JP6813517B2

JP6813517B2 - Machining abnormality detection device and machining abnormality detection method

Info

Publication number: JP6813517B2
Application number: JP2018000899A
Authority: JP
Inventors: 研二竹中; 鈴木　敦; 敦鈴木; 修木原; 猛森下; 千帆奥村; 前田　和彦; 和彦前田; 信治太田; 榊原　健二; 健二榊原; 吉田　和彦; 和彦吉田; 一裕八田
Original assignee: 株式会社竹中電機
Priority date: 2018-01-08
Filing date: 2018-01-08
Publication date: 2021-01-13
Anticipated expiration: 2038-01-08
Also published as: JP2019119015A

Description

本発明は、被加工物であるワークを加工する刃具の異常たとえば欠損、折れ又は寿命などを検出する加工異常検出装置および加工異常検出方法に関する。 The present invention relates to a machining abnormality detecting device and a machining abnormality detecting method for detecting an abnormality, for example, a defect, a breakage, or a life of a cutting tool for machining a workpiece which is a workpiece.

特許文献１には、波形処理手段が各主軸モータの負荷電流の分散を算出して刃具の折損などに影響のない波形変化を取り除き、判断手段が主軸モータ毎に電流データを連結して刃具の状態を予兆判断する刃具診断装置が開示されている（要約「解決手段」の欄参照）。即ち、特許文献１は、判断手段がいずれかの刃具の折損の予兆が発生していると判断したら、対象となる工作機械の制御装置に停止信号を入力して加工を停止（「請求項４」参照）させれば、刃具の折損などの不具合の発生を未然に防ぐことができる（段落番号「００２８」参照）。 In Patent Document 1, the waveform processing means calculates the distribution of the load current of each spindle motor to remove the waveform change that does not affect the breakage of the cutting tool, and the determining means connects the current data for each spindle motor to the cutting tool. A cutting tool diagnostic device for predicting a condition is disclosed (see the summary "Solutions" column). That is, in Patent Document 1, when the determining means determines that a sign of breakage of any of the cutting tools has occurred, a stop signal is input to the control device of the target machine tool to stop machining ("Claim 4"). ”), It is possible to prevent the occurrence of defects such as breakage of the cutting tool (see paragraph number“ 0028 ”).

特許文献２には、刃具を交換しても警報設定値を正しく自動算出することが可能な方法が開示されている（要約「課題」の欄参照）。即ち、特許文献２は、工作機械の刃具ごとの有効電力波形データの特徴に基づき、予めそれぞれの刃具用に警報設定値算出方法を用意し、工作機械と接続された診断装置が工作機械から電力値などの有効電力波形データを収集し、収集の際にどの刃具を使用しているかを表す刃具情報を有効電力波形データに付加しておき、その刃具情報に基づいて警報設定値算出方法を選択することで、刃具を交換しても警報設定値を正しく算出する（要約「解決手段」の欄参照）。 Patent Document 2 discloses a method capable of correctly and automatically calculating an alarm set value even if the cutting tool is replaced (see the column of the summary "problem"). That is, Patent Document 2 prepares an alarm set value calculation method for each machine tool in advance based on the characteristics of the active power waveform data for each machine tool, and the diagnostic device connected to the machine tool supplies electric power from the machine tool. Collect active power waveform data such as values, add cutting tool information indicating which cutting tool is used at the time of collection to the active power waveform data, and select the alarm set value calculation method based on the cutting tool information. By doing so, the alarm set value is calculated correctly even if the cutting tool is replaced (see the summary "Solution" column).

従って、特許文献２は、それぞれの刃具用に警報設定値算出方法を用意しておき工作機械からの刃具情報に基づき、警報設定値算出方法を選択することで、刃具を交換しても警報設定値を正しく自動算出することが可能になる（段落番号「００２０」参照）。 Therefore, in Patent Document 2, an alarm setting value calculation method is prepared for each cutting tool, and an alarm setting value is set even if the cutting tool is replaced by selecting the alarm setting value calculation method based on the cutting tool information from the machine tool. The value can be calculated correctly and automatically (see paragraph number "0020").

特開２０１３−８６１９６号公報特開２００６−８２１５４号公報Japanese Patent Application Laid-Open No. 2013-86196 JP-A-2006-82154

ところで、特許文献１では、波形処理手段により各主軸モータの負荷電流の分散を算出して刃具の折損などに影響のない波形変化を取り除く作業が行われる（段落番号「００２７」参照）構成となっているが、その具体的な算出方法も明示されていない。また同様に、特許文献１では、判断手段がいずれかの刃具折損の予兆発生をどのように判断するかも明示されていない。 By the way, in Patent Document 1, the work of calculating the variance of the load current of each spindle motor by the waveform processing means and removing the waveform change that does not affect the breakage of the cutting tool is performed (see paragraph number “0027”). However, the specific calculation method is not specified. Similarly, Patent Document 1 does not specify how the determination means determines the occurrence of a sign of breakage of any of the cutting tools.

