Analysis system and analysis method

Abstract

To provide an analysis system capable of improving accuracy of predictive maintenance for a maintenance target apparatus that generates vibrations during operation.SOLUTION: An analysis system comprises: a signal acquisition unit that acquires vibration signals detected by sensors attached to a target apparatus during operation; an intensity calculation unit that calculates a plurality of first signal intensities by analyzing the vibration signals; a distance calculation unit that calculates a first Mahalanobis distance in a signal space based on the plurality of first signal intensities at a first time point for a unit space; a data acquisition unit that acquires status data of the target apparatus; an abnormality determination unit that determines whether the target apparatus is abnormal on the basis of the status data when the first Mahalanobis distance is a threshold or longer; and a setting unit that resets the unit space on the basis of a plurality of second signal intensities calculated by analyzing vibration signals acquired during a predetermined period near the first time point when the target apparatus is determined not to be abnormal.SELECTED DRAWING: Figure 14

Description

[Technical Field]

[0001] The present disclosure relates to an analysis system and an analysis method. [Background technology]

[0002] 2. Description of the Related Art Conventionally, a known method for inspecting machinery for abnormalities is to determine whether or not an abnormality exists in a machine by detecting a signal caused by abnormal vibrations during operation of the machine.

[0003] For example, the vibration analysis system disclosed in International Publication No. 2022 / 065103 (Patent Document 1) is configured to calculate multiple signal intensities by analyzing vibration signals corresponding to an object, and to predict when an abnormality will occur in the object based on the Mahalanobis distance of a signal space composed of multiple signal intensities relative to a predetermined unit space. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2022 / 065103 Summary of the Invention [Problem to be solved by the invention]

[0005] The vibration analysis system disclosed in Patent Document 1 outputs warning information to warn of an abnormality in a target device (e.g., a pump) when the Mahalanobis distance between the signal space and the unit space is large. However, when vibrations (disturbances) caused by sources other than the pump accumulate due to equipment replacement near the pump, for example, the Mahalanobis distance between the signal space based on the vibration signal affected by the disturbance and the reference unit space becomes large. In this case, warning information is output even though there is no need to immediately maintain the pump, making it impossible to perform highly accurate predictive maintenance.

[0006] An object in one aspect of the present disclosure is to provide an analysis system and an analysis method that can improve the accuracy of predictive maintenance for equipment that generates vibrations during operation and that is subject to maintenance. [Means for solving the problem]

[0007] An analysis system according to one embodiment includes a signal acquisition unit that acquires a vibration signal detected by a sensor attached to a target device in operation; an intensity calculation unit that calculates a first plurality of signal intensities corresponding to a plurality of frequency bands by analyzing the vibration signal corresponding to the target device; a distance calculation unit that calculates a first Mahalanobis distance of the signal space based on the first plurality of signal intensities at a first time relative to a predetermined unit space; a data acquisition unit that acquires status data regarding the operating status of the target device; an abnormality determination unit that, if the first Mahalanobis distance is greater than or equal to a threshold, determines whether or not there is an abnormality in the target device based on the status data; and, if it is determined that the target device is not abnormal, a setting unit that resets the unit space based on a second plurality of signal intensities corresponding to a plurality of frequency bands calculated by analyzing vibration signals acquired during a predetermined period around the first time.

[0008] Preferably, the intensity calculation unit calculates a third plurality of signal intensities corresponding to the plurality of frequency bands by analyzing the vibration signals acquired after the first time. The distance calculation unit calculates a second Mahalanobis distance of the signal space based on the third plurality of signal intensities for the unit space reset by the setting unit. If the second Mahalanobis distance is equal to or greater than a threshold, the abnormality determination unit determines whether or not there is an abnormality in the target device based on the status data.

[0009] Preferably, the target device is a pump, and the status data includes at least one of a pressure of a fluid discharged by the pump, a current value for driving the pump, a frequency for driving the pump, and a temperature of a housing of the pump.

[0010] Preferably, the abnormality determination unit determines that the pump is abnormal if at least one of the following conditions is met: a first condition that the pressure is less than a first reference value; a second condition that the current value is equal to or greater than a second reference value; a third condition that the frequency is equal to or greater than a third reference value; and a fourth condition that the temperature is equal to or greater than a fourth reference value.

[0011] Preferably, the predetermined unit space is a first unit space configured by a plurality of signal intensities respectively corresponding to a plurality of frequency bands, calculated by analyzing a vibration signal corresponding to the target device in a normal state. The distance calculation unit calculates, as the first Mahalanobis distance, the Mahalanobis distance of a signal space configured by a first plurality of signal intensities at a first time with respect to the first unit space.

[0012] Preferably, the predetermined unit space is a second unit space configured with two-dimensional centroid data indicating the centroid positions of a plurality of signal intensities corresponding to a plurality of frequency bands, calculated by analyzing a vibration signal corresponding to the target device in a normal state. The distance calculation unit calculates, as the first Mahalanobis distance, the Mahalanobis distance of a signal space configured with the two-dimensional centroid data at the first time with respect to the second unit space.

[0013] Preferably, the analysis system further includes an output control unit that outputs warning information when it is determined that the target device is abnormal.

[0014] Preferably, when the first Mahalanobis distance is equal to or greater than a threshold, the output control unit displays the first Mahalanobis distance on the display in a display mode different from that when the first Mahalanobis distance is less than the threshold.

