now be described in detail with reference to the accompanying drawings. The same or corresponding parts in the drawings have the same reference numerals and will not be described again.

[0030] Figure 1 This is a block diagram schematically illustrating the overall configuration of a status monitoring system according to an embodiment of the present invention. (See reference) Figure 1 The status monitoring system 100 includes a sensor unit 10, a data measurement device 20, a data analysis device 30, a diagnostic device 40, and a display device 50.

[0031] Sensor unit 10 includes various sensors attached to the facility. For example, when the condition monitoring system 100 monitors the condition of the wind power generation facility, sensor unit 10 includes a vibration sensor for detecting vibrations of the main bearing. The sensors included in sensor unit 10 are not limited to vibration sensors; they can also be temperature sensors, pressure sensors, strain sensors, load sensors, or other arbitrary sensors. The following description assumes that sensor unit 10 includes a vibration sensor.

[0032] The data measurement device 20 receives the detection signal (analog signal) from the sensor unit 10. The data measurement device 20 is, for example, a data logger or a programmable logic controller (PLC). The data measurement device 20 acquires measurement data from the sensor detection signal according to the measurement conditions set by the data analysis device 30. The measurement conditions include, for example, the measurement interval, measurement time, and sampling frequency.

[0033] More specifically, the measurement interval is equivalent to the transmission interval from the data measurement device 20 to the data analysis device 30. The data analysis device 30 performs analysis processing on a set of measurement data for each measurement interval, and the diagnostic device 40 uses the results of the analysis processing to perform diagnostic processing. The measurement time is the actual time that the measurement is performed in the data measurement device 20 within the measurement interval, and the measurement interval can be equal to the measurement time. The sampling frequency is the frequency at which the detection signal (analog signal) from the sensor unit 10 is sampled.

[0034] The data analysis device 30 comprises a central processing unit (CPU), read-only memory (ROM), random access memory (RAM), etc. (not shown). The CPU deploys a program stored in the ROM to the RAM, etc., and runs the program. The program stored in the ROM refers to a program that describes the steps of the data analysis device 30. The data analysis device 30 can be configured, for example, locally or in the cloud.

[0035] The data analysis device 30 receives measurement data acquired in the data measurement device 20 according to measurement conditions. Then, the data analysis device 30 performs analysis processing on the measurement data. This analysis processing includes, for example, calculating the square root (RMS) of the measurement data, analyzing the frequency by performing a high-speed Fourier transform (FFT) on the measurement data, and calculating the crest factor (CF) of the measurement data. The data analysis device 30 then sends the results of the analysis processing (hereinafter also referred to as "analysis results") to the diagnostic device 40.

[0036] The diagnostic device 40 also comprises a CPU, ROM, RAM, etc. (not shown). The program stored in the ROM is a program that describes the steps of the diagnostic device 40. The diagnostic device 40 is also configured to be, for example, local or cloud-based, and is configured to communicate with the data analysis device 30 via a communication system such as a local area network (LAN) or the Internet, or an external system.

[0037] The diagnostic device 40 receives the analysis results of the measurement data from the data analysis device 30. Then, based on the analysis results, the diagnostic device 40 performs diagnostic processing to diagnose the condition of the facility whose data was collected by the sensor unit 10. For example, when a vibration sensor collects bearing vibration data, the diagnostic processing includes comparing the analysis results (such as RMS, FFT spectrum, CF of the vibration data) with a predetermined threshold to diagnose the damage level of the bearing. The diagnostic device 40 then sends the result of the diagnostic processing (hereinafter also referred to as the "diagnostic result") to the data analysis device 30. The diagnostic device 40 also sends the time required for the diagnostic processing (diagnostic processing time) to the data analysis device 30.

