Mechanical performance diagnosis device, and construction machine diagnosis 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 diagnosis device and a construction machine diagnosis system. [Background technology]

[0002] With regard 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 interruptions to construction work. Basic performance refers to the inherent performance and standard specifications of the construction machinery. In this regard, the market demands that tools for automatic self-diagnosis of failures (automatic self-diagnosis tools) be easy to use even for unskilled personnel, inexpensive, and easy to use.

[0003] For example, Patent Document 1 discloses an automatic self-diagnosis technology that, in order to shorten diagnosis time, diagnoses the presence or absence of abnormalities 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 from 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] The basic performance measurement requires different vehicle postures, movements, and procedures depending on the part to be diagnosed, and it is necessary to respond to each diagnosis part. Therefore, when carrying out the measurement, it is necessary to check the procedure manual and confirm the vehicle postures, movements, and measurement procedures that can be taken for each diagnosis target, which makes the advance preparations complicated. In addition, when actually carrying out the measurement work, it is necessary to prepare special equipment, and since some measurement methods affect the diagnosis results, attention must be paid to the timing of the measurement, etc., which depends on the skill of the person who measures, 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 including: 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 for diagnosing the soundness of the construction machine, wherein the processor executes a process of identifying the operation that was actually performed by comparing sensor waveform data obtained by detecting an operation actually performed by the construction machine with the reference waveform data held in the storage device; and a process of acquiring from the storage device a performance reference value and an allowable error value corresponding to the identified operation, and comparing the acquired performance reference value and allowable error value with a characteristic value 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 of the present specification and the accompanying drawings. Also, aspects of the present disclosure may be realized and realized by the elements and combinations of various elements and aspects of 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. Effect of the Invention

[0009] According to the technology disclosed herein, it is possible to reduce the workload of an operator (user) when diagnosing a construction machine, and to automatically realize a highly accurate and reliable health diagnosis. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram showing a schematic configuration example of a construction machine diagnosis system according to an embodiment of the present invention; [Diagram 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. [Diagram 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 showing an example of the internal functional configuration of a health diagnostic unit 102 of the performance measurement device 1. FIG. [Diagram 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 showing an example of the internal functional configuration of a basic performance measurement diagnosis unit 104 of the performance measurement device 1. FIG. [Figure 7] 2 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 the performance measuring apparatus 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 a storage device 20 of a performance measuring 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 apparatus 1. FIG. [Figure 10] 1 is a diagram showing an example of the configuration of action-specific representative waveform information 1001 stored in an action-specific representative waveform storage unit 204 included in a storage device 20 of the performance measurement apparatus 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] 1 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 a comparison between an example of input information 1301 to a performance measuring device 1 and an example of output information 1302 from the device 1. FIG. [Figure 14] 2 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. FIG. [Figure 15] 1 is a flowchart for explaining a performance measurement diagnosis process according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

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

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

[0013] The performance measuring 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 a number of different sensors that can be used in the application of health check of the construction machine, and can include, for example but not limited to, an accelerometer 21, a microphone 22, and a camera 23. The accelerometer 21 is a microelectromechanical system (MEMS) scale sensor that can be incorporated into a device to measure acceleration with the ability to detect gravity and vibration. The microphone 22 can be an independent microphone or a small microphone built into the performance measurement device 1. The camera 23 can be, for example, an independent small camera or a small camera built into the performance measurement device 1 or the user terminal 4.

[0015] The construction machine 3 is, for example, various types of construction machine such as a hydraulic excavator, a wheel loader, a bulldozer, etc. 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 computing device such as a smartphone, a microcontroller, a personal computer (PC), etc.

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

[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 the 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 action-specific representative waveform holding section 204 , a recommendation information holding section 205 , and an action list holding section 206 .

[0019] The operation-specific representative waveform storage unit 204 stores, for example, representative sensor waveforms for each machine operation that serve as a standard for classifying a machine operation 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, recommendation information such as "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 actions related to a specific diagnosis (test) type. Examples of actions to be diagnosed include (a) arm crowding (pulling action), (b) arm dumping (pushing action), (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 operating 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. Note that an example of the sensor data is accelerometer data that detects load vibrations of a construction machine, and an example of the load is an arm.