[0015] An analysis method according to another embodiment includes the steps of acquiring a vibration signal detected by a sensor attached to a target device in operation, calculating a first plurality of signal intensities corresponding to a plurality of frequency bands by analyzing the vibration signal corresponding to the target device, calculating a first Mahalanobis distance of the signal space based on the first plurality of signal intensities at a first time for a predetermined unit space, acquiring status data regarding the operating state of the target device, and if the first Mahalanobis distance is greater than or equal to a threshold, determining whether or not there is an abnormality in the target device based on the status data, and if it is determined that there is no abnormality in the target device, resetting the unit space based on a second plurality of signal intensities corresponding to a plurality of frequency bands calculated by analyzing vibration signals acquired during a predetermined period around the first time. [Effects of the Invention]

[0016] According to the present disclosure, it is possible to improve the accuracy of predictive maintenance for equipment that generates vibrations during operation and is subject to maintenance. [Brief explanation of the drawings]

[0017] [Figure 1] FIG. 1 is a diagram illustrating an overview of a system. [Figure 2] 1 is a block diagram illustrating an example of the overall configuration of an analysis system. [Figure 3] FIG. 2 is a block diagram illustrating an example of a hardware configuration of the analysis device. [Figure 4] 10 is a flowchart illustrating an example of a preparation process. [Figure 5] FIG. 10 is a diagram illustrating an example of a data set of signal strengths for each frequency band. [Figure 6] FIG. 10 is a diagram illustrating an example of a data set of center of gravity positions. [Figure 7] 10 is a flowchart illustrating an example of an analysis process. [Figure 8] 10 is a flowchart showing an example of a first abnormality determination step. [Figure 9]FIG. 10 is a diagram illustrating an example of a data set of status data. [Figure 10] 10 is a flowchart illustrating an example of a unit space resetting process. [Figure 11] FIG. 10 is a diagram showing changes over time in Mahalanobis distance and discharge pressure. [Figure 12] 10 is a flowchart showing an example of a second abnormality determination step. [Figure 13] FIG. 10 is a diagram illustrating an example of the layout of a user interface screen. [Figure 14] FIG. 2 is a functional block diagram of the analysis device. DETAILED DESCRIPTION OF THE INVENTION

[0018] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In the following description, the same components are denoted by the same reference numerals. The names and functions of the components are also the same. Therefore, detailed description thereof will not be repeated.

[0019] <System configuration> Fig. 1 is a diagram for explaining an overview of system 1000. Referring to Fig. 1, system 1000 is a system for determining whether or not an abnormality exists in a maintenance target device such as a pump (hereinafter also simply referred to as "target device") by analyzing vibration signals generated during operation of the target device, and for performing predictive maintenance of the target device. Predictive maintenance is the detection of any abnormality occurring in the maintenance target device and performing work such as servicing or replacing parts before the maintenance target device reaches a state where it must be stopped.

[0020] In the following description, the target device is assumed to be a pump, but the present invention is not limited to this, and the system 1000 can be applied to any target device that generates vibrations (or sounds) during operation. For example, the system 1000 can also be applied to determining abnormalities in a motor, a part that vibrates due to vibrations from a vibrating body, etc.

[0021] The system 1000 includes an analysis system 100, a plurality of sensors 30, a terminal device 40, a network 50, a monitoring device 60, and a plurality of pumps 70. The analysis system 100 performs vibration analysis of the pump 70. The analysis system 100 includes an analysis device 10 and a sensor unit 20. The sensor unit 20 is electrically connected to the plurality of sensors 30. In the system 1000, two sensor units 20 are connected to the analysis device 10, but three or more sensor units 20, or one sensor unit 20, may be connected to the analysis device 10. Each sensor unit 20 may be electrically connected to one sensor 30. Each sensor unit 20 may be electrically connected to a plurality of sensors 30 attached to the plurality of pumps 70, respectively.

[0022] The sensor 30 is attached to the pump 70 and acquires a detection signal (vibration signal) detected due to vibration or sound of the pump. The analysis device 10 performs vibration analysis of the pump 70 based on the vibration signal input from the sensor 30 via the sensor unit 20.

[0023] The monitoring device 60 monitors status data related to the operating state of the pump 70. The status data includes at least one of the pressure of the fluid discharged by the pump 70 (hereinafter also referred to as "discharge pressure J1"), the current value J2 for driving the pump 70, the frequency J3 for controlling the output of the pump 70, and the temperature J4 of the housing of the pump 70. Typically, the discharge pressure J1, the current value J2, the frequency J3, and the temperature J4 are measured by various measuring devices (e.g., a pressure sensor, a current sensor, a frequency meter, a temperature sensor) provided in the pump 70. The monitoring device 60 receives the status data measured by the various measuring devices. The status data is data for directly checking for an abnormality in the pump 70. Therefore, if the status data is an abnormal value, there is a high possibility that a substantial abnormality has occurred in the pump 70.

[0024] The analysis device 10 is configured to be able to communicate with the monitoring device 60, and acquires (receives) status data from the monitoring device 60. The analysis device 10 performs an abnormality determination for the pump 70 based on the vibration analysis results and status data of the pump 70. Details of the abnormality determination method will be described later. The analysis device 10 is configured to be able to communicate with the terminal device 40 via the network 50. The analysis device 10 transmits the analysis results, determination results, etc. to the terminal device 40.

[0025] The analysis device 10 typically has a structure conforming to a general-purpose computer architecture, and performs various processes described below by executing pre-installed programs with a processor. The analysis device 10 is, for example, a laptop PC (Personal Computer). However, the analysis device 10 may be any other device (for example, a desktop PC or a tablet terminal device) that is capable of executing the functions and processes described below.

[0026] The network 50 includes various networks such as the Internet, etc. The network 50 may employ a wired communication system, or may employ other wireless communication systems such as a wireless LAN (local area network).

[0027] The terminal device 40 is, for example, a portable tablet terminal device, but is not limited to this and may be realized as a smartphone, a desktop PC (Personal Computer), or the like.

[0028] 1, analysis system 100 is configured as a separate device in which analysis device 10 and sensor unit 20 are separate, but analysis system 100 may also be configured as an integrated device in which analysis device 10 and sensor unit 20 are integrated. Furthermore, analysis device 10 and monitoring device 60 may also be configured as an integrated device. In this case, analysis device 10 has the above-mentioned functions of monitoring device 60 and directly receives status data measured by various measuring instruments.

[0029] 2 is a block diagram showing an example of the overall configuration of analysis system 100. Referring to FIG. 2, analysis system 100 includes an analysis device 10 and a sensor unit 20.

[0030] The sensor 30 connected to the sensor unit 20 is a sensor capable of detecting vibration and sound signals, and is configured, for example, by an acceleration sensor using an organic piezoelectric element. Note that the sensor 30 may be any sensor capable of detecting vibration and sound signals, and may be configured as an acceleration sensor of another type (for example, a servo type) or may be configured as various other sensors.