[0038] Condition monitoring system 100, for example, monitors the condition of wind power generation facilities, and such a condition monitoring system 100 requires real-time condition monitoring. In other words, the analysis and diagnostic processing of measurement data at each measurement interval must be completed within the measurement interval. If the analysis and diagnostic processing is not completed within the measurement interval, data will back up, which may require measures to address data loss or diagnostic interruptions. When such measures are taken, real-time processing cannot be achieved, and real-time diagnostics cannot be realized. This will lead to delays in facility anomaly detection and anomaly response.

[0039] In recent years, the computational load of analytical and diagnostic processing has been increasing as larger-scale facilities are monitored for high-reliability diagnostics, making real-time processing a critical challenge. One solution is to use high-performance hardware, but this significantly increases costs, necessitating a cost-effective approach to ensuring real-time processing.

[0040] In the status monitoring system 100 according to this embodiment, the data analysis device 30 sets the measurement conditions of the data measurement device 20 and the analysis conditions of the analysis processing based on the time required for analysis processing (hereinafter also referred to as "analysis processing time") and the time required for diagnostic processing in the diagnostic device 40 (hereinafter also referred to as "diagnostic processing time"). The analysis conditions of the analysis processing refer to conditions that specify the detailed content of the analysis processing. In this embodiment, the analysis conditions specify, for example, whether to perform any one of RMS, FFT spectrum, and CF analysis calculations, and also specify the passband for filtering the measurement data. The analysis processing is not limited to RMS, FFT spectrum, and CF.

[0041] The measurement conditions and analysis conditions of the data measurement device 20 are set based on the analysis processing time and the diagnostic processing time. This allows the measurement and analysis conditions to be set so that the time required for analysis and diagnostic processing does not exceed the measurement interval of the measurement data. Thus, the status monitoring system 100 can ensure real-time processing.

[0042] The display device 50 receives various display data from the data analysis device 30 and displays the received display data on the screen. For example, the display device 50 receives measurement data acquired by the data measurement device 20, the analysis results (analysis results) of the data analysis device 30, the diagnostic results (diagnostic results) of the diagnostic device 40, and various setting information, including the measurement conditions and analysis conditions set by the data analysis device 30, as display data and displays them on the screen.

[0043] Figure 2 Show in detail Figure 1 The structure of the status monitoring system 100 shown is illustrated. (Reference) Figure 2 The data analysis device 30 includes a calculation condition file 32, a calculator 34, and a calculation controller 36.

[0044] The calculator 34 receives measurement data acquired in the data measurement device 20 according to measurement conditions. The calculator 34 also receives analysis conditions set by the calculation controller 36 for analysis processing. Then, the calculator 34 performs analysis processing on the measurement data received from the data measurement device 20 according to the analysis conditions. The analysis conditions and analysis processing will be described in detail later.

[0045] The calculator 34 sends the results of the analysis to the diagnostic device 40. In this example, the data analysis device 30 and the diagnostic device 40 are connected via a communication system 60, such as the Internet or a local area network (LAN), and the analysis results are sent to the diagnostic device 40 via the communication system 60.

[0046] The calculator 34 also times the time required for analysis and processing (analysis and processing time). Then, the calculator 34 outputs the timed analysis and processing time to the computing controller 36.

[0047] The calculation controller 36 acquires the calculation condition file 32 to set the measurement and analysis conditions. The calculation condition file 32 will be described in detail later. The calculation controller 36 also receives the analysis processing time obtained from the calculator 34. The calculation controller 36 also receives, via the communication system 60, the results of diagnostic processing (diagnostic results) performed in the diagnostic device 40 based on the analysis processing results (analysis results) and the time required for diagnostic processing (diagnostic processing time).

[0048] Then, the calculation controller 36 refers to the calculation condition file 32 and, based on the analysis processing time received from the calculator 34 and the diagnostic processing time received from the diagnostic device 40, sets the measurement conditions of the data measurement device 20 and the analysis conditions of the analysis processing performed in the calculator 34. The method for setting the measurement and analysis conditions will be described in detail below.

