JP2022054003A - System for diagnosing failure symptom - Google Patents

Abstract

To provide a system for diagnosing a failure symptom that allows for improving the accuracy of determining respective failure symptoms of a plurality of work machines at a low cost.SOLUTION: A system for diagnosing a failure symptom 1 for diagnosing a state of a failure symptom as to a plurality of work machines 3 comprises: a symptom-state diagnosing section 42 that compares running information of a work machine 3 with a diagnosis threshold and diagnosing a state of a failure symptom; an action determining section 43 that determines a similarity-based classification division of the work machine 3; a threshold-adjustment determining section 23 that compares a disassembly-inspection result of the work machine with a diagnosis result of a symptom state and determines a presence/absence of a necessity to change the diagnosis threshold; and a similarity-based classification determining section 24 that determines a similarity-based classification division of the work machine requiring a change of the diagnosis threshold. The threshold-adjustment determining section determines whether or not a damage state is of a state of a presence of machine down based on the disassembly-inspection result, and the similarity-based classification determining section renews the determination threshold of the similarity-based classification division if determined in a state of a presence of machine down.SELECTED DRAWING: Figure 2

Description

The present invention relates to a failure sign diagnosis system.

Failure of work machinery at a construction site has a large effect on the progress of construction and may lead to a decrease in productivity. Therefore, it is desirable to determine the sign of a failure in the work machine and take measures such as maintenance, maintenance, maintenance, inspection, and maintenance.

Patent Document 1 proposes a technique of an abnormality diagnostic device for estimating a future performance measure of mechanical equipment. In Patent Document 1, "The abnormality diagnosis device 1 has a time-series data acquisition unit 10 that acquires sensor data from a plurality of sensors installed in mechanical equipment as time-series data, and statistical data that uses the time-series data as learning data. By the method, the performance measure calculation unit 12 that calculates the performance measure, which is an index showing the performance of machinery and equipment, and the approximation formula that approximates the transition of the performance measure calculated based on the time series data acquired in the past by a polymorphic formula are calculated. The approximate expression calculation unit 13 and the performance measurement estimation unit 14 that estimates the performance measurement up to a predetermined time in the future by using the approximate expression are provided, and the latest time series data is acquired every time the time series data is acquired. Calculate the performance measure for the latest time series data, add the performance measure for the latest time series data to the above transition, calculate the approximate expression, and estimate the future performance measure using the approximate expression. " A technique has been shown in which a diagnostic threshold is generated based on normal data and a sign of machinery and equipment is determined to improve the accuracy of estimation of future performance measures.

Japanese Unexamined Patent Publication No. 2016-045553

However, the mechanical equipment of Patent Document 1 is used in an environment of certain conditions such as in a factory, and is a work machine having various usage conditions such as the contents of construction, how to move, and the area where it is used. not the same. For example, in the case of a power shovel, it is used not only for general civil engineering, but also for crushed stones, breaker machines for demolition, and forestry. Therefore, in order to improve the accuracy of the failure sign determination of the work machine, it is necessary to individually set the determination threshold value for determining the sign according to the usage conditions. Such work of individually setting the determination threshold requires labor and time, and it is difficult to reduce the cost.

The present invention has been made in view of the above points, and an object of the present invention is to provide a failure sign diagnosis system capable of improving the accuracy of failure sign determination of each of a plurality of work machines at low cost. be.

The failure sign diagnosis system of the present invention that solves the above problems includes a plurality of work machines and a server that transmits / receives information between the plurality of work machines, and determines a failure sign state for the plurality of work machines. It is a failure sign diagnosis system for diagnosing, and is a sign state diagnosis unit that diagnoses a failure sign state of the work machine by comparing the operation information of the work machine with a diagnostic threshold set for the work machine. , The operation determination unit for determining which of the plurality of similar classifications the usage status of the work machine corresponds to, the disassembly investigation result of disassembling at least one of the plurality of work machines and investigating the damaged state, and the above. A threshold adjustment determination unit that compares with a diagnosis result of a sign state to determine whether or not it is necessary to change the diagnosis threshold, and a work machine that is determined by the threshold adjustment determination unit that the diagnosis threshold needs to be changed. It has a similarity classification determination unit for determining which of a plurality of similar classification categories each is classified, and the similarity classification determination unit operates the work machine more than the standard in which the damage state is set in advance. It is characterized in that the determination threshold of the similar classification category is updated when the influence is large.