[0031] If the signal obtained by the sensor 30 is a charge signal, a charge converter is provided between the sensor 30 and the analysis system 100. In this case, the charge converter converts the charge signal from the sensor 30 into a voltage signal and outputs it to the analysis system 100. Note that if the sensor 30 has the function of converting a charge signal into a voltage signal, the charge converter is not necessary.

[0032] The sensor unit 20 converts the vibration signal acquired from the sensor 30 (or a charge converter) into a signal that can be processed by the analysis device 10. Specifically, the sensor unit 20 includes a filter 21, an amplifier 22, and an A / D converter 23.

[0033] The filter 21 is an analog filter that removes noise components from the vibration signal output from the sensor 30. The filter 21 is configured by a low-pass filter, a high-pass filter, and the like.

[0034] The amplifier 22 amplifies the analog signal output from the filter 21 by a predetermined factor and outputs the amplified signal to the A / D converter 23 .

[0035] The A / D converter 23 converts the signal input from the amplifier 22 from an analog signal to a digital signal at a predetermined sampling frequency, and outputs the digitally converted signal to the analysis device 10.

[0036] Fig. 3 is a block diagram showing an example of the hardware configuration of analysis device 10. Referring to Fig. 3, analysis device 10 includes processor 101, memory 103, display 105, input device 107, signal input interface (I / F) 109, and communication interface (I / F) 111. These components are connected to each other so as to be able to communicate data with each other.

[0037] Processor 101 is typically an arithmetic processing unit such as a CPU (Central Processing Unit), an MPU (Multi Processing Unit), etc. Processor 101 controls the operation of each part of analysis device 10 by reading and executing a program stored in memory 103. More specifically, processor 101 realizes each function of analysis device 10 by executing the program.

[0038] The memory 103 is realized by a random access memory (RAM), a read-only memory (ROM), a flash memory, a hard disk, etc. The memory 103 stores programs executed by the processor 101, etc.

[0039] Display 105 is, for example, a liquid crystal display, an organic EL (Electro Luminescence) display, etc. Display 105 may be configured integrally with analysis device 10, or may be configured separately from analysis device 10.

[0040] The input device 107 accepts operation inputs to the analysis device 10. The input device 107 is realized by, for example, a keyboard, buttons, a mouse, etc. The input device 107 may also be realized as a touch panel.

[0041] The signal input interface 109 mediates data transmission between the processor 101 and the sensor unit 20. The signal input interface (I / F) 109 accepts input of a vibration signal from the sensor 30 via the sensor unit 20. Specifically, the signal input interface 109 accepts input of a digital signal from the A / D converter 23.

[0042] The communication interface 111 mediates data transmission between the processor 101 and the terminal device 40, monitoring device 60, etc. As a communication method, for example, a wireless communication method such as Bluetooth (registered trademark) or wireless LAN (Local Area Network) is used. Note that a wired communication method such as USB (Universal Serial Bus) may also be used as the communication method.

[0043] <Abnormality determination method> The abnormality determination method according to this embodiment will be described below. The abnormality determination method includes a preparation step of preparing reference data and an analysis step of analyzing the abnormal state of the pump 70.

[0044] (preparation process) In the preparation step according to this embodiment, for example, the vibration state of the pump 70 is measured at the beginning of operation. Because the pump 70 is in a brand new state at the beginning of operation, the vibration state of the pump 70 in a normal state is measured as a reference. However, instead of the pump 70, a pump of the same type as the pump 70 in a normal state may be separately prepared, and the vibration state of that pump may be measured as a reference.

[0045] 4 is a flowchart showing an example of the preparation process. Typically, the following steps are realized by processor 101 of analysis device 10 executing a program stored in memory 103.

[0046] 4, the processor 101 acquires a vibration signal output from the sensor 30 via the sensor unit 20 (step S10). Specifically, the processor 101 acquires a vibration signal corresponding to the pump 70 in a normal state (a vibration signal indicating the vibration state of the pump 70) from the sensor 30.

[0047] The processor 101 performs octave analysis on the vibration signals accumulated for a predetermined time (e.g., several tens to several hundreds of milliseconds) (step S12). In this embodiment, 1 / 3 octave analysis is used. Therefore, each vibration signal is separated into 48 bands, for example, from 0.4 Hz to 20 kHz, by a 1 / 3 band-pass filter, and the signal strength (vibration strength) is averaged for each band (i.e., frequency band). In the following description, the signal strength averaged in a frequency band is also simply referred to as the "signal strength of the frequency band."

[0048] For each frequency band, the processor 101 stores the signal strength of the frequency band corresponding to the pump 70 in a normal state as reference data R1 in the memory 103 (step S14).

[0049] FIG. 5 is a diagram showing an example of a data set of signal strengths of each frequency band. Referring to FIG. 5, data set 310 includes signal strength L of each frequency band f1 to fn (where n is a natural number) for each time T1 to Tm (where m is a natural number). If each vibration signal is separated into 48 bands, n=48. For example, data set 310 includes signal strengths L1_1 to L1_n of each frequency band f1 to fn at time T1, and signal strengths Lm_1 to Lm_n of each frequency band f1 to fn at time Tm. Reference data R1 includes, for example, signal strength L of each frequency band f1 to fn at each time T1 to Tx. In this case, the period from time T1 to Tx corresponds to the initial operation period.

[0050] 4 again, the processor 101 sets a unit space U1 in the Mahalanobis-Taguchi method (MT method) using the reference data R1 (step S16). Specifically, the processor 101 sets data on the signal strength L of each of the frequency bands f1 to fn at each of the times T1 to Tx as the unit space U1. The unit space U1 is used in a first abnormality determination step, which will be described later.

[0051] The processor 101 calculates two-dimensional centroid data indicating the centroid position of the signal strength of each frequency band (step S18). Specifically, the processor 101 generates the data set shown in FIG.

[0052] Fig. 6 is a diagram showing an example of a data set of center of gravity positions. Referring to Fig. 6, the data set 320 includes a center of gravity position Gx of the frequency band and a center of gravity position Gy of the signal intensity for times T1 to Tm. Two-dimensional center of gravity data (center of gravity positions Gx, Gy) is generated for each of times T1 to Tm. The center of gravity position Gx is expressed by the following equation (1), and the center of gravity position Gy is expressed by the following equation (2).

