Machine performance diagnostic device and construction machinery diagnostic system

Abstract

To reduce a possibility that a human error may occur, and to obtain a further exact diagnosis result.SOLUTION: A mechanical performance diagnosis device for diagnosing the soundness of an operation of a construction machine is provided, the mechanical performance diagnosis device comprises: a storage device storing fundamental waveform data of a plurality of operations of the construction machine, and performance and allowable error values of the plurality of operations; and a processor performing processing for diagnosing the soundness of the construction machine. The processor performs: processing for identifying an actually performed operation by comparing sensor waveform data which are obtained by detecting the actually performed operation of the construction machine by a sensor, and the waveform data which are held in the storage device; and processing for determining the soundness of the construction machine by acquiring a performance reference value and the allowable error value corresponding to a specified operation from the storage device, and comparing the acquired performance reference value and the allowable error value, and a characteristic value of the actually performed operation.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a machine performance diagnostic device and a construction machine diagnostic system. [Background technology]

[0002] When it comes to construction machinery, it is important to measure its basic performance, diagnose and predict potential failures in advance, and perform maintenance before a failure occurs to avoid construction interruptions. Basic performance refers to the construction machinery's inherent performance and standard specifications. In this regard, the market demands that tools for automatic self-diagnosis of failures (automatic self-diagnosis tools) be easy to use, inexpensive, and easy even for inexperienced personnel.

[0003] For example, Patent Document 1 discloses an automatic self-diagnosis technology that, in order to shorten the diagnosis time, diagnoses whether or not there is an abnormality in each part of a construction machine based on the operating sounds of the machine, and when an abnormality is diagnosed, identifies the cause of the abnormality based on information about the part diagnosed as abnormal, and displays the identification result. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-67614 Summary of the Invention [Problem to be solved by the invention]

[0005] When measuring basic performance, the possible vehicle body postures, movements, and procedures vary depending on the part being diagnosed, and it is necessary to respond accordingly to each diagnostic part. Therefore, when carrying out the measurement, it is necessary to check the procedure manual and confirm the possible vehicle body postures, movements, and measurement procedures for each diagnostic target, which makes advance preparations cumbersome. Furthermore, when actually carrying out the measurement work, it is necessary to prepare dedicated equipment, and since some measurement methods can affect the diagnostic results, attention must be paid to the timing of the measurement, which depends on the skill of the person doing the measurement, making it a time-consuming and labor-intensive task.

[0006] In view of such circumstances, the present disclosure proposes a technique for reducing the workload of the measurer and obtaining more accurate diagnostic results. [Means for solving the problem]

[0007] In order to solve the above problems, the present disclosure proposes a machine performance diagnosis device that diagnoses the soundness of the operation of a construction machine, the machine performance diagnosis device comprising: a storage device that stores reference waveform data for each of a plurality of operations of the construction machine, and a performance reference value and an allowable error value for each of the plurality of operations; and a processor that executes processing to diagnose the soundness of the construction machine, wherein the processor executes processing to identify the operation that was actually performed by comparing sensor waveform data obtained by detecting the operation that was actually performed by the construction machine with the reference waveform data held in the storage device; and processing to acquire from the storage device the performance reference value and allowable error value corresponding to the identified operation, and compare the acquired performance reference value and allowable error value with characteristic values ​​of the operation that was actually performed obtained from the sensor waveform data, thereby determining the soundness of the construction machine.

[0008] Further features related to the present disclosure will become apparent from the description and accompanying drawings of this specification, and aspects of the present disclosure may be realized and realized by the elements and combinations of various elements and aspects set forth in the following detailed description and the appended claims. The descriptions herein are exemplary and illustrative only and are not intended to limit the scope or application of the present disclosure in any way. [Effects of the Invention]

[0009] The technology disclosed herein can reduce the workload imposed on operators (users) when diagnosing construction machinery, and can automatically achieve highly accurate and reliable health diagnosis. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a diagram showing an example of a schematic configuration of a construction machine diagnostic system according to an embodiment of the present invention; [Figure 2] 1 is a block diagram showing an example of a schematic functional configuration of a construction machine performance measuring device 1 according to an embodiment of the present invention. [Figure 3] 2 is a diagram illustrating an example of the internal functional configuration of an information acquisition unit 101 of the performance measurement device 1. FIG. [Figure 4] 2 is a diagram illustrating an example of the internal functional configuration of a health diagnosis unit 102 of the performance measurement device 1. FIG. [Figure 5] 2 is a diagram illustrating an example of the internal functional configuration of an operation classification unit 103 of the performance measurement device 1. FIG. [Figure 6] 2 is a diagram illustrating an example of the internal functional configuration of a basic performance measurement diagnostic unit 104 of the performance measurement device 1. FIG. [Figure 7] 1 is a diagram showing an example of the configuration of a history log list, which is an example of information held by a data storage unit 201 included in a storage device 20 of a performance measurement device 1. FIG. [Figure 8] 8 is a diagram showing an example of the configuration of performance reference value information 801 held by a performance reference value holding unit 202 included in the storage device 20 of the performance measurement apparatus 1. FIG. [Figure 9] 9 is a diagram showing an example of the configuration of operating range reference value information 901 held by an operating range reference value holding unit 203 included in the storage device 20 of the performance measurement device 1. FIG. [Figure 10] 1 is a diagram showing an example of the configuration of operation-specific representative waveform information 1001 stored in an operation-specific representative waveform storage unit 204 included in the storage device 20 of the performance measurement device 1. FIG. [Figure 11]1 is a diagram showing an example of the configuration of recommendation information 1101 stored in a recommendation information storage unit 205 included in a storage device 20 of a performance measurement device 1. FIG. [Figure 12] 12 is a diagram showing an example of the configuration of action list information (table) 1201 held by the action list holding unit 206 included in the storage device 20 of the performance measurement device 1. FIG. [Figure 13] 13 is a diagram showing an example of input information 1301 to a performance measurement device 1 and an example of output information 1302 from the device 1 in comparison. [Figure 14] 1 is a diagram showing an example of the configuration of a GUI (Graphical User Interface) displayed on the display screen of the performance measurement device 1 or the display screen of the user terminal 4. FIG. [Figure 15] 10 is a flowchart illustrating a performance measurement and diagnosis process according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] <System configuration example> FIG. 1 is a diagram showing an example of the schematic configuration of a construction machine diagnostic system according to this embodiment.