According to the present invention, it is possible to provide a failure sign diagnosis system capable of setting an appropriate diagnostic threshold value according to each usage situation for a plurality of work machines and improving the accuracy of the sign determination at low cost. Further features relating to the present invention will be apparent from the description herein and the accompanying drawings. In addition, problems, configurations, and effects other than those described above will be clarified by the following description of the embodiments.

The system block diagram of the failure sign diagnosis system which concerns on this embodiment. A flow diagram illustrating the contents of processing executed in the failure sign diagnosis system. A flow chart explaining the contents of the predictive state diagnosis process. The flow diagram explaining the content of the operation determination process. The flow diagram explaining the content of the threshold value adjustment determination process. A table diagram for determining whether or not there is a threshold change based on the predictive diagnosis result and the decomposition survey result. Schematic diagram of the grouping update instruction screen displayed on the server monitor. The flow diagram explaining the content of the similar classification judgment process. The figure explaining the method of changing the similar classification classification. The flow diagram explaining the content of the extraction judgment process. The figure which shows an example of the list of target machines. Schematic diagram of the update instruction confirmation screen displayed on the server monitor. The figure explaining the example of the threshold value calculated in the threshold value calculation part. Schematic diagram of the threshold update confirmation screen displayed on the monitor of the work machine.

Next, embodiments of the present invention will be described in detail with reference to the drawings.
FIG. 1 is a system block diagram of a failure sign diagnosis system according to the present embodiment.

The failure sign diagnosis system 1 includes a plurality of work machines 3 and one server 2 for transmitting / receiving information between the plurality of work machines 3. The number of the work machine 3 and the server 2 is not limited to the configuration of the present embodiment, and any of them may be one or more, and a plurality of servers 2 may be provided.

Each of the plurality of work machines 3 is used for various operations such as construction work, civil engineering work, and snow removal work in various environments such as a tropical area, a frigid area, a dry area, and a snowfall area. In the present embodiment, hydraulic excavators 3A, 3B, and 3C will be described as an example of the plurality of work machines 3. Since the hydraulic excavators 3B and 3C have the same configuration as the hydraulic excavator 3A, detailed description thereof will be omitted.

The hydraulic excavator 3A includes a computing device 31, a plurality of sensors for detecting the operating state of the hydraulic excavator 3A, and a computing device, in addition to general configurations such as a prime mover, a hydraulic pump, a hydraulic actuator, an operating lever, and a control device. It includes a display device 34 that displays the calculation result and the like by 31 and a transmission unit 35 and a reception unit 36 that transmit and receive information between the server 2.

The plurality of sensors include a first pressure sensor 32 that detects the pressure of the hydraulic oil (pump pressure) discharged from the hydraulic pump, and a second pressure sensor 33 that detects the pressure of the hydraulic oil (circuit pressure) from the hydraulic circuit. Have. The plurality of sensors are not limited to the first pressure sensor 32 and the second pressure sensor 33, and may be any number as long as they can detect the operating state of the work machine, the usage environment, and the like. It is not limited to one. For example, it may be a hydraulic pressure sensor that detects the oil pressure of the swivel motor, an outside temperature sensor, a potentiometer that detects the position of the operating lever, a sensor that counts the operation frequency of the operating lever, an hour meter, an angle sensor that detects the angle of the work arm, and operation. An oil temperature sensor, a radiator cooling water temperature sensor, or the like may be used.

The arithmetic unit 31 has an operation information storage unit 41, a sign state diagnosis unit 42, an operation determination unit 43, a determination result storage unit 44, and a display control unit 45. The operation information storage unit 41 acquires the detection values detected by the plurality of sensors and stores them as the operation information of the hydraulic excavator 3A. As the operation information of the hydraulic excavator 3A, specifically, information on the pump pressure of the hydraulic oil discharged from the hydraulic pump and the circuit pressure of the hydraulic oil from the hydraulic circuit is accumulated.

The sign state diagnosis unit 42 compares the operation information of the hydraulic excavator 3A with the diagnostic threshold set for the hydraulic excavator 3A to diagnose the sign state of failure of the hydraulic excavator 3A. The predictive state diagnosis unit 42 includes a diagnostic data generation unit 421, a threshold value determination unit 422, a duration determination unit 424, and a threshold value DB 423.