[0049] When setting measurement and analysis conditions, the computing controller 36 calculates the turnaround time for the overall processing, including analysis processing and diagnostic processing. For example, the computing controller 36 calculates the total turnaround time as the sum of the analysis processing time received from the calculator 34 and the diagnostic processing time received from the diagnostic device 40.

[0050] The method for calculating turnaround time is not limited to this. For example, turnaround time can be the difference between the time when the data analysis device 30 obtains measurement data from the data measurement device 20 and the time when it obtains diagnostic results from the diagnostic device 40. In this case, turnaround time includes analysis processing time and diagnostic processing time.

[0051] Then, the computing controller 36 calculates the "measurement efficiency," which represents the relationship between the measurement interval of the measurement data and the turnaround time of the overall processing, including analysis and diagnostic processing. In this embodiment, the measurement efficiency is expressed as the ratio of the measurement interval to the turnaround time, as shown in the following formula.

[0052] Measurement efficiency = Turnaround time / Measurement interval ... (1)

[0053] Preferably, the communication system 60 times the communication time between the data analysis device 30 and the terminal device 40. Alternatively, the calculator 34 outputs the end time of analysis processing to the calculation controller 36, and the terminal device 40 outputs the start time and end time of diagnostic processing to the calculation controller 36 through the communication system 60. The calculation controller 36 adds the difference between the end time of analysis processing and the start time of diagnostic processing, and the difference between the end time of diagnostic processing and the time when the diagnostic result is received, and times the time required for communication (bidirectional) between the communication system 60. Then, the calculation controller 36 calculates the turnaround time of the overall processing, including the time required for analysis processing and diagnostic processing, as well as the communication time of the communication system 60, and calculates the measurement efficiency based on the calculated turnaround time and the measurement interval of the measurement data.

[0054] Measurement efficiency is not limited to this method; for example, it can also be expressed as the difference between the measurement interval and the turnaround time.

[0055] The closer the measurement efficiency shown in Equation (1) is to 0, the shorter the processing time required for analysis and diagnostic processing compared to the measurement interval. On the other hand, the closer the measurement efficiency is to 1, the closer the processing time required for analysis and diagnostic processing is to the measurement interval, and the shorter the waiting time until the next measurement begins. When the measurement efficiency exceeds 1, the analysis and diagnostic processing do not end within the measurement interval, thus preventing real-time processing.

[0056] The calculation controller 36 calculates the aforementioned measurement efficiency at each measurement interval. Then, based on the calculated measurement efficiency, the calculation controller 36 sets the measurement conditions of the data measurement device 20 and outputs the detailed settings to the data measurement device 20. For example, when the measurement efficiency is less than 1, the calculation controller 36 adjusts each measurement item to shorten the measurement interval and increase the sampling frequency; when the measurement efficiency is greater than or equal to 1, it adjusts each measurement item to extend the measurement interval and decrease the sampling frequency.

[0057] The calculation controller 36 sets the analysis conditions for the analysis process based on the calculated measurement efficiency and outputs the detailed settings to the calculator 34. For example, when the measurement efficiency is low, since there is still processing margin, the calculation controller 36 sets the analysis conditions to perform any other calculations for frequency analysis, such as FFT calculations and CF calculations, in addition to RMS calculations. On the other hand, when the measurement efficiency is high, since there is no processing margin, the calculation controller 36 sets the analysis conditions to limit the calculations performed in the analysis process to a portion of the calculations (e.g., only RMS calculations and FFT calculations, or only RMS calculations).

[0058] Although the setting (adjustment) of measurement conditions and the setting of analysis conditions can be performed separately and independently, in this embodiment, the setting of analysis conditions is performed when the adjustment of measurement conditions is not included in the prescribed adjustment range (described below). As mentioned above, by changing the analysis conditions, the analysis items can be limited: in order to maintain status monitoring for the widest possible range, the adjustment of measurement conditions takes precedence over the change of analysis conditions, and the analysis conditions are set (changed) when real-time processing cannot be ensured by adjusting the measurement conditions.