一方、特許文献２では、「閾値と全領域の最小値の差（図６のＤ）、全領域の最大値と最小値の差（図６のＣ）に対する比の値を予め決めておき、取得したデータの平均波形の最大値と最小値をもとに閾値を決定する」（段落番号「００５０」参照）ものです。即ち、この閾値は予め設定されているため、加工時温度などの環境変化に即応するものでなく、且つ刃具折損などの突発的な不具合の発生を未然に防ぐことが困難である。 On the other hand, in Patent Document 2, "the difference between the threshold value and the minimum value of the entire region (D in FIG. 6) and the value of the ratio to the difference between the maximum value and the minimum value in the entire region (C in FIG. 6) are determined in advance. The threshold value is determined based on the maximum and minimum values of the average waveform of the acquired data "(see paragraph number" 0050 "). That is, since this threshold value is set in advance, it does not respond immediately to environmental changes such as the processing temperature, and it is difficult to prevent the occurrence of sudden defects such as breakage of the cutting tool.

そこで、本発明は、例えば加工時温度などの環境変化に即応して加工の突発的な不具合となる加工時異常の検出精度または刃具寿命の予測精度が向上し得る加工異常検出装置およびその加工異常検出方法を、提供することを目的とする。 Therefore, the present invention provides a machining abnormality detection device capable of improving the detection accuracy of machining abnormalities or the prediction accuracy of cutting tool life, which causes sudden defects in machining in response to environmental changes such as machining temperature, and a machining abnormality thereof. It is an object of the present invention to provide a detection method.

本発明の加工異常検出装置は、加工機械に配置される刃具の異常を検出する加工異常検出装置であって、上記加工機械の駆動モータに供給される加工時の負荷を検出する負荷検出手段と、上記負荷検出手段が検出する上記加工時の負荷データを取込んで記録するデータ収集手段と、上記データ収集手段が収集する上記負荷データに基づき、直前の所定時間幅負荷における総和基礎Σ値およびその直後の所定時間幅負荷における総和新Σ値をそれぞれ演算する演算手段と、上記演算手段で順次演算される新たな基礎演算データとしての総和基礎Σ値を基準に上記総和新Σ値を比較値として上記演算手段で除算し、その除算値が所定範囲内か否かで上記刃具の状態が異常の範囲内か否かを判断する判断手段と、を備える。 The machining abnormality detecting device of the present invention is a machining abnormality detecting device for detecting an abnormality of a cutting tool arranged in a machining machine, and is a load detecting means for detecting a load during machining supplied to the drive motor of the machining machine. Based on the data collecting means that captures and records the load data at the time of processing detected by the load detecting means and the load data collected by the data collecting means, the total basic Σ value in the immediately preceding predetermined time width load and A comparison value of the total new Σ value based on the calculation means for calculating the total new Σ value in the predetermined time width load immediately after that and the total basic Σ value as new basic calculation data sequentially calculated by the above calculation means. The data is divided by the above calculation means, and the determination means for determining whether or not the state of the cutting tool is within the abnormal range is provided based on whether or not the division value is within a predetermined range .

ここで、「負荷を検出」の負荷とは、例えば電流または電力などを含む概念である。また、演算手段は、上記総和基礎Σ値および上記総和新Σ値をそれぞれ演算することにより、上記刃具の状態をも演算するものである。更に、上記総和基礎Σ値（分母）は、演算手段で順次演算される新たな基礎演算データ（「基礎対称比」と同義）として、刃具の状態が異常の範囲内か否かを判断手段が判断する。 Here, the load of "load detection" is a concept including, for example, current or electric power. Further, the calculation means also calculates the state of the cutting tool by calculating the total basic Σ value and the total new Σ value, respectively. Further, the total basic Σ value (denominator) is used as new basic calculation data (synonymous with "basic symmetry ratio") that is sequentially calculated by the calculation means, and the means for determining whether or not the state of the cutting tool is within the abnormal range. to decide.

また、本発明は上述した加工異常検出装置において、上記データ収集手段で収集された所定時間幅負荷における総和基礎Σ値を基準値として上記演算手段で演算すると共に、上記演算手段はその直前までの基準値に予め設定される割合の数値を乗算する規格値を演算し且つ上記規格値より上記基礎演算データである所望Ｎ個の平均値に基づきその直後の規格値を比較値として除算し、この除算した除算値が所定範囲内か否かで上記判断手段は上記刃具の異常を判断するようにしても良い。 Further, in the above-described processing abnormality detection device , the present invention calculates the total basic Σ value in the predetermined time width load collected by the above-mentioned data collecting means as a reference value by the above-mentioned calculation means, and the above-mentioned calculation means up to immediately before that. A standard value is calculated by multiplying the reference value by a numerical value of a preset ratio, and the standard value immediately after that is divided as a comparison value based on the average value of N desired basic calculation data from the standard value. The above-mentioned determination means may determine the abnormality of the cutting tool based on whether or not the divided division value is within a predetermined range.

更に、本発明は上述した加工異常検出装置において、上記データ収集手段で収集された所定時間幅負荷における総和基礎Σ値を基準値として上記演算手段で演算すると共に、上記演算手段はその直前までの基準値に予め設定される割合の数値を乗算する規格値を演算し且つ上記規格値より上記基礎演算データである所望Ｎ個の平均値に基づきその直後の規格値を比較値として除算し、この除算した除算値が所定範囲内か否かで上記判断手段は上記刃具の異常を判断するようにしても良い。 Further, in the above-described processing abnormality detection device , the present invention calculates the total basic Σ value in the predetermined time width load collected by the above-mentioned data collecting means as a reference value by the above-mentioned calculation means, and the above-mentioned calculation means up to immediately before that. A standard value is calculated by multiplying the reference value by a numerical value of a preset ratio, and the standard value immediately after that is divided as a comparison value based on the average value of N desired basic calculation data from the standard value. The above-mentioned determination means may determine the abnormality of the cutting tool based on whether or not the divided division value is within a predetermined range.