The diagnostic data generation unit 421 acquires diagnostic data from the operation information stored in the operation information storage unit 41 and generates diagnostic data for the hydraulic excavator 3A. For example, the data detected by the circuit pressure detected by the second pressure sensor and the threshold data such as the range and the time are acquired. Then, the data itself (raw value) or the data generated by filtering the data is used as diagnostic data.

The threshold value determination unit 422 compares the diagnostic data with the diagnostic threshold value, and determines whether or not the diagnostic data is within the range of the diagnostic threshold value. The threshold value DB 423 stores the diagnostic threshold value, and updates the diagnostic threshold value by receiving an instruction to update the threshold value from the server 2 described later. The duration determination unit 424 determines whether or not the determination result outside the threshold value continues for a predetermined time or longer. The sign state diagnosis unit 42 determines whether or not there is a sign of failure according to the determination result of the duration determination unit 424. The sign state diagnosis unit 42 determines that there is a sign of failure when the determination result outside the threshold value continues for a predetermined time or longer.

The determination result storage unit 44 stores the diagnosis result of the sign diagnosis by the sign state diagnosis unit 42 and outputs it to the display control unit 45. The display control unit 45 controls the display device 34 to display the diagnosis result stored in the determination result storage unit 44. For example, when the predictive state diagnosis unit 42 diagnoses that there is a sign of failure at a predetermined position of the hydraulic excavator 3A, a message prompting inspection or replacement is displayed on the display device 34.

The operation determination unit 43 determines the usage status of the hydraulic excavator 3A, that is, the usage history of the hydraulic excavator 3A being used. The operation determination unit 43 determines which of the plurality of preset similar classification categories the usage status of the hydraulic excavator 3A corresponds to. Similar classifications are classified according to criteria such as the severity of the usage of the work machine, the area of the construction site, the type of the work machine, and how to move the work machine.

Next, the configuration of the server 2 will be described. The server 2 has a configuration capable of transmitting and receiving information by wireless communication with a plurality of work machines 3 having hydraulic excavators 3A, 3B, and 3C. Then, the disassembly survey result and the vehicle management information are input to the server 2 by a route different from that from the work machine 3. The disassembly investigation result is the result of actually investigating the damaged state of the moving part that causes a failure by disassembling at least one of the plurality of work machines 3, and classifies it as either undamaged or damaged. If there is damage, it is further classified as either with machine down or without machine down.

No damage means that there is no problem if you continue to use it, and damaged means that you need to stop using it, which is associated with information on appearance, useful life, or operating time, respectively. .. With or without machine down is an index showing the degree of damage, and the state with machine down has a greater effect on the operation of the work machine than the preset criteria such as the inability of the work machine to continue operation. The state without machine down is a state of damage that has less influence on the operation of the work machine than the preset standard such as not reaching the time when the operation is stopped. The presence or absence of damage and machine down is determined based on preset criteria. The vehicle management information includes information on the types of work machines such as hydraulic excavators, crane trucks, and dump trucks, and the machine number.

The server 2 diagnoses whether or not the diagnostic threshold is appropriate by comparing the disassembly investigation result of disassembling at least one of the plurality of work machines 3 and investigating the damage state with the diagnosis result of the sign state. The server 2 groups the plurality of work machines 3 into similar classification categories (groups) used in similar places and usage conditions, and adjusts the diagnostic threshold value for each similar classification category. The server 2 may adjust the diagnostic threshold value for diagnosing the predictive state of a plurality of work machines 3 used in various use states in various places to an appropriate value according to the state of each work machine 3. can.

When the work machine 3 has a machine down, the server 2 adjusts the determination threshold value of the similar classification category to update the plurality of similar classification categories, and the server 2 updates the plurality of similar classification categories for the plurality of work machines. Performs a process of determining which category is to be classified. Then, the work machines 3 whose similar classification categories have been changed before and after the update of the similar classification categories are extracted from the plurality of work machines 3, and the diagnostic thresholds of the extracted work machines 3 are used based on the operation information. And calculate. Then, the calculated diagnostic threshold value is transmitted to the arithmetic unit 31 of the work machine 3 to update the diagnostic threshold value.