[0059] Figure 3 An example of a measurement condition setting table included in calculation condition file 32 is shown. (Reference) Figure 3 Measurement items are the settings for measurement conditions, including, for example, measurement interval, measurement time, and sampling frequency. Initial settings are the initial values ​​for each measurement item before the computer controller 36 adjusts each measurement item.

[0060] The adjustment range for each measurement item is defined by the setpoints (worst-case condition, desired condition, and optimal condition). The setpoint (worst-case condition) represents the worst-case value for each measurement item. The setpoints for measurement interval and measurement time are relatively large, while the setpoint for sampling frequency is relatively small. The setpoint (desired condition) represents the desired value for each measurement item. The setpoint (optimal condition) represents the optimal value for each measurement item. The setpoints for measurement interval and measurement time are relatively small, while the setpoint for sampling frequency is relatively large.

[0061] As described above, the calculation controller 36 sets measurement conditions based on measurement efficiency. Specifically, when the measurement efficiency is less than 1, the calculation controller 36 adjusts the setpoint of each measurement item towards the "setpoint (optimal condition)". On the other hand, when the measurement efficiency is greater than or equal to 1, the calculation controller 36 adjusts the setpoint of each measurement item towards the "setpoint (worst condition)". In a specific adjustment method, for example, the measurement items are prioritized, and the setpoint is adjusted starting with the highest priority measurement item based on the measurement efficiency.

[0062] When the measurement efficiency is less than 1, the calculation controller 36 ends the setting process when the setpoint of each measurement item is adjusted between the "setpoint (desired condition)" and the "setpoint (optimal condition)". When the measurement efficiency is greater than or equal to 1, the calculation controller 36 ends the setting process and sets the analysis level and analysis conditions when the setpoint of each measurement item is adjusted between the "setpoint (worst condition)" and the "setpoint (optimal condition)".

[0063] The IDs in the table are assigned to each measurement item. (Although described later...) Figure 4 and Figure 5The table shown also provides an ID for each item, but the ID is a number used to distinguish items in each table, and the tables do not use IDs to link items together.

[0064] Figure 4 This shows an example of an analysis level setting table included in calculation condition file 32. (Reference) Figure 4 The details of the analysis performed in calculator 34 are defined according to the analysis level set using the analysis level setting table. Further details will be provided later. Figure 5 To illustrate, in this embodiment, the lower the analysis level, the more limited the types of analysis calculations in the analysis process (e.g., only RMS calculations are performed), and the higher the analysis level, the more types of analysis calculations are performed (e.g., not only RMS calculations are performed, but also FFT and CF calculations are performed).

[0065] The analysis level depends on the measurement efficiency. In this embodiment, when the measurement efficiency R is greater than or equal to 0 and less than 0.5, the analysis level is set to 3 because there is still processing margin. When the measurement efficiency R is greater than or equal to 0.5 and less than 0.8, the analysis level is set to 2. When the measurement efficiency is greater than or equal to 0.8, the analysis level is set to 1 because there is no processing margin.

[0066] Figure 5 This shows an example of the analysis processing settings table included in calculation condition file 32. (Reference) Figure 5 The calculation type refers to the type of analytical calculation that can be performed in the analysis process. In this example, it includes RMS calculation, FFT calculation for frequency analysis, and CF calculation. The calculation parameter refers to the passband of the bandpass filter (BPF) used to preprocess the measurement data received from the data measurement device 20.

[0067] The diagnostic level refers to the level of the diagnostic result obtained in the diagnostic device 40 based on the analysis and processing results. For example, when the sensor unit 10, which includes a vibration sensor, collects bearing vibration data, the damage level of the bearing is diagnosed and displayed as the diagnostic level by comparing the analysis results (e.g., RMS, FFT spectrum, CF of the vibration data) with a predetermined threshold. The analysis level is determined by using... Figure 4 The analysis level setting table is shown, and it is determined based on measurement efficiency.