[0012] The construction machinery diagnostic system is composed of a performance measurement device 1, a sensor group 2, a construction machine 3, and a user terminal 4. In the system configuration example of Fig. 1, the user terminal 4 and the performance measurement device 1 are shown as separate devices, but the user terminal 4 may also be equipped with each function of the performance measurement device 1 and each data holding unit / storage unit, etc.

[0013] The performance measurement device 1 includes, for example, a processor 10, a storage device 20, and a communication device 30.

[0014] The sensor group 2 is composed of multiple different sensors that can be used in construction machinery health check applications, and can include, for example, but is not limited to, an accelerometer 21, a microphone 22, and a camera 23. The accelerometer 21 is a micro-electromechanical system (MEMS)-scale sensor that measures acceleration and has the ability to detect gravity and vibration and may be incorporated into a device. The microphone 22 may be an independent microphone or a miniature microphone built into the performance measurement device 1. The camera 23 may be, for example, an independent miniature camera or a miniature camera built into the performance measurement device 1 or the user terminal 4.

[0015] The construction machine 3 is, for example, a hydraulic excavator, a wheel loader, a bulldozer, or any other type of construction machine. The construction machine 3 includes an angle sensor 13 that detects the current angle of a moving part of the construction machine 3 (for example, in the case of a hydraulic excavator, a boom, an arm, a bucket, etc.). The user terminal 4 can be, for example, a computer device such as a smartphone, a microcontroller, or a personal computer (PC).

[0016] The processor 10, storage device 20, and communication device 30 of the performance measurement device 1 are connected to the various sensors of the sensor group 2 and the angle sensor 13 of the construction machine 3 via, for example, a communication bus. The communication device 30 is also configured to be able to transmit, for example, diagnostic results and the like to the user terminal 4 wirelessly.

[0017] The processor 10 is composed of an arithmetic unit such as a CPU, and generates each processing unit by reading various related programs from a storage device 20 and expanding them in an internal memory (not shown). Each processing unit includes an information acquisition unit 101, a health diagnosis (inspection) unit 102, an operation classification unit 103, and a basic performance measurement diagnosis unit 104. The operation of each process will be described in detail later.

[0018] The storage device 20 includes a data saving section 201 , a performance reference value holding section 202 , an operating range reference value holding section 203 , an operation-specific representative waveform holding section 204 , a recommendation information holding section 205 , and an action list holding section 206 .

[0019] The operation representative waveform storage unit 204 stores, for example, representative sensor waveforms for each machine operation, which serve as a basis for classifying machine operations to be newly diagnosed (inspected).

[0020] The recommendation information storage unit 205 stores recommendation information to be presented to the operator according to the health status of the construction machine. For example, the recommendation information may be, "The arm cylinder seems to be in poor condition. Please show this report to the maintenance department so that they can take measures."

[0021] The action list storage unit 206 stores information on all related operations related to a specific diagnosis (test) type. Examples of operations to be diagnosed include (a) arm crowding (pulling operation), (b) arm dumping (pushing operation), (c) boom raising, (d) boom lowering, (e) bucket crowding, and (f) bucket dumping.

[0022] <Example of performance measurement device configuration> FIG. 2 is a block diagram showing an example of a schematic functional configuration of the construction machine performance measuring device 1 according to this embodiment. The main functions of the performance measurement device 1 are realized by an information acquisition unit 101, a health diagnosis unit 102, a data storage unit 201, an operation classification unit 103, a performance reference value holding unit 202, an operation range reference value holding unit 203, and a basic performance measurement diagnosis unit 104.

[0023] The information acquisition unit 101 collects the sensor data in a predetermined format and makes it ready for processing. An example of the sensor data is accelerometer data that detects load vibrations of the construction machine, and an example of the load is an arm.

[0024] The health diagnosis unit 102 processes the data acquired from the information acquisition unit 101 and outputs a diagnosis result indicating the health of a specific machine and the health of a specific load (whether it is in a healthy state or not). Also, for example, the health diagnosis unit 102 processes vibrations acquired from an operational inspection of the arm of a construction machine using an accelerometer, and outputs information indicating how long it took the machine to perform arm crowding based on the peak level of the vibrations. The data storage unit 201 is configured with a storage device and stores the aggregated sensor data from the information acquisition unit 101 .

[0025] The motion classification unit 103 processes, for example, data acquired from the information acquisition unit 101 and the health diagnosis unit 102, and outputs information on the type of motion performed during diagnosis. One example of processing by the motion classification unit 103 is to classify a machine motion as arm crowding using a waveform detected by an accelerometer.

[0026] The performance reference value holding unit 202 holds (stores) information on reference values ​​(standard values) for the soundness of the machine operation to be inspected, which are set by the manufacturer, for example. An example of information on the standard value for the soundness state is information that the arm crowding operation of a specific construction machine ideally takes 3.9±0.4 seconds.

[0027] The operation range reference value storage unit 203 stores, for example, reference values ​​(standard values) for the operation range of the construction machine. An example of operation range reference value information is information that the boom lift angle is from 0 degrees to 90 degrees.

[0028] The basic performance measurement diagnosis unit 104 is configured, for example, by a processor (or as a function of a processor), and collects the calculation results of the health diagnosis unit 102 and the operation classification unit 103, and by comparing these with specific reference values ​​(performance reference values ​​obtained from the performance reference value storage unit 202), diagnoses (determines) how much the current health state of the construction machinery deviates from the ideal case set by the manufacturer.