The server 2 includes a diagnosis result and decomposition investigation result DB 22, a threshold value adjustment determination unit 23, a similarity classification determination unit 24, an extraction determination unit 25, a threshold value calculation unit 26, a reception unit 21, and a transmission unit 28. ing.

The diagnosis result and the disassembly investigation result DB 22 store the diagnosis result of the sign state of the plurality of work machines 3 communicated with the server 2, the disassembly investigation result (including the presence / absence of machine down) 4, and the vehicle management information 5. .. The diagnosis result, the disassembly investigation result 4 and the vehicle management information 5 of these predictive states are input to the threshold value adjustment determination unit 23 from the diagnosis result and the disassembly investigation result DB 22.

The threshold value adjustment determination unit 23 performs a process of comparing the diagnosis result of the predictive state acquired from the diagnosis result and the decomposition investigation result DB 22 with the decomposition investigation result 4 and determining whether or not it is necessary to change the diagnosis threshold value. The threshold value adjustment determination unit 23 includes a presence / absence determination unit 231 of the decomposition investigation result, a threshold value adjustment presence / absence determination unit 232, and an update instruction unit 233 of the similar classification determination condition.

The presence / absence determination unit 231 of the disassembly survey result determines whether or not the disassembly survey result of the target work machine 3 is stored in advance in the diagnosis result and the disassembly survey result DB. The presence / absence determination unit 232 for threshold adjustment determines whether or not to adjust the diagnostic threshold based on the diagnosis result of the sign and the decomposition investigation result. Specifically, if the diagnostic result of the sign and the disassembly survey result do not match, it is determined that the diagnostic threshold needs to be adjusted, and if they match, it is determined that the diagnostic threshold does not need to be adjusted.

The update instruction unit 233 of the similar classification determination condition outputs an instruction (instruction for grouping update) to change the determination condition of the similar classification classification according to the decomposition investigation result to the similarity classification determination unit 24. In the present embodiment, when the predictive state diagnosis result is no sign, the disassembly investigation result is damaged, and the machine is down, an instruction to change the judgment condition of the similar classification category is output.

The similarity classification determination unit 24 has a machine similarity determination unit 241. The machine similarity determination unit 241 determines which of the plurality of similar classification categories the working machine 3 determined by the threshold value adjustment determination unit 23 to be changed in the diagnostic threshold value is classified. Further, when an instruction to change the determination condition of the similarity classification classification is received from the update instruction unit 233 of the similarity classification determination condition, all the work machines 3 communicatively connected to the server 2 are based on the updated similarity classification classification. Perform group update processing for regrouping.

The extraction determination unit 25 performs a process of determining the work machine 3 which is determined to need to change the diagnostic threshold value from among the plurality of work machines 3 as the target machine for updating the threshold value. Further, the work machine 3 whose classification has been changed before and after the update of the similar classification classification (before and after the grouping update) is extracted as the target machine for the threshold update. The extraction determination unit 25 has a determination unit 251 of the target machine. The discrimination unit 251 of the target machine reads the updated similar classification classification, and when there is a threshold value change policy, performs a process of including the target work machine 3 in the threshold value change determination list, and generates a target machine list. The server 2 is provided with a monitor display unit (not shown), and the target machine list is displayed on the monitor display unit of the server 2, can be confirmed by an administrator or the like who manages the server 2, and updates are executed. You can choose whether or not to use it.

The threshold value calculation unit 26 performs a process of calculating the diagnostic threshold value of the work machine 3 listed as the target machine in the target machine list. The threshold value calculation unit 26 reads past threshold values and operation information, and calculates a diagnostic threshold value.

Next, the contents of the arithmetic processing executed in the failure sign diagnosis system having the above configuration will be described in detail below with reference to FIGS. 2 to 14.

FIG. 2 is a flow chart illustrating the contents of processing executed in the failure sign diagnosis system. FIG. 2 shows processing in the arithmetic unit 31 on the hydraulic excavator side, which is a work machine, and processing in the arithmetic unit 31 on the server 2 side, which is an office PC.

First, in the arithmetic unit 31 on the hydraulic excavator side, the predictive state diagnosis process S101 by the predictive state diagnosis unit 42, the operation determination process S102 by the operation determination unit 43, and the transmission process S103 by the transmission unit 35 are sequentially performed.