[0068] As shown in the figure, in this embodiment, the calculation type of the analysis process depends on the analysis level, which is determined based on measurement efficiency. In this example, when the analysis level is 1 (measurement efficiency R ≥ 0.8), only RMS calculation is performed in the analysis process. When the analysis level is 2 (0.5 ≤ measurement efficiency R < 0.8), in addition to performing RMS calculation, FFT calculation for frequency analysis is also performed in the analysis process. When the analysis level is 3 (0 ≤ measurement efficiency R < 0.5), in addition to performing RMS and FFT calculations, CF is also calculated in the analysis process.

[0069] In this embodiment, the calculation parameters are also set according to the diagnostic level of the diagnostic device 40. In this example, when the diagnostic level of the diagnostic device 40 is 0, if the calculation type is RMS, the calculation parameter (passband of BPF for the measurement data) is set to f01~f02 kHz; if the calculation type is FFT, the calculation parameter is set to f11~f12 kHz; and if the calculation type is CF, the calculation parameter is set to f21~f22 kHz.

[0070] When the diagnostic level of the diagnostic device 40 is 1, if the calculation type is RMS, the calculation parameters are set to f31-f32 kHz; if the calculation type is FFT, the calculation parameters are set to f41-f42 kHz; and if the calculation type is CF, the calculation parameters are set to f51-f52 kHz. When the diagnostic level of the diagnostic device 40 is 2, if the calculation type is RMS, the calculation parameters are set to f61-f62 kHz; if the calculation type is FFT, the calculation parameters are set to f71-f72 kHz; and if the calculation type is CF, the calculation parameters are set to f81-f82 kHz.

[0071] As described above, in this embodiment, the measurement efficiency is calculated based on the time required for analysis and diagnostic processing, and the details of the analysis processing (calculation type) are set according to the analysis level set based on the measurement efficiency. The details of the analysis processing (calculation parameters) are set based on the results (diagnostic level) of the diagnostic processing by the diagnostic device 40.

[0072] Include Figures 3-5 The calculation condition files 32 for each setting table are stored in a storage device (not shown) such as a hard disk drive (HDD) or a solid-state drive (SSD).

[0073] Back to Figure 2 The calculation controller 36 inputs the measurement conditions, set (adjusted) based on measurement efficiency, into the data measurement device 20. Then, the data measurement device 20 measures the data according to the measurement conditions received from the data analysis device 30 (calculation controller 36).

[0074] The calculation controller 36 also outputs the set analysis conditions (such as the calculation type and calculation parameters of the analysis process) to the calculator 34. Then, the calculator 34 performs analysis processing on the measurement data received from the data measurement device 20 according to the analysis conditions received from the calculation controller 36.

[0075] The diagnostic device 40 includes a diagnostic condition file 42 and a diagnostic unit 44. The diagnostic condition file 42 includes diagnostic conditions for performing diagnostic processing in the diagnostic unit 44. For example, the diagnostic condition file 42 includes a threshold value in the diagnostic unit 44 for determining the level (diagnostic level) of the diagnostic result used to perform a diagnosis on the analysis results of the data analysis device 30.

[0076] The diagnostic unit 44 receives the results of the analysis processing performed by the calculator 34 of the data analysis device 30 according to the analysis conditions set by the calculation controller 36. Then, the diagnostic unit 44 refers to the diagnostic condition file 42 and performs diagnostic processing based on the analysis results received from the data analysis device 30. The diagnostic unit 44 sends the diagnostic results obtained through the diagnostic processing to the data analysis device 30 (calculation controller 36).

[0077] The diagnostic unit 44 also times the time required for the diagnostic process (diagnostic processing time). Then, the diagnostic unit 44 sends the timed diagnostic processing time along with the diagnostic results to the data analysis device 30 (computation controller 36).