[0029] Furthermore, in order to verify the correct operating range, the basic performance measurement diagnosis unit 104 requests data on the operating range reference value corresponding to the current construction machine from the operating range reference value storage unit 203. Then, the basic performance measurement diagnosis unit 104 transfers information on the operating range reference value to, for example, a user terminal 4 (a mobile terminal (smartphone) or a computer (PC)) and displays the information on its output screen (if the performance measurement device 1 is implemented in the user terminal 4, information on the operating range reference value, etc. will be output directly to the display screen). This allows the operator to confirm whether the operation of the construction machine in the diagnosis was within the correct operating range, and to understand whether the construction machine is in a sound condition.

[0030] A specific example of the process from the action classification processing by the action classification unit 103 to the basic performance measurement diagnosis processing by the basic performance measurement diagnosis unit 104 will be described. For example, if the diagnosis by the health diagnosis unit 102 results in an operation time of 3.6 seconds, the action classification unit 103 compares the diagnosis result of the health diagnosis unit 102 with the corresponding operation reference value of 3.5±0.4 seconds for the construction machine stored in the performance reference value storage unit 202, and classifies the operation to be diagnosed as arm crowding. Then, the basic performance measurement diagnosis unit 104 sets the reference operation range of the arm crowd to a start angle position of 170 degrees and an end angle position of 15 degrees, and determines whether the operation range is correct by confirming these values ​​with an angle sensor built into the construction machine. Finally, these results are displayed on the display screen of the operator's user terminal. This allows the operator to be informed that the motor of the construction machine performing arm crowding is in a healthy state.

[0031] <Example of internal functional configuration of information acquisition unit 101> FIG. 3 is a diagram showing an example of the internal functional configuration of the information acquisition unit 101 of the performance measurement device 1. As shown in FIG.

[0032] The information acquisition unit 101 includes a sensor sampling frequency setting unit 1011 , a data format setting unit 1012 , and a data acquisition time setting unit 1013 .

[0033] The sensor sampling frequency setting unit 1011 has a function of setting a sampling frequency for acquiring data from one of the sensors 2 (for example, an accelerometer). The sampling frequency may be determined in advance, or may be determined by an operator or other user. For example, the sampling frequency for acquiring data from the accelerometer may be set to 100 samples / second.

[0034] The data format setting unit 1012 has a function of setting the format in which acquired sensor data is to be processed, for example, .csv as a data format.

[0035] The data acquisition time setting unit 1013 has the function of setting a time limit for data acquisition. The time limit can be set manually (e.g., collect data for 20 seconds regardless of the length of the test itself) or automatically (prompting the operator to start data acquisition, perform a diagnosis (examination), and then stop data acquisition).

[0036] <Example of Internal Functional Configuration of Health Diagnosis Unit 102> FIG. 4 is a diagram showing an example of the internal functional configuration of the health diagnosis unit 102 of the performance measurement device 1. As shown in FIG.

[0037] The soundness diagnosis unit 102 includes a noise removal unit 1021 , a feature detection unit 1022 , and a result extraction unit 1023 .

[0038] The noise removal unit 1021 applies a threshold to the waveform data (waveform signal) acquired by the information acquisition unit 101, and removes noise signals.

[0039] The feature detection unit 1022 detects features in the waveform signal from which noise has been removed. For example, this may involve detecting peaks in the waveform signal from the accelerometer 21. In the waveform signal from the accelerometer 21, one peak indicates the start time of the construction machine's operation, and another peak indicates the stop time of the operation.

[0040] The result extraction unit 1023 extracts information about the health of the construction machine based on the feature data analyzed and detected by the feature detection unit 1022. For example, the time required for a certain machine operation can be determined as the difference between the start time and the stop time.

[0041] <Example of Internal Functional Configuration of Action Classification Unit 103> FIG. 5 is a diagram showing an example of the internal functional configuration of the operation classification unit 103 of the performance measurement device 1. As shown in FIG.

[0042] The action classification unit 103 includes a feature analysis unit 1031 , a pattern matching unit 1032 , and a classification unit 1033 .

[0043] The feature analysis unit 1031 analyzes various features to gather further information about the operation of the construction machine. One example of feature analysis is analysis of the peak amplitude and roll-off shape of the accelerometer 21 signal.

[0044] The pattern matching unit 1032 compares the information acquired from the feature analysis unit 1031 with the patterns stored in the action-specific representative waveform storage unit 204, and extracts matching patterns (within a predetermined error range).

[0045] The classification unit 1033 determines (specifies) the type of action being performed based on the result of the comparison by the pattern matching unit.

[0046] <Example of internal functional configuration of basic performance measurement and diagnosis unit 104> FIG. 6 is a diagram showing an example of the internal functional configuration of the basic performance measurement diagnostic unit 104 of the performance measurement device 1. As shown in FIG.

[0047] The basic performance measurement diagnosis unit 104 includes a reference comparison unit 1041 , a result reporting unit 1042 , an operating range confirmation unit 1043 , and a recommendation information acquisition unit 1044 .

[0048] The standard comparison unit 1041 compares the classification results by the operation classification unit 103 and the diagnosis (determination) results by the health diagnosis unit 102 with the performance standard values ​​stored in the performance standard value storage unit 202, and determines whether the construction machine being diagnosed (specific operation: for example, arm crowding operation) is in a healthy state.

[0049] The result reporting unit 1042 creates a report on the health of the construction machine and transmits it together with the raw data (measurement data) to the data saving unit 201 of the storage device 20. This makes it possible to generate a history log on the health of the construction machine.

[0050] In order to confirm whether the operator of the construction machine to be diagnosed has performed the diagnosis within the correct operating range, the operating range confirmation unit 1043 acquires the operating range reference value corresponding to the classification result of the operation classification unit 103 from the operating range reference value storage unit 203 and outputs this information (displays it on the display screen). For example, in the case of an arm pull, the reference operating range information stored in the operating range reference value storage unit 203 has a start angle position of 170 degrees and an end angle position of 15 degrees, which the operator can check using the angle sensor 31 built into the construction machine after performing the diagnosis.

[0051] Based on the comparison result by the reference comparison unit 1041, the recommendation information acquisition unit 1044 acquires appropriate recommendation information corresponding to the current diagnosis content from the information set stored in advance in the recommendation information storage unit 205.