本発明の加工異常検出装置は、加工機械に配置される刃具の異常を検出する加工異常検出装置であって、上記加工機械の駆動モータに供給される加工時の負荷を検出する負荷検出手段と、上記負荷検出手段が検出する上記加工時の負荷データを取込んで記録するデータ収集手段と、上記データ収集手段で収集された所定時間幅負荷における総和基礎Σ値を基準値として演算すると共に上記基準値に予め設定される割合の数値を規格値として乗算し、且つ上記規格値より所望Ｎ個の初期平均値Ｎａ及びその後における次回所望Ｎ個の次回平均値Ｎｘｎをそれぞれ演算する演算手段と、上記演算手段は上記初期平均値Ｎａを基準に上記次回平均値Ｎｘｎを比較値として除算し、その除算値に基づき上記刃具の寿命予兆を設定する設定値について上記設定値以上か否かを判断する判断手段と、上記判断手段が上記設定値以上と判断する場合、上記寿命予兆であるとの予兆処理を行う処理手段と、を備える。 The machining abnormality detecting device of the present invention is a machining abnormality detecting device for detecting an abnormality of a cutting tool arranged in a machining machine, and is a load detecting means for detecting a load during machining supplied to the drive motor of the machining machine. The data collecting means that captures and records the load data at the time of processing detected by the load detecting means and the total basic Σ value in the predetermined time width load collected by the data collecting means are calculated as reference values, and the above is performed. A calculation means that multiplies the reference value by a numerical value of a preset ratio as a standard value, and calculates the desired N initial average value Na and the next desired N next average value Nxn from the standard value, respectively. The calculation means divides the next mean value Nxn as a comparison value based on the initial mean value Na, and determines whether or not the set value for setting the life sign of the cutting tool is equal to or more than the set value based on the divided value. It is provided with a determination means and a processing means for performing a predictive processing that the life is predictive when the determination means is determined to be equal to or higher than the set value.

また、本発明は上述した加工異常検出装置において、上記判断手段は上記除算値が指定回数に亘って上記寿命予兆であると判断する場合に、上記処理手段が予兆警告処理を行う。更に、本発明は上述した各加工異常検出装置において、上記総和基礎Σ値または上記初期平均値Ｎａは、上記刃具の交換時から上記演算手段がそれぞれ演算を開始する。更に本発明は、上述した各加工異常検出装置を、加工設備としてシステム一体的に組込む組込モードとするようにしても良い。 Further, in the above-described processing abnormality detection device of the present invention, when the determination means determines that the division value is the life sign over a specified number of times, the processing means performs the sign warning process. Further, according to the present invention, in each of the above-mentioned processing abnormality detection devices, the above-mentioned calculation means starts the calculation of the total basic Σ value or the above-mentioned initial mean value Na from the time when the cutting tool is replaced. Further, in the present invention, each of the above-mentioned processing abnormality detection devices may be set to an embedded mode in which the system is integrated as a processing equipment.

本発明の加工異常検出制御方法は、加工機械に配置される刃具の異常を検出する加工異常検出装置において、負荷検出手段が上記加工機械の駆動モータに供給される加工時の負荷を検出し、且つ上記負荷検出手段が検出する上記加工時の負荷データをデータ収集手段が取込んで記録すると共に、上記データ収集手段が収集する上記負荷データに基づき演算手段が直前の所定時間幅負荷における総和基礎Σ値およびその直後の所定時間幅負荷における総和新Σ値をそれぞれ演算し、且つ上記演算手段で順次演算される新たな基礎演算データとしての総和基礎Σ値を基準に上記総和新Σ値を比較値として上記演算手段で除算し、その除算値が所定範囲内か否かで上記刃具の状態が異常の範囲内か否かを判断手段が判断する。 In the machining abnormality detection control method of the present invention, in the machining abnormality detection device that detects the abnormality of the cutting tool arranged in the machining machine, the load detecting means detects the load during machining supplied to the drive motor of the machining machine. In addition, the data collecting means captures and records the load data at the time of processing detected by the load detecting means, and the calculation means is based on the load data collected by the data collecting means in the immediately preceding predetermined time width load. Calculate the total new Σ value for each of the Σ value and the predetermined time width load immediately after that, and compare the total new Σ value with reference to the total basic Σ value as new basic calculation data sequentially calculated by the above calculation means. The value is divided by the above-mentioned calculation means, and the determination means determines whether or not the state of the cutting tool is within the abnormal range depending on whether or not the divided value is within a predetermined range .