[0078] Figure 6 and Figure 7 A flowchart illustrating an example of the processing steps performed in the status monitoring system 100 of this embodiment is shown. The processing in this flowchart is executed whenever a predetermined condition is met. For example, the processing in this flowchart is executed periodically, or when the diagnostic result of the diagnostic device 40 changes.

[0079] Reference Figure 6 First, the data analysis device 30 initializes the measurement and analysis conditions by referring to the calculation condition file 32 (step S10). Specifically, for the measurement conditions, the measurement interval, measurement time, and sampling frequency are set as follows: Figure 3 The initial settings are shown in the measurement condition setting table. The data analysis device 30 sends these initial settings as measurement conditions to the data measurement device 20. The data measurement device 20 starts data measurement based on the initial settings of the measurement conditions received from the data analysis device 30.

[0080] For the analysis conditions, initialize the analysis level to the highest level (analysis level 3 in this example) and the diagnostic level to the lowest level (diagnostic level 0 in this example). Then, refer to... Figure 5The analysis and processing settings table shown sets RMS, FFT, and CF calculations as the initial settings for calculation types in the analysis and processing, based on the initial settings for analysis level and diagnostic level.

[0081] After the measurement and analysis conditions are initialized, the data analysis device 30 begins reading measurement data from the data measurement device 20 (step S20). Then, the data analysis device 30 performs analysis processing on the measurement data received from the data measurement device 20 according to the set analysis conditions (step S30). As described above, under the initial settings, each of the RMS, FFT, and CF calculations is performed on the read measurement data. The data analysis device 30 calculates the time required to perform the analysis processing (analysis processing time). Then, the data analysis device 30 sends the execution result of the analysis processing (analysis result) to the diagnostic device 40.

[0082] When the data analysis device 30 performs analysis processing, the diagnostic device 40 performs diagnostic processing on the analysis results (step S40). The diagnostic device 40 refers to the diagnostic condition file 42 to determine the diagnostic level of the analysis results received from the data analysis device 30. The diagnostic device 40 also calculates the time required to perform the diagnostic processing (diagnostic processing time). Then, the diagnostic device 40 sends the diagnostic processing result (diagnostic level) and the diagnostic processing time to the data analysis device 30.

[0083] When the diagnostic result and diagnostic processing time are received from the diagnostic device 40, the data analysis device 30 calculates the turnaround time of the overall processing, including the analysis processing and diagnostic processing (step S50). In this example, the turnaround time is calculated as the total time of the analysis processing time calculated during the execution of the analysis processing and the diagnostic processing time received from the diagnostic device 40.

[0084] Then, the data analysis device 30 calculates the measurement efficiency based on the above formula (1) according to the measurement interval set as a measurement condition and the calculated turnaround time (step S60).

[0085] refer to Figure 7 The data analysis device 30 determines whether the calculated measurement efficiency and measurement conditions are within the specified conditions (step S70). Specifically, if the measurement efficiency is less than 1, then for each measurement item of the measurement conditions ( Figure 3 When the set value of a measurement item is between the "set value (desired condition)" and the "set value (optimal condition)", the data analysis device 30 determines that the measurement efficiency and measurement conditions are within the specified conditions. However, if the analysis level is 1, when the set value of each measurement item is between the "set value (worst condition)" and the "set value (optimal condition)", the data analysis device 30 determines that the measurement efficiency and measurement conditions are within the specified conditions.

[0086] When it is determined in step S70 that the measurement efficiency and measurement conditions are within the specified conditions (step S70: Yes), the data analysis device 30 determines that the diagnostic processing is performed in real time, and the processing proceeds to "end".

[0087] If it is determined in step S70 that the measurement efficiency and measurement conditions are not within the specified conditions (step S70: No), the data analysis device 30 determines whether the number of times the measurement conditions have been adjusted has exceeded the upper limit (step S80). The adjustment of the measurement conditions will be explained in step S90. The upper limit is appropriately set as a count value, which is generally sufficient to adjust the measurement efficiency and measurement conditions within the specified conditions.