[0024] The health diagnostic unit 102 processes the data acquired from the information acquisition unit 101, and outputs a diagnostic result indicating the health of a specific machine and the health of a specific load (whether it is in a healthy state or not). For example, the health diagnostic 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 execute arm crowding based on the peak level of the vibration. 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 the processing by the motion classification unit 103 is classifying 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 the reference value (standard value) of the soundness state of the machine operation to be inspected, which is set by the manufacturer, for example. One example of the information on the standard value of the soundness state is information that the arm crowd 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, a reference value (standard value) of the operation range of the construction machine. An example of the operation range reference value information is information that the boom raising 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 part of a function of a processor) and collects the calculation results of the health diagnosis unit 102 and the operation classification unit 103 and compares these with specific reference values ​​(performance reference values ​​obtained from the performance reference value storage unit 202) to diagnose (determine) to what extent 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. The basic performance measurement diagnosis unit 104 then transfers the 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, the information on the operating range reference value and the like 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 grasp whether the construction machine is in a sound condition or not.

[0030] A specific example from the action classification process by the action classification unit 103 to the basic performance measurement diagnosis process by the basic performance measurement diagnosis unit 104 will be described. For example, if the diagnosis by the health diagnosis unit 102 gives a result of 3.6 seconds of the action time, the action classification unit 103 compares the diagnosis result of the health diagnosis unit 102 with the action reference value 3.5±0.4 seconds of the corresponding construction machine stored in the performance reference value storage unit 202, and classifies the action to be diagnosed as arm crowding. Then, the basic performance measurement diagnosis unit 104 sets the reference action range of the arm crowd to a start angle position of 170 degrees and an end angle position of 15 degrees, and checks the numerical values ​​with an angle sensor built into the construction machine to determine whether the action range is correct. Finally, these results are displayed on the display screen of the user terminal of the operator. This makes it possible to inform the operator that the motor of the construction machine performing the 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 any one of the sensors 2 (e.g., an accelerometer). The sampling frequency may be determined in advance, or may be determined by an operator or another 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 is an example of the 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 (such as collecting data for 20 seconds regardless of the length of the test itself) or automatically (asking 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 diagnostic 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 value to the waveform data (waveform signal) acquired by the information acquisition unit 101, and removes the noise signal.

[0039] The feature detection unit 1022 detects features in the waveform signal from which noise has been removed. For example, the feature detection unit 1022 may detect 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 operation of the construction machine, and another peak indicates the stop time of the operation.

[0040] The result extraction unit 1023 extracts information on the soundness 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 a matching pattern (within a predetermined error range).

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

[0046] <Example of internal functional configuration of basic performance measurement diagnosis unit 104> FIG. 6 is a diagram showing an example of the internal functional configuration of the basic performance measurement diagnosis 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 report 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 (judgment) 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 (a specific operation: for example, arm crowding operation) is in a healthy state or not.

[0049] The result reporting unit 1042 creates a report on the soundness 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 soundness 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 an 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 the information (displays it on the display screen). For example, in the case of arm pull, the reference operating range information stored in the operating range reference value storage unit 203 is a start angle position of 170 degrees and an end angle position of 15 degrees, which the operator can confirm with 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 an information set previously stored in the recommendation information storage unit 205.

[0052] <Examples of information stored in 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 measuring apparatus 1. As shown in FIG.

[0053] The history log list is made up 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 result for an operation due to an improper operation by the operator), and diagnosis result (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. A 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 stored in the performance reference value storage 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 measuring apparatus 1. As shown in FIG.

[0057] The performance reference value information 801 is management information including, 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 criterion 8013 is, for example, a reference time (e.g., 3.5 seconds) required for the corresponding operation. The allowable error 8014 indicates a range (tolerance: for example, ±0.4 seconds) within which the operation can be determined to be normal even if it does not match the criterion 8013.

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

[0060] <Example 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 threshold value information 901 held by the operating range threshold 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 including a motion 9012 , a start angle 9013 , and an end angle 9014 for each model 9011 .

[0062] The model number 9011 is information indicating the model name of the construction machine. The operation 9012 is an operation of the corresponding model, for example, arm crowding, bucket crowding, etc. The start angle 9013 is information indicating the start angle of the corresponding operation. The end angle 9014 is information indicating the end angle of the corresponding operation. 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 action-specific representative waveform storage unit 204> FIG. 10 is a diagram showing an example of the configuration of the action-specific representative waveform information 1001 stored in the action-specific representative waveform storage unit 204 included in the storage device 20 of the performance measuring apparatus 1. As shown in FIG.