[0053]

number

[0054]

number

[0055] f i represents the i-th frequency band, and L irepresents the signal strength of the i-th frequency band, and S represents the sum of the signal strengths of all frequency bands. Using equations (1) and (2), dataset 320 consisting of two-dimensional data (center of gravity positions Gx, Gy) is generated from dataset 310 consisting of n-dimensional (multidimensional) data (signal strength L of each frequency band f1 to fn). In dataset 320, for example, the center of gravity positions Gx, Gy at time T1 are represented by center of gravity positions Gf_1, GL_1, respectively, and the center of gravity positions Gx, Gy at time Tm are represented by center of gravity positions Gf_m, GL_m, respectively.

[0056] 4, the processor 101 sets a unit space U2 in the MT method using the center of gravity data in the initial period after the start of operation (for example, from time T1 to Tx) (step S20). Specifically, the processor 101 sets the two-dimensional center of gravity data (center of gravity positions Gx, Gy) at each of the times T1 to Tx as the unit space U2. The unit space U2 is used in a second abnormality determination step, which will be described later.

[0057] (Analysis process) The analysis step includes a first abnormality determination step and a second abnormality determination step for determining whether or not the pump 70 has an abnormality.

[0058] 7 is a flowchart showing an example of the analysis step. Referring to FIG. 7, the processor 101 acquires a vibration signal output from the sensor 30 via the sensor unit 20 (step S30). Specifically, the processor 101 acquires a vibration signal corresponding to the pump 70 during a normal period (for example, an operating period after the end of an initial operation period) from the sensor 30.

[0059] The processor 101 performs octave analysis on the vibration signals accumulated for a predetermined time (step S32). The processor 101 stores, for each frequency band, the signal strength of that frequency band corresponding to the pump 70 in the memory 103 (step S34). Specifically, the signal strength of each frequency band in the pump 70 at a certain time Ts is stored in the form of a data set 310. Here, a series of signal strengths Ls_1 to Ls_n of frequency bands f1 to fn in the pump 70 at time Ts is also referred to as signal strength data Ps. Note that the period from time T1 to Tx corresponds to the initial period of operation, and therefore the normal period corresponds to the period from time Tx+1 to time Tm. Therefore, time Ts is any one of time Tx+1 to time Tm.

[0060] The processor 101 executes a first abnormality determination step (step S40) and a second abnormality determination step (step S50) using the signal strength data Ps and the data obtained in the preparation step. These steps may be executed in parallel or sequentially.

[0061] [First abnormality determination process] Fig. 8 is a flowchart showing an example of the first abnormality determination step. In the first abnormality determination step, a data set 310 formed of multidimensional data is used. Referring to Fig. 8, processor 101 calculates a Mahalanobis distance MD1 of a signal space X1s formed of a plurality of signal intensities with respect to unit space U1 set in step S16 of Fig. 4 (step S41). Signal space X1s is formed of a plurality of signal intensities Ls_1 to Ls_n (i.e., signal intensity data Ps) at time Ts.

[0062] The processor 101 determines whether the Mahalanobis distance MD1 is equal to or greater than a threshold value Th1 (for example, 4) (step S42). If the Mahalanobis distance MD1 is less than the threshold value Th1 (NO in step S42), the processor 101 ends the first abnormality determination step. If the Mahalanobis distance MD1 is equal to or greater than the threshold value Th1 (YES in step S42), the processor 101 acquires status data relating to the operating status of the pump 70 from the monitoring device 60 (step S43).

[0063] 9 is a diagram showing an example of a data set of status data. Referring to FIG. 9, data set 330 includes status data D1 to Dp (where p is a natural number) for each of times t1 to tg (where g is a natural number). In data set 330, status data D1 to Dp at time t1 is represented by status data D1_1 to Dp_1, respectively, and status data D1 to Dp at time tg is represented by status data D1_g to Dp_g, respectively. For example, status data D1, D2, D3, and D4 are the discharge pressure J1, current value J2, frequency J3, and temperature J4 of pump 70, respectively.

[0064] The processor 101 receives a data set 330 including status data for a certain period in the past (for example, the period from time t1 to tg) from the monitoring device 60. The processor 101 does not have to receive the status data in the format of the data set 330. For example, the processor 101 may be configured to specify specific status data (for example, status data D2_3 at time t3) and receive the status data.

[0065] 8, the processor 101 determines whether the status data is normal (step S44). For example, assume that the status data is a discharge pressure J1. In this case, the processor 101 determines that the status data (i.e., the discharge pressure J1) is normal if the discharge pressure J1 is equal to or greater than the reference value E1, and determines that the status data is not normal (i.e., abnormal) if the discharge pressure J1 is less than the reference value E1.

[0066] For example, if the pump 70 does not have a control mechanism, the discharge pressure of the pump 70 operating at rated pressure under certain conditions is an indicator of the pump's capacity. Therefore, a decrease in discharge pressure indicates a lack of pump capacity. On the other hand, if the pump 70 has a control mechanism and is controlled to discharge a constant pressure, the discharge pressure is kept constant by varying the control value (current, frequency, etc.) for controlling the discharge pressure. However, if the control value deviates from the control range due to an abnormality in the pump 70, the discharge pressure will decrease. Therefore, regardless of whether the pump 70 has a control mechanism or not, if the discharge pressure of the pump 70 decreases and falls below the reference value E1, it is considered that an abnormality has occurred in the pump 70.

[0067] If the status data is abnormal (NO in step S44), the processor 101 determines that some abnormality has occurred in the pump 70, and outputs an abnormality alert (step S45). Typically, the abnormality alert is displayed on the display 105. The abnormality alert may also be configured to be output as audio via a speaker.

[0068] On the other hand, if the status data is normal (YES in step S44), the processor 101 determines that no abnormality has occurred in the pump 70 (i.e., the pump 70 is in a normal state), and resets (updates) the unit space U1 that was previously set in the preparation process (step S46).