FIG. 3 is a flow chart for explaining the contents of the predictive state diagnosis process.
The predictive state diagnosis process S101 acquires diagnostic data such as sensor data and threshold data (range, time) (S111). Since this diagnostic data is a detection value (raw data) as it is including noise and the like, the diagnostic data in which noise is removed by filtering is generated (S112). Then, the diagnostic threshold set in the threshold DB 423 is compared with the diagnostic data, and it is determined whether or not the diagnostic data is larger than the diagnostic threshold (outside the threshold) (S113). Here, when the result determined to be larger than the diagnostic threshold is continuously continued for 1 minute (1 min) or more, it is determined that there is a sign of failure (S115), and it is determined to be below the diagnostic threshold or larger than the diagnostic threshold. If the results are not continuous for 1 minute or more, it is determined that there is no sign of failure (S116).

FIG. 4 is a flow diagram illustrating the content of the operation determination process.
In the operation determination process S102, for example, the operation data (sensor data) of the own work machine 3 accumulated during a predetermined period (every month in this embodiment) is acquired from the operation information storage unit 41 (S121). ), Based on the acquired operation data, it is determined which of the similar classification categories the operating state of the own work machine 3 corresponds to. In the present embodiment, the classification is based on the average pressure of the hydraulic oil discharged from the hydraulic pump, and when the average pressure is equal to or higher than the determination threshold value α (YES in S122), it is determined that the similar classification classification is large. In (S123), when the average pressure is smaller than the determination threshold value α and β or more (YES in S124), it is determined that the similar classification category is in the middle (S125). Then, when the average pressure is smaller than β (NO in S124), it is determined that the similar classification category is small (S126). Table 1 below is a table showing the relationship between the similar classification and the average pressure.

The transmission unit 35 performs a transmission process S103 for transmitting the predictive state diagnosis result by the predictive state diagnosis process S101 and the operation determination result by the operation determination process S102 to the reception unit 21 of the server 2.

Then, as shown in FIG. 2, in the arithmetic unit on the server 2 side, the reception process S201 for receiving the predictive state diagnosis result by the predictive state diagnosis process S101 and the operation determination result by the operation determination process S102 by the receiving unit 21 and the receiving unit. The DB storage process S202 for storing the predictive state diagnosis result by the sign state diagnosis process S101 received by 21 and the operation judgment result by the operation judgment process S102 in the diagnosis result and the disassembly investigation result DB 22 is performed, and then the threshold adjustment determination unit 23 is performed. The threshold adjustment determination process S203 is performed.

FIG. 5 is a flow chart illustrating the content of the threshold value adjustment determination process.
In the threshold adjustment determination process S203, the diagnosis result of the sign of failure, the disassembly investigation result of the work machine 3, and the machine down information are acquired from the diagnosis result and the disassembly investigation result DB 22 (S211), and whether or not the disassembly investigation result is increased. Is determined (S212). Then, when there is an increase in the decomposition survey result (YES in S212), it is determined whether or not to change the diagnostic threshold of the predictive state based on the predictive diagnosis result and the decomposition survey result (S213).

FIG. 6 is a table diagram for determining the presence / absence of a threshold change based on the predictive diagnosis result and the decomposition survey result.
Here, if the predictive diagnosis result is a sign and the decomposition survey result is damaged, or if the predictive diagnosis result is no sign and the decomposition survey result is undamaged (YES in S213), the diagnosis of the predictive diagnosis is made. Since the threshold value is appropriate, it is determined that there is no need to change (S220), and the routine is exited.

On the other hand, if the predictive diagnosis result is no sign and the disassembly survey result is damaged, or the sign diagnosis result is sign and the disassembly survey result is undamaged (NO in S213), the judgment of the sign is not appropriate. Therefore, it is determined that the diagnostic threshold needs to be changed (S214). When the predictive diagnosis result is a sign and the decomposition survey result is undamaged (YES in S215), it is assumed that the diagnostic threshold value of the predictive diagnosis is larger than the measured value which is the decomposition survey result, and the threshold value for narrowing the diagnostic threshold value is narrowed. The change policy is set (S216).