[0064] The representative waveform information by action 1001 is composed of acquisition time information at which a representative waveform was acquired and the corresponding waveform for each action (100111, 100112) for each model 10011. It is assumed that the representative waveform information by action 1001 stores different waveforms for all actions 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 configuration 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 recommended action content (recommended information) 11012 corresponding to the drift value.

[0067] The drift value 11011 is information indicating how far the measurement result is from the reference value, and is displayed as a percentage. For example, the ideal arm cloud duration for model M1 is 3.2 seconds, with a tolerance of ±0.3 seconds, which corresponds to (0.3 / 3.2)×100=9.4%. If the measurement time were 3.4 seconds, D1 would be ((3.4-3.2) / 3.2)×100, which is 6.25%. In this case, D1 is lower than 9.4% indicated by the drift value 11011, so the recommendation content 11012 in this case would be "The target part of the construction machine in question is in a healthy state. No action is required." On the other hand, for example, when the drift D2% during the measurement time is higher than 9.4% indicated by the drift value 11011, the recommendation content 11012 becomes "There is a problem with the soundness of the relevant part of the construction machine. If possible, contact the maintenance person 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] <Example of information held by the action list holding unit 206> FIG. 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 apparatus 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 diagnosis of the operation has been completed. If the operation has been diagnosed, it is indicated with a "◯" mark, and if the operation diagnosis has not been completed, it is indicated with an "X" mark, thereby making it possible to indicate the diagnosis status of the corresponding operation.

[0072] Additionally, columns such as result (diagnosis result) 12013, criteria (reference value) 12014, tolerance (tolerance range relative to the reference value) 12015, and other columns (not shown) 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 to track actions that have been diagnosed and those that have not yet been performed.

[0074] The storage device 20 of the performance measuring device 1 may be configured to previously store, 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 an operator starts diagnosing a 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 the previous use (the information on the previous diagnosis result 12013 and status 12011 is reset).

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

[0076] The input information 1301 includes, for example, the model of the construction machine 13011, a start instruction (pressing the start button) for starting data collection before diagnosis, and a stop instruction (pressing the stop button) for stopping / ending 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, recommendations 13026, a report 13027, and a 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 diagnosis is complete.

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

[0080] Outputting the motion 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 motion range matches the reference value.

[0081] By outputting the health 13024, it is possible to provide information for confirming whether or not a part (e.g., an arm) performing a motion is in a healthy state by a motion diagnosis of the target. As information indicating the health 13024, for example, the result of a test recently performed may be output.

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

[0083] By outputting 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 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 that helps the user track all past diagnosis details.

[0086] <Configuration Example of GUI> FIG. 14 is a diagram showing a configuration example 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-Execution (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 operations that have been diagnosed and the operations that have not been diagnosed can be confirmed. In the example of FIG. 14, six operations are prepared, and it is shown that only the first two have been 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] In-progress (execution screen) GUI_G2 shows that the operation of the construction machine selected by the user (or operator) is in progress. After the operation is completed, the operator presses the stop button.

[0089] The GUI (result screen)_G3 for displaying diagnostic results displays the classified actions and a reference range for the operator to confirm, but may also display an instruction to the operator to confirm the range of actions. The diagnostic results are also displayed with the reference and acceptable range for reference, and drift values ​​and recommendations are also displayed. In addition, an action list (table: see FIG. 12) is displayed with information on actions marked as completed (◯) or incomplete (×). In the example of FIG. 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 may 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 a history log. If the measurement is not performed correctly, if the operating range is not correct, or if other problems occur, the operator (user) may press the repeat button, so that the display screen transitions to the input GUI (input screen)_G1 without recording the erroneous measurement results, etc.

[0091] <Performance measurement and diagnosis process> FIG. 15 is a flowchart for explaining the performance measurement 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 (such as a smartphone with an accelerometer)) in a predetermined location on the construction machine to be diagnosed (for example, in a cup holder of a cabinet or in a box on the floor) so that it can detect (pick up) vibrations during operation of the construction machine, and instructs the performance measuring device 1 to start diagnosis (for example, by pressing a 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 the 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 as completed (◯) and undiagnosed operations marked as incomplete (×). When the operator selects the operation to be diagnosed, the processor 10 accepts the selection. The operations of the construction machine selected by the operator include, for example, arm crowding, arm dumping, boom raising, boom lowering, bucket crowding, bucket dumping, etc.