[0069] Fig. 10 is a flowchart showing an example of a unit space resetting step. Referring to Fig. 10, the processor 101 selects a signal strength L to be used for resetting the unit space U1 (step S102). Specifically, the processor 101 selects a signal strength L obtained by analyzing a vibration signal acquired during a predetermined period Y around time Ts.

[0070] Here, the processor 101 executes a process of determining whether the Mahalanobis distance MD1 of the signal space X1s at time Ts relative to the unit space U1 set in step S16 is equal to or greater than the threshold value Th1 (YES in step S43) and whether the status data is normal (YES in step S44), and then executes a process of resetting the unit space U1 (step S46). The predetermined period Y is set to, for example, a fixed period from time T(sa×n) to time T(s+a×n). For example, a=50.

[0071] As an example, in consideration of a case where the vibration signal changes suddenly around time Ts, the predetermined period Y is set to a fixed period after time Ts. For example, the predetermined period Y is the period from time Ts to time T(s+5×n) (a period of "5×n"). In this case, in step S102, the processor 101 selects the signal strength L of each of the frequency bands f1 to fn at each of times Ts to T(s+5×n) as the signal strength L for resetting the unit space U1.

[0072] As another example, if the vibration signal gradually changes around time Ts, the predetermined period Y may be set to a certain period before time Ts. In this case, for example, the predetermined period Y is the period from time T(s-5×n) to time Ts. As yet another example, the predetermined period Y may be set to a period before and after time Ts. In this case, for example, the predetermined period Y is the period from time T(sh) to time T(s+5×nh), where "h" is a natural number satisfying h<5×n.

[0073] The predetermined period Y can be changed by the user as needed. Subsequently, the processor 101 stores the selected signal strength L as new reference data R2 in the memory 103 (step S104). The processor 101 resets the unit space U1 using the reference data R2 (step S106). For example, the processor 101 sets the data of the signal strength L of each of the frequency bands f1 to fn at each of the times Ts to T(s+5×n) as the new unit space U1. Hereinafter, the reset unit space U1 will also be referred to as a "unit space U1x."

[0074] Here, the reason for executing the above-mentioned resetting process of the unit space U1 will be explained in detail. FIG. 11 is a diagram showing the time changes of the Mahalanobis distance and the discharge pressure. The horizontal axis of FIG. 11 indicates time (for example, times "1" to "10000"), the vertical axis on the left indicates the Mahalanobis distance MD1, and the vertical axis on the right indicates the discharge pressure as status data. FIG. 11 shows an example in which a pump 70 that was already operating at the initial point in time (i.e., time "1") breaks down (ends of life) around time "10000". Here, a case will be explained in which the status data is the discharge pressure J1, but the status data may also be a current value J2, a frequency J3, or a temperature J4.

[0075] Referring to Fig. 11, graph 401 shows the Mahalanobis distance MD1 (hereinafter also referred to as "Mahalanobis distance MD1_1") between the initial unit space U1 and the signal space at each time. Graph 402 shows the Mahalanobis distance MD1 (hereinafter also referred to as "Mahalanobis distance MD1_2") between the reset unit space U1x and the signal space at each time. Graph 403 shows the discharge pressure when the initial point in time is "1".

[0076] In the example of FIG. 11, the threshold value Th1 of the Mahalanobis distance MD1 is set to "6". The reference value E1 of the discharge pressure is set to "0.8". When the discharge pressure becomes 0.7 or less, it is determined that the pump 70 has failed. At the initial point in time, it is assumed that an initial unit space U1 (for example, the unit space U1 set in step S16 of the preparation process) is set.

[0077] Between approximately time "1400" and time "3000", the Mahalanobis distance MD1_1 rises sharply. Specifically, around time "2500", the Mahalanobis distance MD1_1 exceeds the threshold value Th1, indicating an abnormal value. At this time, the discharge pressure remains above the reference value E1 and is within the normal range. In such a case, the vibration state of the pump 70 has changed for some reason, resulting in an increase in the Mahalanobis distance MD1_1, but the pump performance is considered to be normal.

[0078] Therefore, the processor 101 determines that the pump 70 is maintaining a normal state (is not abnormal), and resets the unit space U1 using the signal strength L for a predetermined period Y after time "2500". The processor 101 sets, for example, the signal strength L from time "2500" to time "2740" (i.e., the predetermined period Y) as the reset unit space U1x. By using the reset unit space U1x, the processor 101 calculates the Mahalanobis distance MD1_2 based on the state after the change in the vibration state of the pump 70.

[0079] The Mahalanobis distance MD1_2 of the signal space at each time relative to the unit space U1x is shown from around time "2900" onwards. As shown in Fig. 11, the Mahalanobis distance MD1_2 is the Mahalanobis distance based on the unit space U1x after the change in the vibration state, and therefore it can be seen that it is smaller than the Mahalanobis distance MD1_1 based on the unit space U1.

[0080] As time passes, the discharge pressure of the pump 70 gradually decreases and falls below the reference value E1 around time "6100", but this does not pose a practical problem and the pump 70 continues to operate. No increase in the Mahalanobis distance MD1_2 can be confirmed around time "6100".

[0081] After the time "8000", the Mahalanobis distance MD1_2 increases sharply. Specifically, around the time "9000", the Mahalanobis distance MD1_2 exceeds the threshold value Th1, indicating an abnormal value. Also, around the time "9000", the discharge pressure is less than the reference value E1, and the pump performance is considered to be insufficient. In this way, since the Mahalanobis distance MD1_2 exceeds the threshold value Th1 and the discharge pressure is less than the reference value E1, the processor 101 determines that an abnormality has occurred in the pump 70. Note that, referring to the graph 401 around the time "9000", although the Mahalanobis distance MD1_1 tends to increase, this change becomes less apparent. Then, around the time "10000", the pump 70 begins to malfunction.

[0082] As described above, according to the abnormality determination method that determines an abnormality in the pump 70 using the Mahalanobis distance MD1_2 for the reset unit space U1x and the discharge pressure, the abnormality can be determined shortly before the timing at which a sudden failure of the pump 70 occurs (for example, around time "9000").