[0052] <Examples of information stored in the data storage unit 201> FIG. 7 is a diagram showing an example of the configuration of a history log list, which is an example of information held by the data storage unit 201 included in the storage device 20 of the performance measurement apparatus 1. As shown in FIG.

[0053] The history log list consists of multiple history files for each operation and sample of each construction machine (by model). For example, if you select any file (history log file) 7012 from the list shown in the upper part of Figure 7, you can view the file contents shown in the lower part of Figure 7.

[0054] The history file is saved, for example, as a .csv file, and the title of the history file includes the date (automatically assigned by the device's OS), the model of the construction machine (set by the operator), operation information (obtained from the operation classification unit 103), sample number (if the experiment is to be repeated, excluding the diagnosis results for improperly operated operations by the operator), and diagnosis results (information reported from the basic performance measurement diagnosis unit 104).

[0055] An example of a history file is shown in the lower diagram of Fig. 7. The history file 7012 includes, as configuration items, a data acquisition time 70121, raw data 70122 which is measurement data, an operation 70123 which indicates the operation content, a sample number 70124, and a result 70125 which indicates the diagnosis result.

[0056] <Examples of information held by the performance reference value holding unit 202> FIG. 8 is a diagram showing an example of the configuration of performance reference value information 801 held by the performance reference value holding unit 202 included in the storage device 20 of the performance measurement apparatus 1. As shown in FIG.

[0057] The performance reference value information 801 is management information that includes, for each model 8011, an operation 8012, a standard 8013, and an allowable error 8014.

[0058] The model 8011 is information indicating the model name of the construction machine. The operation 8012 is the operation of the corresponding model, for example, arm crowding, bucket crowding, etc. The standard 8013 is, for example, the reference time required for the corresponding operation (for example, 3.5 seconds). The allowable error 8014 indicates the range (tolerance: for example, ±0.4 seconds) within which the operation can be determined to be normal even if it does not match the standard 8013.

[0059] The operation of the diagnostic target can be identified by using the performance reference value information 801. For example, if the diagnostic result of the health diagnostic unit 102 is 3.6 seconds, and the reference value of the performance reference value information for the operational arm pull in the compatible model is 3.5 seconds with an allowable error range of ±0.4 seconds, the operation of the diagnostic target can be identified as an arm pull.

[0060] <Examples of Information Stored in the Operating Range Reference Value Storage Unit 203> FIG. 9 is a diagram showing an example of the configuration of operating range reference value information 901 held by the operating range reference value holding unit 203 included in the storage device 20 of the performance measurement apparatus 1. As shown in FIG.

[0061] The motion range reference value information 901 is management information that includes a motion 9012 , a start angle 9013 , and an end angle 9014 for each model 9011 .

[0062] The model 9011 is information indicating the model name of the construction machine. The operation 9012 is an operation of the corresponding model, and includes, for example, arm crowding, bucket crowding, etc. The start angle 9013 is information indicating the angle at which the corresponding operation starts. The end angle 9014 is information indicating the angle at which the corresponding operation ends. For example, for a boom raising operation, the start angle is 0 degrees and the end angle is 90 degrees.

[0063] <Example of information stored in the operation-specific representative waveform storage unit 204> FIG. 10 is a diagram showing an example of the configuration of the operation-specific representative waveform information 1001 stored in the operation-specific representative waveform storage unit 204 included in the storage device 20 of the performance measurement device 1. As shown in FIG.

[0064] The representative waveform information by operation 1001 is composed of acquisition time information at which a representative waveform was acquired and the corresponding waveform for each operation (100111, 100112) for each model 10011. It is assumed that the representative waveform information by operation 1001 stores different waveforms for all operations available for each model.

[0065] <Examples of information stored in the recommendation information storage unit 205> FIG. 11 is a diagram showing an example of the structure of recommendation information 1101 stored in the recommendation information storage unit 205 included in the storage device 20 of the performance measurement device 1. As shown in FIG.

[0066] The recommendation information 1101 is made up of a drift value 11011 and a recommendation content (recommended information) 11012 of a countermeasure corresponding to the drift value.

[0067] The drift value 11011 is information that indicates how far the measurement result deviates from the reference value, and is displayed as a percentage. For example, the ideal arm crowd duration for model M1 is 3.2 seconds, with a tolerance of ±0.3 seconds, which corresponds to (0.3 / 3.2) x 100 = 9.4%. If the measurement time were 3.4 seconds, D1 would be ((3.4 - 3.2) / 3.2) x 100, or 6.25%. In this case, D1 is lower than the 9.4% indicated by the drift value 11011, so the recommendation content 11012 in this case would be "The relevant part of the construction machine in question is in a healthy state. No action is required." On the other hand, for example, if the drift D2% over the measurement time is higher than 9.4% indicated by the drift value 11011, the recommendation content 11012 will be "There is a problem with the soundness of the relevant part of the construction machine. If possible, please contact the maintenance staff and show them this report."

[0068] In this way, it is possible to present recommended information in various forms, such as by setting the importance (importance of action) according to the degree of deviation from the reference value.

[0069] <Examples of information held by the action list holding unit 206> FIG. 12 is a diagram showing an example of the structure of action list information (table) 1201 held by the action list holding unit 206 included in the storage device 20 of the performance measurement device 1. As shown in FIG.

[0070] The action list information 1201 is made up of a state 12011 and an operation 12012 for each model.

[0071] The status 12011 is information indicating whether or not the operation diagnosis has been completed. If the operation diagnosis has been completed, it is indicated by a "◯" mark, and if the operation diagnosis has not been completed, it is indicated by an "X" mark, thereby indicating the diagnosis status of the corresponding operation.

[0072] Additionally, columns (not shown) such as result (diagnosis result) 12013, reference (reference value) 12014, tolerance (tolerance range relative to reference value) 12015, and others may be added to allow the user to visualize the overall condition of the machine.