また、本発明の加工異常検出制御方法は、加工機械に配置される刃具の異常を検出する加工異常検出装置において、負荷検出手段が上記加工機械の駆動モータに供給される加工時の負荷を検出し、且つ上記負荷検出手段が検出する上記加工時の負荷データをデータ収集手段が取込んで記録し、上記データ収集手段で収集された所定時間幅負荷における総和基礎Σ値を基準値として演算手段が演算すると共に上記基準値に予め設定される割合の数値を規格値として乗算し、且つ上記規格値より所望Ｎ個の初期平均値Ｎａ及びその後における次回所望Ｎ個の次回平均値Ｎｘｎをそれぞれ演算し、上記演算手段は上記初期平均値Ｎａを基準に上記次回平均値Ｎｘｎを比較値として除算し、その除算値に基づき上記刃具の寿命予兆を設定する設定値について上記設定値以上か否かを判断手段が判断すると共に、上記判断手段が上記設定値以上と判断する場合に上記寿命予兆であるとの予兆処理を処理手段が行う。 Further, in the machining abnormality detection control method of the present invention, in the machining abnormality detecting device for detecting the abnormality of the cutting tool arranged in the machining machine, the load detecting means detects the load during machining supplied to the drive motor of the machining machine. In addition, the data collecting means captures and records the load data at the time of processing detected by the load detecting means, and the calculation means uses the total basic Σ value in the predetermined time width load collected by the data collecting means as a reference value. Calculates and multiplies the reference value by a preset ratio value as a standard value, and calculates the desired N initial mean values Na and the next desired N next mean values Nxn from the standard values. Then, the calculation means divides the next average value Nxn as a comparison value based on the initial average value Na, and determines whether or not the set value for setting the life sign of the cutting tool is equal to or more than the above set value based on the divided value. When the determination means determines, and when the determination means determines that the value is equal to or greater than the set value, the processing means performs the predictive processing of the life sign.

本発明では、総和基礎Σ値（分母）または所望Ｎ個の初期平均値Ｎａ（分母）を基準に比較値（分子）で演算するので、この演算される除算値に基づく加工時異常の検出精度が向上し得る。また、本発明によれば、初期平均値Ｎａ（分母）を基準に次回平均値Ｎｘｎを比較値（分子）として演算するので、この演算される除算値に基づく刃具寿命の予測精度が向上し得る。即ち、本発明では、順次演算される新たな基礎演算データ（分母）で刃具の状態が異常の範囲内か否かなどを判断するので、環境変化すなわち所謂加工変動基準に即応して加工（「刃具」自体の概念をも含む）の突発的な不具合たとえば刃具の欠損などの検出精度が向上し得る。 In the present invention, the comparison value (numerator) is calculated based on the total basic Σ value (denominator) or the desired N initial mean values Na (denominator). Therefore, the detection accuracy of machining anomalies based on the calculated division value. Can be improved. Further, according to the present invention, since the next mean value Nxn is calculated as the comparison value (numerator) based on the initial mean value Na (denominator), the prediction accuracy of the cutting tool life based on the calculated division value can be improved. .. That is, in the present invention, since the new state of the basic cutting tool in the operation data (denominator) which is sequentially calculating determines like whether the range abnormality, environmental changes i.e. processed and responsive to the so-called machining variation reference ( " Sudden defects (including the concept of "cutting tool" itself) can improve the detection accuracy of, for example, missing cutting tools.

本実施例における加工異常検出装置の平面図である。It is a top view of the processing abnormality detection device in this Example. 図１に示す加工異常検出装置に関する回路の構成図である。It is a block diagram of the circuit about the processing abnormality detection apparatus shown in FIG. 図２に示す回路のタイミングチャート図である。It is a timing chart diagram of the circuit shown in FIG. 図１に示す加工異常検出装置の検出処理に関するフローチャート図である。It is a flowchart about the detection process of the processing abnormality detection apparatus shown in FIG. 図４中のモード１に関するサブルーチン図である。It is a subroutine diagram about mode 1 in FIG. 図４に示すΣ値に関する説明図である。It is explanatory drawing about the Σ value shown in FIG. 図４に示すモード１の判定を説明するための判定イメージ図である。It is a judgment image diagram for demonstrating the judgment of mode 1 shown in FIG. 図４におけるモード２に関するサブルーチン図である。It is a subroutine diagram about mode 2 in FIG. 図４に示すモード２の判定を説明するための判定イメージ図である。It is a judgment image diagram for demonstrating the judgment of mode 2 shown in FIG. 図４におけるモード３に関するサブルーチン図である。It is a subroutine diagram about mode 3 in FIG. 図１０のモード３における刃具１０個毎の平均グラフ図である。It is an average graph figure for every 10 cutting tools in mode 3 of FIG. 図１０のモード３における刃具寿命曲線を示す測定グラフ図である。It is a measurement graph figure which shows the cutting tool life curve in mode 3 of FIG. 図１０のモード３におけるバラツキとＣＶ値との比較グラフ図である。It is a comparison graph figure of the variation and CV value in mode 3 of FIG.

以下、本発明を実施するための形態について、具体化した一実施例を説明する。 Hereinafter, a specific embodiment of the embodiment for carrying out the present invention will be described.

以下、図１または図２に基づいて、本発明の一実施形態である加工異常検出装置１６を含む加工設備システムＳ（図２参照）について説明する。図２に示すように、加工異常検出装置（以下、単に「検出装置」ともいう）１６は、切削などの加工機械１０に配置される刃具Ｗの異常を検出する装置である。また、加工設備システムＳは、加工機械１０を含む加工設備Ｈと、この加工設備Ｈに後付け配置される検出装置１６と、この検出装置１６に接続される種々の接続端末とで構成される。 Hereinafter, the processing equipment system S (see FIG. 2) including the processing abnormality detection device 16 according to the embodiment of the present invention will be described with reference to FIG. 1 or FIG. As shown in FIG. 2, the machining abnormality detection device (hereinafter, also simply referred to as “detection device”) 16 is a device that detects an abnormality of the cutting tool W arranged in the machining machine 10 for cutting or the like. Further, the processing equipment system S is composed of a processing equipment H including a processing machine 10, a detection device 16 retrofitted to the processing equipment H, and various connection terminals connected to the detection device 16.