[0083] On the other hand, for example, when an abnormality determination method using only the Mahalanobis distance MD1_1 based on the initial unit space U1 is adopted, it is conceivable to determine an abnormality in the pump 70 at the time when the Mahalanobis distance MD1_1 becomes equal to or greater than the threshold value Th1 (for example, around time "2500"). However, at this time, no substantial abnormality has occurred in the pump 70, and it is too early to perform maintenance on the pump 70, so this is not appropriate.

[0084] Furthermore, when an abnormality determination method using the Mahalanobis distance MD1_1 and the discharge pressure is adopted, it is conceivable to determine that an abnormality has occurred in the pump 70 when the Mahalanobis distance MD1_1 is equal to or greater than the threshold value Th1 and the discharge pressure is less than the reference value E1 (for example, around time "6100"). At this time, although the pump 70 has deteriorated, it is still in a state where it can operate normally. Therefore, it is considered that the timing for maintaining the pump 70 is somewhat early.

[0085] Note that, when an abnormality determination method using only the discharge pressure without using the Mahalanobis distance is adopted, it is conceivable to determine an abnormality in the pump 70 when the discharge pressure falls below the reference value E1 (for example, around time "6100") or when the discharge pressure falls below a limit value (for example, 0.7) (for example, around time "10000"). When an abnormality in the pump 70 is determined when the discharge pressure falls below the reference value E1, as described above, this time is somewhat too early for the timing to perform maintenance on the pump 70. Furthermore, when an abnormality in the pump 70 is determined when the discharge pressure falls below the limit value, it is highly likely that the pump 70 has already broken down (or is about to break down) at that time, and therefore this time is too late for the timing to perform maintenance on the pump 70.

[0086] Therefore, according to the abnormality determination method of this embodiment based on the Mahalanobis distance MD1_2 and the discharge pressure, an abnormality can be determined shortly before a failure occurs, allowing the pump 70 to operate for a longer period of time and enabling maintenance of the pump 70 to be performed before a sudden failure occurs. In other words, it is possible to improve the accuracy of predictive maintenance of the pump 70.

[0087] [Second abnormality determination process] 12 is a flowchart showing an example of the second abnormality determination step. Referring to FIG. 12, the processor 101 calculates two-dimensional centroid data indicating the centroid position of the signal strength of each frequency band (step S51). Specifically, the processor 101 calculates the two-dimensional centroid data (i.e., centroid positions Gx, Gy) from the signal strength data Ps stored in step S34 of FIG. 7 using equations (1) and (2).

[0088] The processor 101 calculates the Mahalanobis distance MD2 of the signal space X2s composed of two-dimensional center of gravity data with respect to the unit space U2 set in step S20 of Fig. 4 (step S52). The signal space X2s is composed of center of gravity positions Gx, Gy (i.e., Gf_s, GL_s) at time Ts.

[0089] Processor 101 determines whether Mahalanobis distance MD2 is greater than or equal to threshold value Th2 (e.g., 4) (step S53). If Mahalanobis distance MD2 is less than threshold value Th2 (NO in step S53), processor 101 terminates the second abnormality determination step. If Mahalanobis distance MD2 is greater than or equal to threshold value Th2 (YES in step S53), processor 101 executes processing of step S54. Note that the processing of steps S54, S55, and S56 is similar to the processing of steps S43, S44, and S45 in FIG. 8, respectively, and therefore detailed description thereof will not be repeated.

[0090] If the status data is normal (YES in step S55), the processor 101 resets (updates) the unit space U2 set in the preparation step (step S57). The method for resetting the unit space U2 is basically the same as the method for resetting the unit space U1 described in FIG.

[0091] Specifically, the processor 101 selects two-dimensional center of gravity data (center of gravity positions Gx, Gy) obtained by analyzing vibration signals acquired during a predetermined period Y around time Ts. For example, the processor 101 selects the center of gravity data (center of gravity positions Gx, Gy) for each of times Ts to T(s+5×n) as center of gravity data for resetting the unit space U2. The processor 101 sets the selected two-dimensional center of gravity data for each of times Ts to T(s+5×n) as the unit space U2x after resetting.

[0092] According to the second abnormality determination process, similarly to the first abnormality determination process described above, it is possible to improve the accuracy of predictive maintenance for the pump 70 as described with reference to FIG.

[0093] <Screen example> 13 is a diagram showing an example layout of user interface screen 500. However, user interface screen 500 may have any layout other than that shown in FIG. 13 as long as it can realize the functions described below.

[0094] 13, a user interface screen 500 includes display areas 502, 504, and 506, a measurement condition and setting value display area 514, various buttons 516, display areas 520, 530, and 540, and graphs 550 and 560.

[0095] Display area 502 displays the identification number (unit number) of sensor unit 20, the identification number (sensor number) of sensor 30, the name of the measurement target (e.g., pump), etc. Display area 504 displays the Mahalanobis distance MD1 or MD2 (hereinafter also collectively referred to as "Mahalanobis distance MD") and the status of the abnormality determination result based on the discharge pressure. For example, the status "normal" or "abnormal" is displayed depending on the abnormality determination result.

[0096] The display area 506 displays the value (score) of the Mahalanobis distance MD1 and the score of the Mahalanobis distance MD2. The color of the score changes depending on the calculated score of the Mahalanobis distance MD. For example, if the Mahalanobis distance MD1 is equal to or greater than the threshold value Th1, the score is displayed in a color that evokes "abnormality" (for example, red). On the other hand, if the Mahalanobis distance MD1 is less than the threshold value Th1, the score is displayed in a color that evokes "normality" (for example, black). Note that it is sufficient if the "abnormal" score is emphasized (made more noticeable) than the "normal" score.

[0097] Display area 520 displays time-series sensor data (raw data) detected by sensor 30. Display area 530 displays the analysis results (frequency spectrum) obtained by fast Fourier transform (FFT) analysis of the time-series sensor data. Display area 540 displays signal strength data obtained by 1 / 3 octave analysis of the time-series sensor data in a bar graph. Graph 550 shows time-series data of Mahalanobis distance MD1. Graph 560 shows time-series data of Mahalanobis distance MD2.