[0073] The action list information 1201 can indicate whether a health diagnosis has been completed for a specific model of construction machine, allowing the user to check available actions and keep track of actions that have been diagnosed and actions that have not yet been performed.

[0074] The storage device 20 of the performance measurement device 1 may be configured to store in advance in the action list holding unit 206 action list information 1201 in which the status 12011 is blank (or the status of all operations is incomplete (x)) for all models of all construction machines. Also, when the operator starts diagnosing the target construction machine 3, all operations of the construction machine 3 may be registered in the action list holding unit 106 as action list information 1201. If there is a construction machine of the same model that has been diagnosed in the past, it is possible to reuse the action list information 1201 from that previous use (the information on the previous diagnosis result 12013 and status 12011 may be reset).

[0075] <Input and output information> FIG. 13 is a diagram showing an example of input information 1301 to the performance measurement device 1 and an example of output information 1302 from the device 1 in comparison.

[0076] The input information 1301 may include, for example, the model of the construction machine 13011, a start instruction (pressing the start button) to start collecting data before diagnosis, and a stop instruction (pressing the stop button) to stop / end the diagnosis 13012. However, the input information 1301 is not limited to these. It is also possible to automatically stop the diagnosis after a certain period of time.

[0077] The output information 1302 may include, for example, an operation list (with completion status mark) 13021, construction machine operation 13022, operation range reference value 13023, health 13024, reference value (including tolerance) 13025, recommendation 13026, report 13027, and history log 13028.

[0078] Outputting the operation list 13021 allows the user to keep track of which machine operations have already been diagnosed and which operations have not yet been diagnosed. As shown in Figure 12, operations that have been diagnosed can include a mark ("o") indicating that the diagnosis is complete.

[0079] By outputting the construction machine operation 13022, it becomes possible to check the construction machine operation (e.g., arm crowd) that was automatically classified in the diagnosis that was just performed.

[0080] Outputting the operating range reference value 13023 can provide information for the operator of the construction machine to confirm whether the operation has been performed correctly. For example, by outputting the reference start angle and reference end angle, the operator can compare them with the angles of the angle sensor 31 built into the construction machine 3 and confirm whether the operating range matches the reference value.

[0081] By outputting the health status 13024, it is possible to provide information for confirming whether or not the part (e.g., arm) that performs the operation is in a healthy state through the operation diagnosis of the target. As information indicating the health status 13024, for example, it is conceivable to output the results of a test that has been recently performed.

[0082] By outputting the reference value (including the tolerance) 13025, it is possible to provide information for confirming the reference value (including the tolerance) for diagnosis of a specific operation of a specific construction machine.

[0083] By outputting the recommendation 13026, it is possible to provide information (recommendations) for the operator (user) to interpret the information on soundness 13024 and determine whether it is necessary to contact for maintenance.

[0084] The report 13027 can be output as information obtained by adding raw data to all the above outputs 13021 to 13026.

[0085] By outputting the history log 13028, it is possible to provide information useful for the user to track all past diagnosis contents.

[0086] <Example of GUI configuration> FIG. 14 is a diagram showing an example of the configuration of a GUI (Graphical User Interface) displayed on the display screen of the performance measuring device 1 or the display screen of the user terminal 4. Examples of the GUI include an input GUI (input screen) _G1, an in-operation (execution screen) GUI_G2, and a diagnosis result display GUI (result screen) _G3.

[0087] On the input GUI (input screen) _G1, the model (model number) of the construction machine can be input. Also, on the input GUI (input screen) _G1, the diagnosed operations and the undiagnosed operations can be confirmed. In the example of FIG. 14, six operations are prepared, and it is shown that only the first two are diagnosed. Note that on the input GUI (input screen) _G1, the method of starting the diagnosis may be displayed, or the diagnosis may be started simply by pressing the start button.

[0088] The Running (Running Screen) GUI_G2 shows that the operation of the construction machine selected by the user (or operator) is currently running. After the operation is completed, the operator will press the stop button.

[0089] The GUI for displaying diagnostic results (result screen)_G3 displays the classified actions and a reference range for the operator to confirm, but may also display an instruction to prompt the operator to confirm the action range. The diagnostic results are also displayed along with the reference and acceptable range for reference, and drift values ​​and recommendations are also displayed. Furthermore, an action list (table: see Figure 12) is displayed along with information on actions marked as completed (◯) or incomplete (×). In the example of Figure 14, action A13 is marked as completed (◯), and the diagnostic results are entered in the action list.

[0090] The diagnostic result display GUI (result screen)_G3 can include a save button and a repeat execution instruction button. When the operator (user) presses the save button, the report and raw data are saved in the history log. If the measurement was not performed correctly, the operating range was incorrect, or other problems occurred, the operator (user) can press the repeat button, and the display screen can be configured to transition to the input GUI (input screen)_G1 without recording the erroneous measurement results, etc.

[0091] <Performance measurement and diagnostic processing> FIG. 15 is a flowchart for explaining the performance measurement and diagnosis process according to this embodiment.

[0092] (i) Step S1501 When the operator places the performance measuring device 1 (or a terminal on which the functions of the device are implemented (a smartphone with a built-in accelerometer)) in a predetermined location on the construction machine to be diagnosed (for example, in a cup holder in a cabinet or in a box on the floor) so that it can detect (pick up) vibrations while the construction machine is in operation, and instructs the performance measuring device 1 to start diagnosis (for example, by pressing the diagnosis start button), the processor 10 accepts the instruction. Note that the placement location may differ depending on the type of sensor.

[0093] (ii) Step S1502 The processor 10 prompts the operator to input (select) the model of the construction machine, and accepts input of model information of the construction machine by the operator.

[0094] (iii) Step S1503 The operator checks the undiagnosed operations of the target construction machine from the action list information 1201 (see FIG. 12), and selects the next operation to be diagnosed. The action list information 1201 lists all operations to be diagnosed, with diagnosed operations marked with a completed (◯) and operations to be undiagnosed marked with an incomplete (×). When the operator selects an operation to be diagnosed, the processor 10 accepts the selection. Note that examples of operations of the construction machine that the operator can select include arm crowding, arm dumping, boom raising, boom lowering, bucket crowding, and bucket dumping.