なお、刃具Ｗは、図示しないが複数本たとえば面取用刃具およびエンドミルなどが切替可能に配置されており、ワーク（「被加工物」と同義）の加工に際して任意に選択可能となっている。また、検出装置１６は、加工設備Ｈの施工時に予め一体的に組込むように製造しても良い。
（加工異常検出装置１６の概略構成） Although not shown, a plurality of blades W, such as a chamfering blade and an end mill, are arranged so as to be switchable, and can be arbitrarily selected when processing a work (synonymous with "workpiece"). Further, the detection device 16 may be manufactured so as to be integrally incorporated in advance at the time of construction of the processing equipment H.
(Rough configuration of machining abnormality detection device 16)

図１に示すように、検出装置１６は、その装置本体１８に電源線などのコネクタ（図示省略）が着脱可能に接続される構成となっている。即ち、装置本体１８は、その表示面１８Ａに直流２４ボルト供給用の電源コネクタ２０と、図示しない外部機器との接続コネクタ２２と、データ保存のためのＵＳＢコネクタ２４と、ＬＡＮケーブル（図示省略）を接続するＬＡＮコネクタ２６と、デジタルなどのデータ入出力用のＩ／Ｏコネクタ２８と、Ｉ／Ｏ増設時の接続コネクタ３０と、を備える。 As shown in FIG. 1, the detection device 16 has a configuration in which a connector (not shown) such as a power line is detachably connected to the device main body 18. That is, the device main body 18 has a power connector 20 for supplying 24 volt DC, a connector 22 for connecting to an external device (not shown), a USB connector 24 for storing data, and a LAN cable (not shown) on the display surface 18A. A LAN connector 26 for connecting the above, an I / O connector 28 for input / output of digital data, and a connection connector 30 for adding an I / O are provided.

また、装置本体１８は、表示面１８Ａに例えば電源・コネクタ接続・異常警告出力・予兆警告出力など複数のランプが配列される点灯器３２と、図２に示すＵＳＢメモリ６２の着脱時に用いるスイッチ３４と、を備える。更に、装置本体１８には、表示面１８Ａの長手方向の両端に、一対の図示しない取付金具がそれぞれ配置されている。なお、装置本体１８は、略片手サイズの箱形状となっており、持運びが容易となっている。
（加工異常検出装置１６の制御系に関する構成） Further, the apparatus main body 18 has a lighting device 32 in which a plurality of lamps such as a power supply, a connector connection, an abnormality warning output, and a sign warning output are arranged on the display surface 18A, and a switch 34 used when attaching / detaching the USB memory 62 shown in FIG. And. Further, the apparatus main body 18 is provided with a pair of mounting brackets (not shown) at both ends of the display surface 18A in the longitudinal direction. The device main body 18 has a box shape of substantially one-handed size, and is easy to carry.
(Configuration related to the control system of the machining abnormality detection device 16)

図２に示すように、検出装置１６は、判断手段および演算手段ならびに処理手段などであるＣＰＵ（中央処理装置）４０と、このＣＰＵ４０などを起動させる電力を供給する電源回路３８と、を備える。また、検出装置１６には、ＬＥＤなどを点灯させるための点灯回路３６及び上述した点灯器３２とを備える。そして、点灯器３２は、ＣＰＵ４０に基づき、点灯または消灯する。なお、加工設備Ｈ内の電源１１と接続された電源回路３８における配線は、ＣＰＵ４０に接続されている部位以外の図示を省略する。これは、ＣＰＵ４０以外の各電子部品に複数の配線を接続する場合の錯綜を防止するためである。
（ＣＰＵ４０に関する構成） As shown in FIG. 2, the detection device 16 includes a CPU (central processing unit) 40 which is a determination means, a calculation means, a processing means, and the like, and a power supply circuit 38 for supplying electric power for activating the CPU 40 and the like. Further, the detection device 16 is provided with a lighting circuit 36 for lighting an LED or the like and a lighting device 32 described above. Then, the lighting device 32 is turned on or off based on the CPU 40. The wiring in the power supply circuit 38 connected to the power supply 11 in the processing facility H is not shown except for the portion connected to the CPU 40. This is to prevent complications when a plurality of wirings are connected to each electronic component other than the CPU 40.
(Configuration related to CPU 40)

図２に示すＣＰＵ４０は、その制御手段の一部を構成する制御部４２と、演算手段の一部を構成する演算部４４と、データ収集手段および記憶手段であるメモリ４６と、アナログをデジタルへと変換するＡ／Ｄ４８（負荷検出手段の一部を構成）と、例えばゲートウェイなどの通信ネットワークを介して通信する通信部５０を内蔵している。通信手段である通信部５０は、例えばＬＡＮ等で構成されている。なお、ここで「負荷」とは、電流の他に例えば電力などを含む概念である。 The CPU 40 shown in FIG. 2 digitally converts analog into a control unit 42 that constitutes a part of the control means, a calculation unit 44 that forms a part of the calculation means, a memory 46 that is a data collection means and a storage means, and an analog. It has a built-in A / D 48 (which constitutes a part of the load detecting means) that converts the data into, and a communication unit 50 that communicates via a communication network such as a gateway. The communication unit 50, which is a communication means, is composed of, for example, a LAN or the like. Here, the "load" is a concept that includes, for example, electric power in addition to the electric current.