[0088] When it is determined that the number of times the measurement conditions have been adjusted exceeds the upper limit (step S80: Yes), the data analysis device 30 determines that real-time processing cannot be performed, and the processing proceeds to "End". Although not specifically illustrated, in this case, the situation where the number of times the measurement conditions have been adjusted exceeds the upper limit can be displayed on the display device 50.

[0089] On the other hand, when it is determined that the number of adjustments to the measurement conditions is still less than or equal to the upper limit (step S80: No), the data analysis device 30 adjusts the measurement conditions (step S90). Specifically, when the measurement efficiency is less than 1, the data analysis device 30 adjusts the set value of each measurement item to the "set value (optimal condition)" ( Figure 3 When the measurement efficiency is greater than or equal to 1, the data analysis device 30 adjusts the setpoint of each measurement item towards the "setpoint (worst-case condition)". In this case, each measurement item can be prioritized, and the setpoint is adjusted starting with the highest priority measurement item based on the measurement efficiency.

[0090] The methods for adjusting measurement conditions are not limited to this one; various methods can be used. For example, by using the setpoint of each measurement item as a design variable, the normalized deviation of the setpoint of the optimal or desired conditions from the normalized deviation of each measurement item at that moment can be used as the target variable. Then, optimization techniques such as the steepest descent method can be used to adjust the design variable to bring the target variable close to 0.

[0091] Then, the data analysis device 30 determines whether the set value of the adjusted measurement conditions is included within the specified adjustment range (step S100). The specified adjustment range refers to, for example... Figure 3The range shown is from "Set value (worst condition)" to "Set value (best condition)". When it is determined that the set value of the measurement condition is included within the specified adjustment range (step S100: Yes), the data analysis device 30 sets the measurement conditions adjusted in step S90 for the data measurement device 20 (step S140). After the measurement conditions are set, the process returns to... Figure 6 Step S30 involves performing analysis and processing based on the adjusted measurement data.

[0092] When it is determined in step S100 that the set value of the measurement condition is not included in the specified adjustment range (step S100: No), the data analysis device 30 sets the analysis conditions. In other words, the data analysis device 30 refers to the analysis level setting table contained in the calculation condition file 32. Figure 4 Based on step S60 ( Figure 6 The analysis level is set based on the measurement efficiency calculated in the step S110.

[0093] Then, the data analysis device 30 acquires the diagnostic result (diagnostic level) from the diagnostic device 40 (step S120). Then, the data analysis device 30 refers to the calculation condition file 32 ( Figure 5 The analysis processing setting table contained in the data analysis device 30 sets the analysis conditions for analysis processing based on the analysis level set in step S110 and the diagnostic level obtained in step S120 (step S130). Specifically, the data analysis device 30 refers to the analysis processing setting table ( Figure 5 The analysis process then proceeds to step S140, where the adjusted measurement conditions from step S90 are set based on the analysis and diagnostic levels. The calculation type (such as RMS calculation, FFT calculation, CF calculation) and calculation parameters (passband of the BPF for the measurement data) are then defined.

[0094] As described above, in this embodiment, measurement conditions (for each measurement item) are set based on measurement efficiency determined according to the time required for analysis and diagnostic processing. Analysis conditions (analysis calculation type) are also set based on the analysis level set according to measurement efficiency. As a result, measurement and analysis conditions can be set such that the time required for analysis and diagnostic processing does not exceed the measurement interval of the measurement data. Therefore, according to this embodiment, real-time processing can be ensured.

[0095] In this embodiment, when the measurement conditions are not included in the specified adjustment range (e.g., the range from the set value (worst-case condition) to the set value (best-case condition)... Figure 3 When the measurement is within the specified range, the analysis conditions (calculation type) are set according to the analysis level corresponding to the measurement efficiency. Therefore, according to this embodiment, as long as the measurement conditions are included within the adjustment range, the analysis conditions (calculation type) will not be changed unnecessarily.