[0095] (iv) Step S1504 The information acquisition unit 101 of the processor 10 starts acquiring related data. For example, when an operator presses a data acquisition start button on the screen of the performance measurement device 1 (smartphone), the information acquisition unit 101 activates at least one of the sensor group 2 (for example, the accelerometer 21) and collects data acquired by the sensor.

[0096] (v) Step S1505 When the operator operates the construction machine and performs the operation selected in step S1504 (e.g., arm crowding), the health diagnosis unit 102 collects data acquired by at least one of the sensor group 2 during the operation and stores it in the data storage unit 201.

[0097] (vi) Step S1506 The processor 10 analyzes the data collected in step S1505 and generates some analytical results.

[0098] For example, the health diagnosis unit 102 calculates the time taken for an action from data acquired by a sensor (for example, the peak value of a vibration waveform acquired by an accelerometer), stores the analysis data (vibration waveform and inter-peak time) in the data storage unit 201, and also passes it to the action classification unit 103.

[0099] The action classification unit 103 acquires the analysis data acquired by the health diagnosis unit 102, compares the analysis data (e.g., vibration waveform) with waveforms previously stored in the action-specific representative waveform storage unit 204, and identifies the action to be diagnosed.

[0100] The basic performance measurement diagnosis unit 104 acquires data on the operating range standard value corresponding to the operation identified by the operation classification unit 103 from the operating range standard value storage unit 203, compares the operating range standard value with the analysis data, and determines whether the construction machine being diagnosed is in a healthy state with respect to the operation (to what extent it deviates from a healthy state).

[0101] (vii) Step S1507 The processor 10 transfers the operations identified by the operation classification unit 103, the health determined by the basic performance measurement diagnosis unit 104, and the operation range (including information on the operation range reference value) to, for example, a user terminal 4 (a mobile terminal (smartphone) or a computer (PC)), and displays the information on its output screen.

[0102] More specifically, it outputs which operation the operator (user) selected, the range of operation (start position and stop position) to confirm whether the operator performed the operation correctly, and a comparison of the soundness of the construction machine (the execution time of the operation) with a reference value (reference value at the time of manufacture).This information can be used as a reference for determining what state is sound and what state is not sound.

[0103] (viii) Step S1508 The processor 10 obtains the recommendation content 11012 (see Figure 11) corresponding to the diagnosis result of the basic performance measurement diagnosis unit 104 from the recommendation information storage unit 205, and displays it, for example, on the screen of the user terminal 4 (see GUI (result screen)_G3 for displaying diagnosis results (Figure 14)).

[0104] As explained in Fig. 11, the recommendation content 11012 is generated (selected) based on how much the soundness of the relevant operation of the construction machine deviates from the reference value (the reference value at the time of manufacture). For example, if the soundness of the construction machine deviates by D% from the manufacturing reference value, a recommendation such as "There is a problem with the soundness of the relevant part of the construction machine. If possible, please contact the maintenance person and show them this report" can be made.

[0105] (ix) Step S1509 The operator determines whether the sensor data has been collected appropriately, and if so, presses the Save button. If not, presses the Repeat button. Processor 10 determines which button was pressed. If the Save button was pressed (Yes in step S1509), the process proceeds to step S1510. If the Repeat button was pressed (No in step S1509), the process proceeds to step S1504.

[0106] (x) Step S1510 The processor 10 stores the report (operation type of the construction machine, diagnosis results, and recommendation information) and raw data in a storage device as a history log. These reports and raw data can be referenced when further analysis is required.

[0107] (xi) Step S1511 The processor 10 assigns a completion (diagnosed) mark (◯) to the diagnosed operation in the action list of the construction machine to be diagnosed.

[0108] (xii) Step S1512 The processor 10 determines whether diagnosis has been completed for all operations of the construction machine to be diagnosed. If diagnosis has been completed for all operations (Yes in step S1512), the performance measurement diagnosis process ends. If there are any operations that have not been diagnosed (No in step S1512), the process proceeds to step S1504.

[0109] <Example> A: Example 1 (1) Example of a device that implements the functions of the performance measurement device 1 As described above, a smartphone can be used as an example of a main device that implements the functions of the performance measurement device 1. A MEMS (Micro Electro Mechanical System) sensor (such as an accelerometer) built into the smartphone can be used as the main sensor for acquiring data. The data acquired by the sensor (accelerometer) can be processed and analyzed by the smartphone's CPU.

[0110] The memory of the smartphone can be used to store the raw data and the results. In this embodiment, the performance measurement diagnostic processing function is implemented in the form of an application on the smartphone.

[0111] (2) Use Cases Examples of possible use cases (including operator actions) are as follows:

[0112] (i) The operator places the smartphone in the cup holder of the cabinet of the construction machine.

[0113] (ii) The operator starts an application for performance measurement and diagnostic processing on the smartphone.

[0114] (iii) The operator checks the operation of the construction machine to be diagnosed from the operation list (for example, arm cloud).

[0115] (iv) When the operator presses the start button, the sensor (accelerometer) begins acquiring data.

[0116] (v) The operator operates the construction machine and performs arm-crowd operations.

[0117] (vi) During the execution of the operation, the smartphone's accelerometer detects vibrations inside the smartphone housing.

[0118] (vii) After the arm crowding operation is completed, the operator presses the stop button to stop the data acquisition process.

[0119] (viii) The smartphone then begins analyzing the aggregated accelerometer data, which indicates vibration levels and the start and stop times of the arm crowd test.

[0120] (ix) Algorithm configuration (ix-1) Automatic measurement of operation time of construction machinery The start and stop times of construction machine operation can be automatically detected using the data from the accelerometer 21. For example, the maximum point of the waveform data acquired by the accelerometer 21 is detected and subjected to threshold processing. Peak detection is then performed, and the first peak can be considered to be the start time and the last peak the stop time, and the time between these peaks can be considered to be the operation time of the construction machine.