[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 operates 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 the data in the data storage unit 201.

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

[0098] For example, the health diagnosis unit 102 calculates the time taken for an action from data acquired by a sensor (e.g., 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, and compares and matches the analysis data (e.g., vibration waveform) with waveforms previously stored in the action-specific representative waveform storage unit 204 to identify the action to be diagnosed.

[0100] The basic performance measurement diagnosis unit 104 acquires data on operating range standard values ​​corresponding to the operations 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 healthiness determined by the basic performance measurement diagnosis unit 104, and the operation range (including information on the operation range reference values) 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 and stop positions) to check if the operator performed the operation correctly, and a comparison of the soundness of the construction machine (time it takes to perform 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 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 contents 11012 are generated (selected) based on the degree to which 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, contact the maintenance staff and show them this report" can be made.

[0105] (ix) Step S1509 The operator determines whether the sensor data has been properly collected, and if so, presses the Save button, or if not, presses the Repeat button. The processor 10 determines which button has been pressed. If the Save button has been pressed (Yes in step S1509), the process proceeds to step S1510. If the Repeat button has been 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 result, and recommendation information) and the 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 gives a completion (diagnosed) mark (◯) to the diagnosed action 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 undiagnosed operations remain (No in step S1512), the process proceeds to step S1504.

[0109] <Example> Example A: (1) Examples of devices that implement 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 measuring 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 functionality of the performance measurement diagnostic process is implemented in the form of an application on the smartphone.

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

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

[0113] (ii) The operator starts an application relating to the performance measurement and diagnosis process of the smartphone.

[0114] (iii) The operator checks the operation of the construction machine to be diagnosed from the operation list (e.g., 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) While the action is being performed, 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 when the arm cloud test started and stopped.

[0120] (ix) Algorithm configuration (ix-1) Automatic measurement of operation time of construction machinery The start and stop times of the 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 regarded as the start time and the last peak as the stop time, and the time between these peaks can be regarded as the operation time of the construction machine.

[0121] (ix-2) Automatic classification of construction machinery operations With regard to the operation of the construction machine to be diagnosed, it is possible to automatically detect which operation has been performed by performing peak analysis of the waveform data by 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, reference time and allowable error, recommendation comments (including drift value), a completion mark (◯) for recently diagnosed operations (e.g., arm cloud), an action list (updated version) including the result display, 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 a different operation range from the standard) (see Figure 14).

[0124] B: Example 2 As a modification of the first embodiment, a microcontroller such as Arduino (registered trademark) with a built-in accelerometer can be used. The same process 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. Some microcomputers have a built-in CPU 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 diagnosing device) performs the following processes: a process of identifying an actually performed operation by comparing sensor waveform data obtained by detecting an actually performed operation (e.g., arm crowding) of a construction machine (e.g., a hydraulic excavator) with a sensor (e.g., an accelerometer 21) and reference waveform data (representative waveform data for each operation) stored in advance in a storage device; a process of acquiring a performance reference value and an allowable error value (see FIG. 8) corresponding to the identified operation from the storage device, comparing the performance reference value (reference time required for the operation) and the allowable error 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)), and judging the soundness of the construction machine. In other words, if the characteristic value (operation time) of an operation is within the allowable error range of the reference value, the operation of the construction machine is judged to be in a sound state; otherwise, the operation is judged to have a problem with soundness. The health determination result is then output to a display unit of a user terminal 4, such as a smartphone equipped with the performance measuring device 1, or to a display unit of a user terminal 4, such as a smartphone independent of the performance measuring device 1. This allows the operator to see the health determination result and determine the need for maintenance of the construction machine.

[0126] (ii) The performance measuring device 1 may output values ​​detected by angle sensors of the angle of a specific part (e.g., arm or boom) of the construction machine at the start position and the angle of a specific part at the end position when the construction machine operation is actually performed, together with the judgment result of the soundness of the construction machine, to the display unit. This allows the operator to judge whether the operation was performed correctly. If it was not correct, 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 a number of types of recommendation information regarding measures to be taken 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 measures should be taken.

[0128] (iv) The performance measuring device 1 further holds in the storage device 20 action list information indicating the diagnostic status (whether diagnostics are complete or not) and 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 result for operations for which the process of judging soundness has been completed in the action list information, 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 has been completed in the construction machine to be diagnosed.