[0098] The user can check the status of the pump 70 by visually checking the display areas 504, 506, etc. For example, if the status "Abnormal" is displayed, the user can begin equipment maintenance such as inspection, maintenance, and repair of the pump 70.

[0099] <Functional configuration> 14 is a functional block diagram of analysis device 10. Referring to FIG. 14, analysis device 10 includes, as its main functional components, a signal acquisition unit 202, an intensity calculation unit 204, a setting unit 206, a distance calculation unit 208, a data acquisition unit 210, an abnormality determination unit 212, and an output control unit 214. Each of these functions is realized, for example, by processor 101 of analysis device 10 executing a program stored in memory 103. Note that some or all of these functions may be configured to be realized by hardware.

[0100] The signal acquiring unit 202 acquires a vibration signal detected by the sensor 30 attached to the operating pump 70. Specifically, the signal acquiring unit 202 receives the vibration signal (digital signal) detected by the sensor 30 via the sensor unit 20.

[0101] The intensity calculation unit 204 calculates a plurality of signal intensities corresponding to a plurality of frequency bands by analyzing the vibration signal acquired by the signal acquisition unit 202. Specifically, the intensity calculation unit 204 calculates the signal intensity of each frequency band (for example, signal intensity L of each frequency band f1 to fm) by performing octave analysis (for example, 1 / 3 octave analysis) on the vibration signal corresponding to the pump 70. Note that the intensity calculation unit 204 may be configured to calculate the signal intensity of each frequency band by Fast Fourier Transform (FFT).

[0102] The setting unit 206 sets a unit space based on the plurality of signal intensities calculated by the intensity calculation unit 204. Specifically, the intensity calculation unit 204 calculates a plurality of signal intensities corresponding to a plurality of frequency bands (for example, signal intensity L for each of frequency bands f1 to fn at each of times T1 to Tx) by analyzing a vibration signal corresponding to the pump 70 in a normal state. In one aspect, the setting unit 206 sets a unit space formed by the plurality of signal intensities at each of times T1 to Tx as an initial unit space U1. In another aspect, the setting unit 206 calculates two-dimensional center-of-gravity data indicating the center-of-gravity position of the plurality of signal intensities at each of times T1 to Tx, and sets a unit space formed by the center-of-gravity data as an initial unit space U2.

[0103] The distance calculation unit 208 calculates the Mahalanobis distance of the signal space based on the intensities of multiple signals at a first time (e.g., time Ts) with respect to the unit space using the MT algorithm. For example, the distance calculation unit 208 calculates the Mahalanobis distance MD1 of the signal space X1s with respect to a preset initial unit space U1. The distance calculation unit 208 also calculates the Mahalanobis distance MD2 of the signal space X2s with respect to a preset initial unit space U2.

[0104] The data acquisition unit 210 acquires status data relating to the operating status of the pump 70. The status data includes at least one of the discharge pressure J1, the current value J2, the frequency J3, and the temperature J4.

[0105] The abnormality determination unit 212 determines whether or not there is an abnormality in the pump 70 based on the Mahalanobis distance MD and the status data. In one aspect, the abnormality determination unit 212 determines whether or not the Mahalanobis distance MD1 is equal to or greater than a threshold value Th1. If the Mahalanobis distance MD1 is equal to or greater than the threshold value Th1, the abnormality determination unit 212 determines whether or not there is an abnormality in the pump 70 based on the status data. Specifically, if the status data is normal (for example, if the discharge pressure J1 is equal to or greater than a reference value E1), the abnormality determination unit 212 determines that the pump 70 is normal, and if the status data is abnormal (for example, if the discharge pressure J1 is less than the reference value E1), the abnormality determination unit 212 determines that the pump 70 is abnormal.

[0106] As another example, the abnormality determination unit 212 determines that the pump 70 is normal when the current value J2 is less than the reference value E2, and determines that the pump 70 is abnormal when the current value J2 is equal to or greater than the reference value E2, because the current value increases as the load on the pump 70 increases.

[0107] Furthermore, the abnormality determination unit 212 determines that the pump 70 is normal when the frequency J3 is less than the reference value E3, and determines that the pump 70 is abnormal when the frequency J3 is equal to or greater than the reference value E3. This is because, if the discharge pressure of the pump 70 does not reach the specified pressure for some reason, control to increase the frequency is executed.

[0108] Furthermore, the abnormality determination unit 212 determines that the pump 70 is normal when the temperature J4 is less than the reference value E4, and determines that the pump 70 is abnormal when the temperature J4 is equal to or greater than the reference value E4. This is because when the mechanical load increases due to wear of the pump 70 components, the temperature of the housing rises due to heat generated by poor lubrication.

[0109] From the above, if at least one of the following conditions is met: the first condition that the discharge pressure J1 is less than the reference value E1; the second condition that the current value J2 is equal to or greater than the reference value E2; the third condition that the frequency J3 is equal to or greater than the reference value E3; and the fourth condition that the temperature J4 is equal to or greater than the reference value E4, the abnormality determination unit 212 may determine that the pump 70 is abnormal.

[0110] If it is determined that the pump 70 is not abnormal, the setting unit 206 resets a unit space (e.g., unit spaces U1, U2) based on a plurality of signal intensities corresponding to a plurality of frequency bands during a predetermined period Y around the first time (e.g., a period from time Ts to time T(s+5×n)). The plurality of signal intensities are calculated by the intensity calculation unit 204 analyzing vibration signals acquired during the predetermined period Y. The setting unit 206 sets the plurality of signal intensities during the predetermined period Y (e.g., each of times Ts to T(s+5×n)) as a unit space U1x, and sets two-dimensional center-of-gravity data of the plurality of signal intensities during the predetermined period Y as a unit space U2x.

[0111] Furthermore, the intensity calculation unit 204 calculates a plurality of signal intensities corresponding to a plurality of frequency bands, respectively, by analyzing vibration signals acquired after a first time (e.g., time Ts). The distance calculation unit 208 calculates a Mahalanobis distance MD (e.g., Mahalanobis distance MD1_2) of a signal space based on the plurality of signal intensities for a unit space (e.g., unit space U1x, U2x) reset by the setting unit 206. If the Mahalanobis distance MD is equal to or greater than a threshold, the abnormality determination unit 212 determines whether or not there is an abnormality in the pump 70 based on the status data, as described above.