[0121] (ix-2) Automatic classification of construction machinery operations Regarding the operation of the construction machine to be diagnosed, it is possible to automatically detect which operation has been performed by analyzing the peaks of the waveform data from the accelerometer 21. For example, the peak amplitude of the waveform data is detected and pattern matching is performed. Then, the peaks are classified based on the pattern matching results.

[0122] (x) Screen output

[0123] The smartphone screen (Result Screen_G3) displays the type of construction machinery operation (e.g., arm cloud), the operation standard range (e.g., start angle 170 degrees, end angle 10 degrees), operation time, standard time and tolerance, recommendation comments (including drift value), a completion mark (◯) for recently diagnosed operations (e.g., arm cloud), an action list (updated version) including the results, a save button for saving the report and raw data, and a repeat button for repeating the test in case of an error (e.g., an operator error) (e.g., if the operator performs an operation within an operation range that differs from the standard) (see Figure 14).

[0124] B: Example 2 As a variation of the first embodiment, a microcontroller such as Arduino (registered trademark) with a built-in accelerometer can be used. The same processing described in the first embodiment can be repeated (wirelessly or wired) by a microcomputer connected to a computer to perform control and visualize the output. Note that some microcomputers have built-in CPUs and memory, and can function as long as a display device is connected.

[0125] <Summary> (i) According to this embodiment, the performance measuring device 1 (machine performance diagnosis device) performs the following processes: (1) identifies the actually performed operation of a construction machine (e.g., a hydraulic excavator) by comparing sensor waveform data obtained by detecting an actually performed operation (e.g., arm crowding) using a sensor (e.g., an accelerometer 21) with reference waveform data (representative waveform data for each operation) previously stored in a storage device; (2) acquires a performance reference value and a tolerance value (see FIG. 8) corresponding to the identified operation from the storage device, and compares the performance reference value (reference time required for the operation) and the tolerance value with a characteristic value of the actually performed operation (e.g., the time between peaks in the sensor waveform: the actual time required for one operation (operation time)) to determine the soundness of the construction machine. In other words, if the characteristic value (operation time) of the operation is within the tolerance range of the reference value, the operation of the construction machine is determined to be in a sound state; otherwise, the operation is determined to have a problem. The health assessment results are then output to the display of a user terminal 4, such as a smartphone equipped with the performance measurement device 1, or to the display of a user terminal 4, such as a smartphone, that is independent of the performance measurement device 1. This allows the operator to view the health assessment results and determine whether maintenance of the construction machine is necessary.

[0126] (ii) The performance measuring device 1 may output values ​​detected by angle sensors of the angle of a predetermined part of the construction machine (for example, an arm or boom) at the start position and the angle of a predetermined part at the end position when an operation of the construction machine is actually performed, together with the judgment result of the soundness of the construction machine, to the display unit. This allows the operator to determine whether the operation was performed correctly. If the operation was not performed correctly, the diagnosis result for that operation can be discarded (reset), and the diagnosis for the same operation can be performed again.

[0127] (iii) The performance measuring device 1 may further store in the storage device 20 multiple types of recommendation information regarding countermeasures according to the degree of deviation from the performance reference value, and may output the recommendation information corresponding to the soundness judgment result together with the judgment result to the display unit. When there is a problem with the soundness of the construction machine, even an inexperienced operator will be able to recognize what countermeasures should be taken.

[0128] (iv) The performance measuring device 1 further stores action list information in the storage device 20 that indicates the diagnostic status (whether the diagnosis is complete or not) and the diagnostic results for each of the multiple operations of the construction machine, and updates the action list information by inputting information indicating that the diagnostic status is complete and the judgment results for operations for which the soundness judgment process has been completed, and outputs the updated action list information to the display unit. In this way, it becomes possible to immediately recognize to what extent the diagnosis of the entire operation of the construction machine being diagnosed has been completed.

[0129] (v) When a save instruction from the operator (pressing the save button displayed on the result display screen_G3) is detected, the performance measuring device 1 saves the judgment results and the detection data of the operations that were actually performed as a diagnosis history log (see FIG. 7) in the storage device 20. By referring to the diagnosis history log, it is possible to check whether the construction machine has undergone regular health diagnosis of each operation, and also to check whether deterioration is gradually progressing even if there is no problem with the health of the machine.

[0130] On the other hand, when a repeat instruction from the operator (pressing the repeat button displayed on the result display screen_G3) is detected, the performance measuring device 1 resets the judgment result and the sensor detection data for the identified operation, and performs a diagnosis on the same operation again. This means that if the operator fails to properly perform the operation of a part of the construction machine that is to be diagnosed (for example, an arm), data related to that operation does not need to be left in the diagnosis history log, making it easier to verify the diagnosis results.

[0131] (vi) As shown in FIG. 13, the only information the operator needs to input into the performance measurement device 1 is the construction machine model information and instructions to start and stop the diagnosis. Meanwhile, the output information of the performance measurement device 1 includes the health assessment results, information on the type of identified operation, information on the operating range reference value for the identified operation, the performance reference value for the identified operation, recommendation information corresponding to the assessment results, and sensor-detected data for the identified operation. In this way, the operator only needs to input the minimum amount of information to obtain appropriate diagnostic results (the number of input items can be reduced to an absolute minimum), thereby reducing the burden on the operator. Furthermore, even inexperienced operators can obtain appropriate diagnostic results. As a result, the possibility of human error can be reduced.

[0132] (vii) In the above example, the history log is stored on a storage device, but by transferring it to a server / cloud server and managing it, it is possible to unify and centralize the data and improve updateability.

[0133] (viii) The functions of the embodiments of the present disclosure can also be realized by software program code. In this case, a storage medium on which the program code is recorded is provided to a system or device, and the computer (or CPU or MPU) of the system or device reads the program code stored on the storage medium. In this case, the program code read from the storage medium itself realizes the functions of the above-mentioned embodiments, and the program code itself and the storage medium on which it is stored constitute the present disclosure. Examples of storage media for providing such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, optical disks, magneto-optical disks, CD-Rs, magnetic tapes, non-volatile memory cards, and ROMs.