If the predictive diagnosis result is no sign and the disassembly investigation result is damaged (NO in S215), the threshold change policy for expanding the diagnostic threshold is adopted (S217). Then, when it is determined whether or not there is a machine down (S218) and it is determined that there is a machine down (YES in S218), the similarity classification determination unit 24 is instructed to update the grouping to update the similar classification classification (S219).

FIG. 7 is a schematic diagram of a screen for grouping update instructions displayed on the monitor of the server.
On the monitor of the server 2, a screen for selecting whether or not to update the grouping is displayed because a machine down unexpectedly predicted is detected as a display (FIG. 7A) before the grouping update instruction. Then, when an operation for updating the grouping is performed by an administrator or the like who manages the server 2, the instruction is transmitted to the similarity classification determination unit 24. Then, the monitor of the server 2 shows the display (FIG. 7 (B)) after the grouping update instruction.

Then, as shown in FIG. 2, in the arithmetic unit on the server 2 side, the similarity classification determination process S204 by the similarity classification determination unit 24, the extraction determination process S205 by the extraction determination unit 25, and the threshold value calculation process S206 by the threshold value calculation unit 26. Is done.

FIG. 8 is a flow diagram for explaining the content of the similarity classification determination process, and FIG. 9 is a diagram for explaining a method of changing the similarity classification classification.
In the similarity classification determination process S204, similarity determination data including the diagnosis result of the predictive diagnosis, the decomposition investigation result, the threshold value data, and the threshold value determination result is acquired from the diagnosis result and the decomposition investigation result DB 22 (S231). Then, it is determined whether or not there is a grouping update instruction (S232), and when the grouping update instruction is received in S219 of FIG. 5, the group update process S233 is performed.

In the group update process S233, for example, when the similar classification category in which the machine down has occurred is the middle area, the group update process S233 updates the range of the middle area of the similar classification category. This aims to pick up a wide range of machines with similar uses to avoid the risk of machine down.
Specifically, as shown in FIG. 9, the judgment threshold value α that is the boundary value between the medium region and the large region is expanded to α'on the large region side, and the judgment threshold β that is the boundary value between the medium region and the small region is set. Expand to β'on the small area side.

Further, as a modification, for example, if there is a group update instruction, the classification is in the middle region, and the pump pressure at that time is in the range of α to β, it may not be changed. That is, the similarity classification determination threshold may not be changed as long as it is within the range of the previous similarity classification determination threshold, so that the range for expanding the region may be limited and the threshold may be converged. According to the configuration of this modification, it is possible to prevent the grouping range from continuing to expand when the machine down occurs continuously in the same grouping range at the time of the similarity classification determination due to the continuous change processing of the similar classification classification. be able to.

The target data extraction process S234 performs a process of extracting the target data for determining the similarity, and in the present embodiment, the pump pressure of the hydraulic pump is extracted as the target data. Then, in S235 and later, it is determined which of the similar classification categories each work machine 3 corresponds to, and if the group update process is performed in S233, all the work machines connected to the server 2 are connected. A process of reviewing the similarity classification for 3 is performed.

For example, when the average pressure of the predetermined work machine 3 is equal to or higher than the determination threshold value α (YES in S235), the similarity determination is made that the similarity classification of the work machine 3 has a large pump pressure (S236). Then, when the average pressure of another work machine 3 is smaller than the determination threshold value α and β or more (YES in S237), the similarity determination is made that the similarity classification of the work machine is under pump pressure. (S238). Further, when the average pressure of another work machine 3 is smaller than β (NO in S237), the similarity determination is made that the similarity classification of the work machine is that the pump pressure is small (S239).

Next, in the extraction determination process S205, a process of identifying and extracting the work machine 3 determined to require the change of the diagnostic threshold value (with the threshold value change policy) from the plurality of work machines 3 is performed (FIG. 10). First, the similar classification classifications of all the work machines 3 connected to the server 2 are read (S241). Then, the work machine 3 determined to have the threshold value change policy by the threshold value adjustment determination process S203 is extracted (YES in S242), and the process of including the work machine 3 in the threshold value change determination list is performed (S243), based on the threshold value change determination list. A target machine list of the target work machine 3 is created (S244).