ここで、メモリ４６には、後述するモード３の設定値などが予め記憶されている。また、メモリ４６内のテーブル４６Ａには、後述するモード１乃至モード３の演算式（アルゴリズム）などが記憶されている。更に、メモリ４６には、検出装置１６に各種の処理たとえば加工異常検出処理を制御するプログラムが記憶されている。そして、ＣＰＵ４０は、検出装置１６の全体的な動作を司り、例えば駆動／停止信号Ｓ１がＣＰＵ４０へ入力される場合にはその信号Ｓ１に基づき加工異常検出処理を行う。また、検出装置１６には、タイマ５４及び検出装置１６内の温度を計測するための温度センサ５２がＣＰＵ４０に接続されている。
（インタフェイスに関連する構成） Here, the memory 46 stores in advance the setting values of the mode 3 described later. Further, in the table 46A in the memory 46, arithmetic expressions (algorithms) of modes 1 to 3 described later are stored. Further, in the memory 46, a program for controlling various processes such as machining abnormality detection processes is stored in the detection device 16. Then, the CPU 40 controls the overall operation of the detection device 16, and for example, when the drive / stop signal S1 is input to the CPU 40, the processing abnormality detection process is performed based on the signal S1. Further, in the detection device 16, a timer 54 and a temperature sensor 52 for measuring the temperature inside the detection device 16 are connected to the CPU 40.
(Configuration related to interface)

図２に示すように、検出装置１６は、インタフェイスＩ／Ｆとしての運転信号（図３中ではシグナルの「Ｓ」として表す）入力部７０と、負荷検出手段の一部である電圧入力部７２と、異常信号出力部７４と、を備える。そして、この出力部７４などは、加工設備Ｈの図示しない端子に接続される。そして、加工設備Ｈは、加工異常検出装置１６などを一体的に組込む組込モードとすることも可能となっており、且つ各種機器に適応し得る構成となっている。 As shown in FIG. 2, the detection device 16 includes an operation signal (represented as “S” of the signal in FIG. 3) input unit 70 as an interface I / F and a voltage input unit which is a part of the load detection means. 72 and an abnormal signal output unit 74 are provided. Then, the output unit 74 and the like are connected to terminals (not shown) of the processing equipment H. Further, the processing equipment H can be set to an embedded mode in which the processing abnormality detecting device 16 and the like are integrally incorporated, and has a configuration that can be adapted to various devices.

また、加工設備Ｈは、図示しない各種スイッチと、ランプ等の表示器と、ブザー等の警報器などを備える。加工設備Ｈ中の加工機械１０には、駆動モータＭを駆動させる駆動回路などで構成される駆動部１２及びこの駆動部１２などを制御する制御部１４が配置されている。そして、この制御部１４は、検出装置１６の運転信号入力部７０と接続されており、駆動モータＭの駆動／停止信号Ｓ１と刃具交換信号Ｓ２と刃具チェンジ信号Ｓ３などが運転信号入力部７０へ出力されるされるように構成している。そのため、信号Ｓ１乃至Ｓ３は検出装置１６の運転信号入力部７０へ入力される。 Further, the processing equipment H includes various switches (not shown), indicators such as lamps, alarms such as buzzers, and the like. The processing machine 10 in the processing equipment H is provided with a drive unit 12 including a drive circuit for driving the drive motor M and a control unit 14 for controlling the drive unit 12. The control unit 14 is connected to the operation signal input unit 70 of the detection device 16, and the drive / stop signal S1 of the drive motor M, the blade replacement signal S2, the blade change signal S3, and the like are sent to the operation signal input unit 70. It is configured to be output. Therefore, the signals S1 to S3 are input to the operation signal input unit 70 of the detection device 16.

更に、駆動部１４はその駆動用電流ラインＭＬ上に電流センサ（以下、単に「センサ」ともいう）１３が接続され、ラインＭＬはセンサ１３を経て電圧入力部７２及び駆動モータＭにそれぞれ接続される。そのため、駆動モータＭに加工時の電流が供給される。即ち、ラインＭＬのセンサ１３及び電圧入力部７２は、ＣＰＵ４０のＡ／Ｄ４８と共に負荷検出手段を構成する。そして、センサ１３に電流が供給されると、センサ１３は例えば５Ａ＝０．５Ｖなど変換した後に、アナログ値として電圧入力部７２へと出力する。その後、そのアナログ値は、ＣＰＵ４０内のＡ／Ｄ４８でデジタル値へと変換される。 Further, the drive unit 14 is connected to a current sensor (hereinafter, also simply referred to as “sensor”) 13 on the drive current line ML, and the line ML is connected to the voltage input unit 72 and the drive motor M via the sensor 13, respectively. To. Therefore, a current during processing is supplied to the drive motor M. That is, the sensor 13 of the line ML and the voltage input unit 72 constitute a load detecting means together with the A / D 48 of the CPU 40. Then, when a current is supplied to the sensor 13, the sensor 13 converts, for example, 5A = 0.5V, and then outputs the analog value to the voltage input unit 72. After that, the analog value is converted into a digital value by A / D48 in the CPU 40.