[0096] It should be understood that the embodiments disclosed herein are presented for illustrative purposes and are not limiting in any way. Therefore, the scope of the invention is intended to be defined by the claims, and not only by the foregoing embodiments, and includes all modifications and variations that are equivalent in meaning and scope to the claims.

[0097] Label Explanation

[0098] 10 Sensor unit; 20 Data measurement device; 30 Data analysis device; 32 Calculation condition file; 34 Calculator; 36 Calculation controller; 40 Diagnostic device; 42 Diagnostic condition file; 44 Diagnostic unit; 50 Display device; 60 Communication system.

Claims

1. A status monitoring system for monitoring the status of facilities, characterized in that, include: A sensor, which is attached to the facility; A data measurement device that receives the detection signal from the sensor and acquires measurement data from the detection signal according to the provided measurement conditions; A data analysis device that receives the measurement data from the data measurement device and performs analysis processing on the measurement data; as well as A diagnostic device that performs diagnostic processing to diagnose the condition of the facility based on the analysis results obtained through the analysis processing. The data analysis device sets the measurement conditions and analysis conditions for the analysis process based on the time required for the analysis and diagnostic processes. The data analysis device sets the measurement conditions based on measurement efficiency, which represents the relationship between the measurement interval of the measurement data in the data measurement device and the time required for the analysis and diagnostic processing. The data analysis device sets the measurement conditions and the analysis conditions so that the time required for the analysis and diagnostic processing does not exceed the measurement interval of the measurement data. The measurement interval is equivalent to the transmission interval from the data measurement device to the data analysis device when sending the measurement data.

2. The status monitoring system as described in claim 1, characterized in that, The data analysis device sets the analysis conditions based on the measurement efficiency.

3. The status monitoring system as described in claim 2, characterized in that, The data analysis device sets the analysis conditions based on the measurement efficiency and the results of the diagnostic processing.

4. The status monitoring system as described in claim 2 or 3, characterized in that, When the measurement conditions set based on the measurement efficiency are not included in the specified adjustment range, the data analysis device sets the analysis conditions.

5. The status monitoring system as described in any one of claims 1 to 3, characterized in that, The sensor includes at least one of a vibration sensor, a temperature sensor, a pressure sensor, a strain sensor, and a load sensor.

6. A data analysis apparatus for performing analysis processing on measurement data received from a data measurement device, the data measurement device being configured to acquire the measurement data from detection signals of sensors attached to a facility based on provided measurement conditions, the data analysis apparatus characterized in that it comprises: A calculator that performs the analytical processing on the measurement data; as well as A computing controller sets the measurement conditions and the analysis conditions of the analysis process based on the analysis processing and the time required for diagnostic processing to diagnose the state of the facility based on the analysis results obtained through the analysis processing. The computing controller sets the measurement conditions based on measurement efficiency, which represents the relationship between the measurement intervals of the measurement data in the data measurement device and the time required for the analysis and diagnostic processes. The computing controller sets the measurement conditions and the analysis conditions so that the time required for the analysis and diagnostic processing does not exceed the measurement interval of the measurement data. The measurement interval is equivalent to the transmission interval from the data measurement device to the data analysis device when sending the measurement data.

7. The data analysis device as described in claim 6, characterized in that, The computational controller sets the analysis conditions based on the measurement efficiency.

8. The data analysis apparatus as described in claim 7, characterized in that, The computational controller sets the analysis conditions based on the measurement efficiency and the results of the diagnostic process.

9. The data analysis apparatus as described in claim 7 or 8, characterized in that, The computing controller sets the analysis conditions when the measurement conditions set based on the measurement efficiency are not included in the specified adjustment range.

10. The data analysis apparatus as described in any one of claims 6 to 8, characterized in that, The sensor includes at least one of a vibration sensor, a temperature sensor, a pressure sensor, a strain sensor, and a load sensor.

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