FIG. 11 is an example of a target machine list, and the target machine list includes a machine number for specifying a target work machine 3, a similar classification category, and information on a sign change determination. When the target machine list is created, a display process (S245) for displaying the target machine list on the display device of the server 2 is performed. In the display process, an instruction for selecting whether or not to execute the update instruction is displayed together with the target machine list (S251, FIG. 12). When the update instruction is input as "Yes" (YES in S252) by the administrator of the server 2 or the like, it is determined that there is an execution determination to execute the update (S253), and the update instruction is input as "No". (NO in S252), a cancellation determination is made to cancel the execution of the update (S254).

Then, the presence / absence of the execution determination is determined (S246), and if the execution determination is present, an instruction to change the diagnostic threshold value is transmitted to the work machine 3 for which the sign change determination is made in the threshold value change list (S247). .. In the example shown in FIG. 11, it is shown that the similar classification category expands the predictive change determination for the working machine 3 in the middle.

In the threshold value calculation process S206 by the threshold value calculation unit 26, a process of calculating the diagnostic threshold value of the sign state is performed, and the diagnostic threshold value of the work machine 3 showing the threshold value change policy is calculated among the plurality of work machines 3.

FIG. 13 is a diagram illustrating an example of a threshold value calculated by the threshold value calculation unit.
The vertical axis of the graph shown in FIG. 13 is the pressure sensor value indicating the pressure of the hydraulic oil discharged from the hydraulic circuit, and the horizontal axis is the time. In the example shown in FIG. 13, when the pressure exceeds (exceeds) the diagnostic threshold Th, it is detected as an abnormality. For example, as a result of the threshold value adjustment determination process (S203), (1) there is a sign and there is no damage, that is, the existing diagnostic threshold value Th is set too strict (too low), and the operation of the work machine 3 is actually performed. If it is erroneously detected that there is a sign of failure even though there is no damage to the component, the diagnostic threshold Th is increased by δ so that it becomes larger than the measured value to obtain the diagnostic threshold Th.

Then, (2) when there is no sign and there is damage (no machine down), that is, the existing diagnostic threshold Th setting is loose and too sweet (too high), and the moving parts of the work machine 3 are actually damaged. However, if it is erroneously detected that there is no sign of failure, the diagnostic threshold Th is lowered by ε so that the diagnostic threshold Th becomes equal to or less than the measured value to obtain the diagnostic threshold Thb. Then, (3) when there is no sign and there is damage (with machine down), that is, the setting of the diagnostic threshold Th is significantly loose, and the moving parts of the work machine 3 are actually damaged, and the damaged state is the work. If the effect on the operation of the machine 3 is large, it is considered to be overlooked, and the diagnostic threshold Th is lowered by ζ minutes to the diagnostic threshold Thc so that the diagnostic threshold Th is less than the measured value and has a safety margin. .. The ζ minute can be a value obtained by multiplying the ε minute by the safety factor FS (ζ = −ε × FS).

When the threshold value update data is calculated by the threshold value calculation process S206, the transmission unit of the server 2 transmits the threshold value update data to the work machine 3 that is the target of the threshold value update (S207). FIG. 14 is a schematic diagram of a threshold value update confirmation screen displayed on the monitor of the work machine. When the work machine 3 receives the threshold value update data from the server 2 (S104), as shown in FIG. 14A, the work machine 3 causes the display device 34 to select whether or not to update the diagnostic threshold value (S105). ) Is performed by the display control unit 45. When "perform update" is selected by the user of the work machine 3, the threshold value DB 423 performs a process of updating the diagnostic threshold value using the update data. When the process of updating the diagnostic threshold value Th is performed, as shown in FIG. 14B, a display indicating that the diagnostic threshold value has been updated is displayed.

The failure sign diagnosis system 1 described above is a sign state diagnosis unit 42 that diagnoses a failure sign state of the work machine 3 by comparing the operation information of the work machine 3 with the diagnostic threshold set for the work machine 3. , The operation determination unit 43 for determining the usage status of the work machine 3 and the disassembly investigation result in which at least one of the plurality of work machines 3 is disassembled to investigate the damaged state and the diagnosis result in the predictive state are compared with each other to make a diagnostic threshold. Which of the plurality of similar classifications is the work machine 3 determined by the threshold adjustment determination unit 23 to determine whether or not it is necessary to change the diagnostic threshold? It has a similarity classification determination unit 24 that determines based on the operation determination result, and the threshold adjustment determination unit 23 determines that the diagnostic threshold needs to be changed, and the damage state is determined based on the decomposition investigation result. It is determined whether or not there is a machine down, and the similarity classification determination unit 24 updates the determination threshold of the similarity classification classification when it is determined that the damaged state is the state with the machine down.