ここで、上述した駆動／停止信号Ｓ１は加工機械１０の駆動モータＭ（例えば図示しないワークを挟持するチャックＣなど）が駆動または停止すると、自動的に出力する信号である。また、刃具交換信号Ｓ２は加工機械１０に配置される刃具Ｗが新たな刃具へ交換される時に制御部１４から出力される信号で、刃具チェンジ信号Ｓ３は上述したように複数種の刃具たとえばタップ刃・エンドミールなどを切替え可能な構成である場合これらの切替わる際の信号である。 Here, the drive / stop signal S1 described above is a signal that is automatically output when the drive motor M of the processing machine 10 (for example, a chuck C that sandwiches a work (not shown)) is driven or stopped. Further, the cutting tool change signal S2 is a signal output from the control unit 14 when the cutting tool W arranged in the processing machine 10 is replaced with a new cutting tool, and the cutting tool change signal S3 is a plurality of types of cutting tools such as taps as described above. When the blade, end meal, etc. can be switched, this is the signal when switching between them.

また図２に示すように、外部のゲートウェイ又はサーバー６０はＣＰＵ４０内の通信部５０に接続され、検出装置１６から外部通信端末へとデータ等が通信される。更に、検出装置１６は、外部のＵＳＢメモリ６２またはトランシーバ６４などと通信するための通信回路５６及び図１に示すＵＳＢコネクタ２４などで構成される接続部または図示しない送受信部などで構成される通信器５８を備える。
（本実施例の作用） Further, as shown in FIG. 2, the external gateway or server 60 is connected to the communication unit 50 in the CPU 40, and data or the like is communicated from the detection device 16 to the external communication terminal. Further, the detection device 16 is a communication composed of a communication circuit 56 for communicating with an external USB memory 62, a transceiver 64, etc., a connection unit including a USB connector 24 shown in FIG. 1, or a transmission / reception unit (not shown). A vessel 58 is provided.
(Action of this example)

図３に示すタイミングチャート及び図４などに示すフローチャートを主に用いて、図２に示す加工異常検出装置１６の動作およびＣＰＵ４０の加工異常検出処理（以下、単に「検出処理」ともいう）について説明する。ＣＰＵ４０の検出処理は、加工機械１０から駆動／停止信号Ｓ１が入力されると、メモリ４６に記憶されるプログラムが実行される。実行される処理ルーチンは図４などのフローチャートで表され、これらのプログラムは予めメモリ４６（図２参照）のプログラム領域に記憶されている。 The operation of the machining abnormality detection device 16 shown in FIG. 2 and the machining abnormality detection process of the CPU 40 (hereinafter, also simply referred to as “detection process”) will be described mainly by using the timing chart shown in FIG. 3 and the flowchart shown in FIG. To do. In the detection process of the CPU 40, when the drive / stop signal S1 is input from the processing machine 10, the program stored in the memory 46 is executed. The processing routine to be executed is represented by a flowchart such as FIG. 4, and these programs are stored in advance in the program area of the memory 46 (see FIG. 2).

先ず図２に示す駆動モータＭの制御部１４から駆動／停止信号Ｓ１が供給されると、図３に示す検出処理が開始してオンＨ状態になる（立上がる）と共に電圧値などのデータ収集すなわち測定を開始する（立上がる）。そののち再び駆動／停止信号Ｓ１が再入力されると、オフＬ状態になり停止する（立下がる）と共にデータ収集（測定）も停止する（立下がる）。 First, when the drive / stop signal S1 is supplied from the control unit 14 of the drive motor M shown in FIG. 2, the detection process shown in FIG. 3 is started to enter the on-H state (rise) and collect data such as a voltage value. That is, the measurement is started (stands up). After that, when the drive / stop signal S1 is re-input, it goes into an off-L state and stops (falls down), and at the same time, data collection (measurement) also stops (falls down).

この停止処理後すなわち立下がりと同期して、ＣＰＵ４０は加工異常か否かの判定処理を行う。ここで、検出処理として駆動／停止信号Ｓ１を用いたのは、切削加工の開始と測定開始のタイミング精度を向上させるためである。なお、本実施例において、読取スピードの設定を１０ｍＳと１００ｍＳと１０００ｍＳなどに選択可能としても良い。 After this stop process, that is, in synchronization with the fall, the CPU 40 performs a process of determining whether or not there is a machining abnormality. Here, the drive / stop signal S1 is used as the detection process in order to improve the timing accuracy of the start of the cutting process and the start of the measurement. In this embodiment, the reading speed may be set to 10 mS, 100 mS, 1000 mS, or the like.