[0112] When it is determined that the pump 70 is abnormal, the output control unit 214 outputs warning information (for example, an abnormality alert) that warns of the occurrence of an abnormality in the pump 70. Furthermore, when the Mahalanobis distance MD is equal to or greater than a threshold, the output control unit 214 displays the Mahalanobis distance MD on the display 105 in a display mode that is different from when the Mahalanobis distance MD is less than the threshold. For example, when the Mahalanobis distance MD1 is equal to or greater than a threshold Th1, the output control unit 214 displays the Mahalanobis distance MD1 in red, and when the Mahalanobis distance MD1 is less than the threshold Th1, the output control unit 214 displays the Mahalanobis distance MD1 in black.

[0113] <Advantages> According to this embodiment, since an abnormality can be detected shortly before a failure occurs in the pump 70, maintenance of the pump 70 can be performed at a more appropriate timing. As a result, the accuracy of predictive maintenance can be improved.

[0114] <Other embodiments> (1) In the above-described embodiment, a program may be provided that causes a computer to function and execute the control described in the above flowchart. Such a program may be recorded on a non-transitory computer-readable recording medium such as a flexible disk, secondary storage device, main storage device, or memory card attached to the computer and provided as a program product. Alternatively, the program may be recorded on a recording medium such as a hard disk built into the computer and provided. The program may also be provided by downloading via a network.

[0115] (2) The configurations exemplified as the above-described embodiments are merely examples of the configurations of the present invention, and may be combined with other known technologies, or may be modified, such as by omitting some parts, without departing from the spirit of the present invention. Furthermore, the above-described embodiments may be implemented by appropriately adopting the processes and configurations described in other embodiments.

[0116] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0117] 10 analysis device, 20 sensor unit, 21 filter, 22 amplifier, 23 A / D converter, 30 sensor, 40 terminal device, 50 network, 60 monitoring device, 70 pump, 100 analysis system, 101 processor, 103 memory, 105 display, 107 input device, 109 signal input interface, 111 communication interface, 202 signal acquisition unit, 204 intensity calculation unit, 206 setting unit, 208 distance calculation unit, 210 data acquisition unit, 212 abnormality determination unit, 214 output control unit, 1000 system.

Claims

1. a signal acquisition unit that acquires a vibration signal detected by a sensor attached to the target device during operation; an intensity calculation unit that calculates a first plurality of signal intensities corresponding to a plurality of frequency bands by analyzing the vibration signal corresponding to the target device; a distance calculation unit that calculates a first Mahalanobis distance of a signal space based on the first plurality of signal intensities at a first time with respect to a predetermined unit space; a data acquisition unit that acquires status data relating to the operating status of the target device; an abnormality determination unit that determines whether or not there is an abnormality in the target device based on the status data when the first Mahalanobis distance is equal to or greater than a threshold; and a setting unit that, when it is determined that the target device is not abnormal, reconfigures the unit space based on a second plurality of signal intensities corresponding to the plurality of frequency bands, which are calculated by analyzing the vibration signals acquired during a predetermined period around the first time.

2. the intensity calculation unit calculates a third plurality of signal intensities corresponding to the plurality of frequency bands, respectively, by analyzing the vibration signal acquired after the first time point; the distance calculation unit calculates a second Mahalanobis distance of a signal space based on the third plurality of signal intensities with respect to the unit space reset by the setting unit; The analysis system according to claim 1 , wherein when the second Mahalanobis distance is equal to or greater than the threshold value, the abnormality determination unit determines whether or not an abnormality exists in the target device based on the status data.

3. the target equipment is a pump, 3. The analysis system according to claim 1, wherein the status data includes at least one of a pressure of the fluid discharged by the pump, a current value for driving the pump, a frequency for driving the pump, and a temperature of a housing of the pump.

4. 4. The analysis system of claim 3, wherein the abnormality determination unit determines that the pump is abnormal when at least one of a first condition that the pressure is less than a first reference value, a second condition that the current value is equal to or greater than a second reference value, a third condition that the frequency is equal to or greater than a third reference value, and a fourth condition that the temperature is equal to or greater than a fourth reference value is satisfied.

5. the predetermined unit space is a first unit space configured by a plurality of signal intensities respectively corresponding to the plurality of frequency bands, the signal intensities being calculated by analyzing a vibration signal corresponding to the target device in a normal state; 3. The analysis system according to claim 1, wherein the distance calculation unit calculates, as the first Mahalanobis distance, a Mahalanobis distance of a signal space formed by the first plurality of signal intensities at the first time with respect to the first unit space.

6. the predetermined unit space is a second unit space configured with two-dimensional centroid data indicating centroid positions of a plurality of signal intensities respectively corresponding to the plurality of frequency bands, the centroid data being calculated by analyzing a vibration signal corresponding to the target device in a normal state; 3. The analysis system according to claim 1, wherein the distance calculation unit calculates, as the first Mahalanobis distance, a Mahalanobis distance of a signal space constituted by the two-dimensional center of gravity data at the first time with respect to the second unit space.

7. The analysis system according to claim 1 , further comprising an output control unit that outputs warning information when the target device is determined to be abnormal.

8. 8. The analysis system according to claim 7, wherein the output control unit, when the first Mahalanobis distance is equal to or greater than the threshold, displays the first Mahalanobis distance on the display in a different display manner than when the first Mahalanobis distance is less than the threshold.

9. acquiring a vibration signal detected by a sensor attached to the target device during operation; calculating a first plurality of signal strengths corresponding to a plurality of frequency bands by analyzing the vibration signal corresponding to the target device; calculating a first Mahalanobis distance in a signal space based on the first plurality of signal intensities at a first time for a predetermined unit space; acquiring status data relating to the operational status of the target device; a step of determining whether or not an abnormality exists in the target device based on the status data when the first Mahalanobis distance is equal to or greater than a threshold value; and if it is determined that the target device is not abnormal, resetting the unit space based on a second plurality of signal intensities corresponding to the plurality of frequency bands, which are calculated by analyzing the vibration signals acquired during a predetermined period around the first time.

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