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

[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 of the identified operation, and performs diagnosis again for the same operation. This makes it easier to verify the diagnosis result, since data on the operation does not need to be left in the diagnosis history log when the operator fails to properly perform the operation of a part of the construction machine that is to be diagnosed (e.g., an arm, etc.).

[0131] (vi) As shown in FIG. 13, the information that the operator should input to the performance measuring device 1 is only the information on the model of the construction machine and instructions to start and stop the diagnosis. On the other hand, the output information of the performance measuring device 1 includes the judgment result on the soundness, the information on the type of the identified operation, the information on the operation range reference value of the identified operation, the performance reference value of the identified operation, the recommendation information corresponding to the judgment result, and the detection data of the identified operation by the sensor. In this way, the operator can obtain an appropriate diagnosis result by inputting only the minimum information (the number of input items can be reduced to an extreme extent), so that the burden on the operator can be reduced. Also, even an operator with little experience can obtain an appropriate diagnosis result. 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, data can be unified and centralized, and updateability can be improved.

[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 in the storage medium. In this case, the program code itself read from the storage medium 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 supplying 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] Also, an operating system (OS) running on a computer may perform all or a part of the actual processing based on the instructions of the program code, and the functions of the above-mentioned embodiments may be realized by the processing. Furthermore, after the program code read from a storage medium is written into a memory on a computer, a CPU of the computer may perform all or a part of the actual processing based on the instructions of the program code, and the functions of the above-mentioned embodiments may be realized by the processing.

[0135] Furthermore, the program code of the software that realizes the functions of the embodiments may be distributed over 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 used, the computer (or CPU or MPU) of the system or device reads out 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. Moreover, various types of general purpose devices may be used in accordance with the teachings described herein. It may prove beneficial to construct specialized apparatus to perform the steps of the methods described herein. Also, various inventions may be formed by suitable combinations of multiple components disclosed in the embodiments. For example, some components may be omitted from all components shown in the embodiments. Furthermore, components across different embodiments may be combined as appropriate. Although the present disclosure has been described with reference to specific examples, these are intended to be illustrative and not limiting in all respects. Those skilled in the art will recognize that there are numerous combinations of hardware, software, and firmware suitable for implementing the present disclosure. For example, the described software may be implemented in a wide variety of programming or scripting languages, such as assembler, C / C++, perl, Shell, PHP, Java, and the like.

[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 of the control lines and information lines in the product are necessarily shown. All of the components may be connected to each other. [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 Microphone 23 Camera 101 Information acquisition department 102 Health Diagnosis Department 103 Motion classification section 104 Basic Performance Measurement and Diagnosis Section 201 Data Storage Department 202 Performance standard value storage unit 203 Operating range reference value storage unit 204 Representative waveform holding section for each operation 205 Recommendation information storage unit 206 Action List Holder

Claims

1. A machine performance diagnosis device for diagnosing the soundness of an operation of a construction machine, comprising: 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, to a display unit, the action list information corresponding to the information on the type of the construction machine inputted to an input unit; a process of acquiring the reference waveform data corresponding to information on the model of the construction machine from the storage device, and comparing the acquired reference waveform data with sensor waveform data obtained by detecting an actually performed operation of the construction machine with a sensor, thereby identifying the actually performed operation; a process of acquiring the performance standard value and the allowable error value corresponding to the specified operation from the storage device, comparing the acquired performance standard value and the allowable error value with a feature value in the actually executed operation obtained from the sensor waveform data, judging the soundness of the construction machine, and outputting the judged result of the 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, 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, in relation to an operation of judging the soundness of the construction machine when the input unit is input; A machine performance diagnostic device that performs the following:

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 allowable error value is information indicating how much of a difference from the reference time is required for the operation to be considered sound; The processor detects the start and end times of an operation actually performed by the construction machine from the sensor waveform data, calculates the duration of the operation actually performed 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 by 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 soundness of the construction machine, to the display unit, in a machine performance diagnosis device.

6. In claim 1, the storage device further stores a plurality of types of recommendation information regarding measures to be taken according to the degree of deviation from the performance reference value; The processor obtains 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 judgment result and the detection data of the specified operation by the sensor, 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 regarding measures to be taken according to 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 operating 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 by the sensor of the identified operation.

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 diagnosis system, wherein the processor of the machinery performance diagnosis 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 group of sensors and the machinery performance diagnostic device are implemented inside the user terminal.

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