According to the failure sign diagnosis system 1, when there is a work machine whose damage state is determined to be in the state of machine down as a result of the disassembly investigation, the determination threshold value of the similar classification category to which the work machine belongs is updated. Will be done. As a result, among the plurality of work machines 3, the diagnostic threshold value can be changed collectively for the work machines 3 whose similar classification classification has been changed. Therefore, it is possible to set an appropriate diagnostic threshold value for each of the plurality of work machines 3 according to the usage situation, and it is possible to improve the accuracy of the sign determination at low cost.

In the above-described embodiment, the case of the hardware configuration in which each work machine 3 has the arithmetic unit 31 has been described as an example, but the present invention is not limited to this, and for example, the arithmetic unit 31 in the server 2 is described. May be provided, and the hardware configuration may be such that the result of calculation by the arithmetic unit 31 is transmitted from the server 2 to the work machine 3.

Although the embodiments of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various designs are designed without departing from the spirit of the present invention described in the claims. You can make changes. For example, the above-described embodiment has been described in detail in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to the one including all the described configurations. Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Further, it is possible to add / delete / replace a part of the configuration of each embodiment with another configuration.

1 Failure sign diagnosis system 2 Server 3 Work machine 23 Threshold adjustment judgment unit 24 Similar classification judgment unit 25 Extraction judgment unit 26 Threshold calculation unit 42 Prediction state diagnosis unit 43 Operation judgment unit

Claims (6)

It is a failure sign diagnosis system that includes a plurality of work machines and a server that transmits / receives information between the plurality of work machines, and diagnoses a failure sign state of the plurality of work machines.
A predictive state diagnosis unit that diagnoses a predictive state of failure of the work machine by comparing the operation information of the work machine with a diagnostic threshold set for the work machine.
An operation determination unit that determines the usage status of the work machine, and
A threshold adjustment determination unit that determines whether or not it is necessary to change the diagnostic threshold by comparing the disassembly investigation result of disassembling at least one of the plurality of work machines and investigating the damage state with the diagnosis result of the sign state. ,
Based on the operation determination result, the similarity classification determination unit determines which of the plurality of similar classification categories the work machine determined to need to be changed by the threshold value adjustment determination unit is classified. Have and
When it is determined that the diagnostic threshold value needs to be changed, the threshold value adjustment determination unit determines whether or not the damage state is a state with machine down based on the decomposition investigation result.
The failure sign diagnosis unit is characterized in that, when the threshold adjustment determination unit determines that the damaged state is a state with machine down, the similarity classification determination unit updates the determination threshold value of the similar classification category. system. An extraction determination unit that determines as a target machine a work machine that is determined to need to change the diagnostic threshold value from the plurality of work machines.
It has a threshold value calculation unit that calculates a diagnostic threshold value of a work machine determined as a target machine by the extraction determination unit based on the operation information.
The failure sign diagnosis system according to claim 1, wherein the sign state diagnosis unit updates the diagnosis threshold value based on a calculation result of the threshold value calculation unit. The failure sign according to claim 1, wherein the threshold adjustment determination unit selects a threshold change policy for narrowing the diagnostic threshold when the diagnosis result is no sign and the decomposition investigation result is damaged. Diagnostic system. The failure sign according to claim 1, wherein the threshold adjustment determination unit selects a threshold change policy for expanding the diagnostic threshold when the diagnosis result is a sign and the decomposition investigation result is undamaged. Diagnostic system. The sign state diagnosis unit compares the operation information of the work machine with the diagnosis threshold value, and when the determination result outside the threshold value is continuously continued for a predetermined time or longer, the work machine is said to have a sign of failure. The failure sign diagnosis system according to claim 1, wherein the diagnosis is performed. The failure sign diagnosis system according to claim 1, wherein the operation determination unit determines the similar classification based on the pump pressure of the hydraulic pump of the work machine.

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