[0134] In addition, an operating system (OS) running on a computer may perform some or all of the actual processing based on instructions in the program code, and the functions of the above-described embodiments may be realized by this processing. Furthermore, after the program code is read from a storage medium and written to a memory on a computer, a CPU of the computer may perform some or all of the actual processing based on instructions in the program code, and the functions of the above-described embodiments may be realized by this processing.

[0135] Furthermore, the program code of the software that realizes the functions of the embodiments may be distributed via a network and stored in a storage means such as a hard disk or memory of the system or device, or in a storage medium such as a CD-RW or CD-R, so that when in use, the computer (or CPU or MPU) of the system or device reads and executes the program code stored in the storage means or storage medium.

[0136] Finally, it should be understood that the processes and techniques described herein are not inherently related to any particular apparatus, but may be implemented by any suitable combination of components. Furthermore, various types of general-purpose devices can be used in accordance with the teachings described herein. It may prove useful to construct specialized apparatus to perform the method steps described herein. Various inventions can also be formed by suitable combinations of multiple components disclosed in the embodiments. For example, some components may be omitted from all of the components shown in the embodiments. Furthermore, components from different embodiments may be combined as appropriate. While the present disclosure has been described with reference to specific examples, these are intended in all respects to be illustrative and not limiting. Those skilled in the art will recognize that numerous combinations of hardware, software, and firmware are suitable for practicing the present disclosure. For example, the described software can be implemented in a wide variety of programming or scripting languages, including assembler, C / C++, Perl, Shell, PHP, Java, etc.

[0137] Furthermore, in the above-described embodiment, the control lines and information lines are those that are considered necessary for the explanation, and not all control lines and information lines in the product are necessarily shown. All components may be interconnected. [Explanation of symbols]

[0138] 1 Performance measurement device 2 Sensor group 3. Construction machinery 4. User terminal 10 processors 20 Storage Devices 30 Communication Devices 21 Accelerometer 22 microphones 23 Camera 101 Information acquisition department 102 Health Diagnosis Department 103 Motion classification section 104 Basic Performance Measurement and Diagnostics Unit 201 Data Storage Department 202 Performance standard value storage unit 203 Operating range reference value holding unit 204 Representative waveform holding section for each operation 205 Recommendation Information Storage Unit 206 Action List Holder

Claims

1. A machine performance diagnostic device that diagnoses the soundness of operation of a construction machine, a storage device for storing reference waveform data for each of a plurality of operations of the construction machine configured for each model of the construction machine, a performance reference value and an allowable error value for each of the plurality of operations, and action list information indicating a diagnostic state and a diagnostic result for each of the plurality of operations of the construction machine; a processor that executes a process for diagnosing the soundness of the construction machine, The processor: a process of outputting the action list information corresponding to the information on the model of the construction machine input to an input unit to a display unit; a process of acquiring the reference waveform data corresponding to the model information of the construction machine from the storage device, and comparing the acquired reference waveform data with sensor waveform data obtained by detecting the operation actually performed by the construction machine with a sensor, thereby identifying the operation actually performed; a process of acquiring the performance reference value and the tolerance value corresponding to the identified operation from the storage device, comparing the acquired performance reference value and the tolerance value with the characteristic value of the actually executed operation obtained from the sensor waveform data, determining the soundness of the construction machine, and outputting the determined soundness of the construction machine to the display unit; When an instruction to store the judgment result and the sensor waveform data in the storage device is input to the input unit, in relation to the operation of performing the process of judging the soundness of the construction machine, a process of updating the action list information by adding information indicating that the diagnosis status is complete and the judgment result to the action list information, and outputting the updated action list information to the display unit; Machine performance diagnostic equipment.

2. In claim 1, The processor identifies the actually performed operation by pattern matching the sensor waveform data of the actually performed operation with the reference waveform data.

3. In claim 1, the performance reference value indicates a reference time for each of the plurality of operations, and the tolerance value is information indicating how much difference from the reference time is required for the operation to be sound, The processor detects the start and end times of operations actually performed by the construction machine from the sensor waveform data, calculates the duration of the actually performed operation accordingly, and determines the soundness of the construction machine by comparing the calculated duration with the reference time and the allowable error value as the feature value.

4. In claim 1, A machine performance diagnosis device, wherein the sensor waveform data is vibration waveform data obtained by detecting vibrations of the construction machine using an accelerometer when the construction machine is actually operating.

5. In claim 1, The processor outputs values ​​detected by an angle sensor of the angle of a specified part of the construction machine at the start position and the angle of the specified part at the end position when the operation of the construction machine is actually performed, together with the judgment result of the health of the construction machine, to the display unit.

6. In claim 1, the storage device further stores a plurality of types of recommendation information relating to measures to be taken depending on the degree of deviation from the performance reference value; The processor acquires the recommendation information corresponding to the judgment result from the storage device, and outputs the recommendation information together with the judgment result to the display unit.

7. In claim 1, When the processor detects a repeat instruction, it resets the determination result and the data detected by the sensor for the identified operation, and performs a diagnosis on the same operation again.

8. In claim 1, the storage device further holds a plurality of types of recommendation information relating to measures to be taken depending on the degree of deviation from the performance reference value, and information on an operating range reference value indicating a standard for an operating range of the specified operation; The processor: Receives instructions to start and stop diagnosis as input information, A machine performance diagnosis device that outputs, as output information, information on the type of the identified operation, information on the operation range standard value of the identified operation, the performance standard value of the identified operation, the recommendation information corresponding to the judgment result, and detection data of the identified operation by the sensor.

9. Construction machinery and a sensor group including at least one sensor; A user terminal; The machine performance diagnosis device according to claim 1, A construction machinery diagnostic system in which the processor of the machinery performance diagnostic device outputs the results of the processing for determining the soundness of the construction machinery to the display unit of the user terminal.

10. In claim 9, A construction machinery diagnostic system in which the sensor group and the machinery performance diagnostic device are implemented inside the user terminal.

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