そして、ＣＰＵ４０が正常の範囲内であると判定する場合、異常出力信号を出力することなく、何らの信号も出ないＬ状態を維持する。一方、ＣＰＵ４０が異常であると判定する場合、図３に示すよう判定処理と同期して異常出力信号Ｈが所定時間に亘って出力される。また、異常出力信号Ｈが停止するオフＬ状態と同時に、ＣＰＵ４０はリセット解除信号を所定時間たとえば５００ｍＳ以上に亘って出力させる。この所定時間５００ｍＳは、解除の確実性を考慮したもので、図２に示すタイマ５０をカウントして処理する。なお、５００ｍＳは、任意に例えば２００ｍＳなど変更し得る。 Then, when it is determined that the CPU 40 is within the normal range, the L state in which no signal is output is maintained without outputting an abnormal output signal. On the other hand, when the CPU 40 determines that the abnormality is present, the abnormality output signal H is output over a predetermined time in synchronization with the determination process as shown in FIG. Further, at the same time as the off-L state in which the abnormal output signal H is stopped, the CPU 40 outputs the reset release signal for a predetermined time, for example, 500 mS or more. The predetermined time of 500 mS is processed by counting the timer 50 shown in FIG. 2 in consideration of the certainty of release. Note that 500 mS can be arbitrarily changed, for example, 200 mS.

図３の処理をフローチャートで詳述すると、図４に示すステップ１００では、上述した駆動／停止信号Ｓ１（図２及び図３参照）が加工機械１０から運転信号入力部７０へ入力されたか否かを判断する。ステップ１００が肯定の場合すなわち駆動／停止信号Ｓ１が入力されハイＨ状態となる場合には、ステップ１０２でデータ収集（測定）を開始する（図３参照）。なお、ステップ１００が否定の場合は、駆動／停止信号Ｓ１が入力されるのを待つ。 To elaborate the process of FIG. 3 with a flowchart, in step 100 shown in FIG. 4, whether or not the above-mentioned drive / stop signal S1 (see FIGS. 2 and 3) is input from the processing machine 10 to the operation signal input unit 70. To judge. When step 100 is affirmative, that is, when the drive / stop signal S1 is input and the high H state is reached, data collection (measurement) is started in step 102 (see FIG. 3). If the step 100 is negative, it waits for the drive / stop signal S1 to be input.

ＣＰＵ４０は、図４に示すステップ１０４において、駆動／停止信号が再入力されたか否かを判断する。ステップ１０４が肯定の場合すなわち再入力された場合は、ステップ１０６でデータ収集（測定）を停止する（図３参照）。ここで、データ収集は、そのデータ例えば後述する加工時総和電流値Σなどをメモリ４６へ記録することも含まれる。なお、ステップ１０４が否定の場合は、駆動／停止信号が再入力されるのを待つ。
（モード１に関する処理） In step 104 shown in FIG. 4, the CPU 40 determines whether or not the drive / stop signal has been re-input. If step 104 is affirmative, that is, if it is re-entered, data collection (measurement) is stopped in step 106 (see FIG. 3). Here, the data collection also includes recording the data, for example, the total processing current value Σ, which will be described later, in the memory 46. If step 104 is negative, it waits for the drive / stop signal to be re-input.
(Processing related to mode 1)

その後ステップ１０８において、ＣＰＵ４０はモード１か否かを判断する。ここで、本実施例におけるモードは後述するようにモード１乃至モード３が選択可能となっており、その中でモード１及びモード２は刃具異常たとえば図２に示す刃具Ｗが欠損などで加工される被加工物（ワーク）の加工不具合の発生に迅速かつ確実に即応するための手法である。即ち、上述した加工不具合の発生は工場設備の環境たとえば温度・湿度・材料のバラツキなどで変化するため、判定の判断基準（以下、単に「加工変動基準」ともいう）も常時変動する。 After that, in step 108, the CPU 40 determines whether or not the mode is 1. Here, as the mode in this embodiment, modes 1 to 3 can be selected as described later, and among them, modes 1 and 2 are machined due to an abnormality in the cutting tool, for example, the cutting tool W shown in FIG. 2 is defective. This is a method for quickly and surely responding to the occurrence of processing defects in the workpiece (workpiece). That is, since the occurrence of the above-mentioned processing defects changes depending on the environment of the factory equipment such as temperature, humidity, and material variation, the judgment criteria for judgment (hereinafter, also simply referred to as “processing variation criteria”) also constantly change.

そして、その変動に即応するモード１及びモード２は、図２に示すＣＰＵ４０の演算部４４で刃具Ｗを例えば新品などに交換し、最初の加工１回目から順次演算される新たな基礎演算データを基礎対称比（分母）として刃具Ｗの状態が異常の範囲内か否かを判断する手法である。 Then, in modes 1 and 2 that immediately respond to the fluctuation, the cutting tool W is replaced with, for example, a new one by the calculation unit 44 of the CPU 40 shown in FIG. 2, and new basic calculation data that is sequentially calculated from the first machining is used. This is a method for determining whether or not the state of the cutting tool W is within the abnormal range as the basic symmetry ratio (denominator).

この中でもモード１は、メモリ４６で収集（「記録」と同義）された直前の所定時間幅負荷（電流）における基礎対称比としての総和基礎Σ値すなわち基準値を演算部４４で演算する手法であり、後述するモード２のいわゆる移動平均と比較して厳しく判定する。具体的にモード１は、上記総和基礎Σ値（分母）を基準に、その直後の所定時間幅電流における総和新Σ値（分子）を比較値として演算部４４で除算して、その除算値が所定範囲内か否かで図２に示すＣＰＵ４０は刃具Ｗの異常を判断する。なお、モード２の詳述及びモード３については、後述する。 Among these, mode 1 is a method in which the calculation unit 44 calculates the total basic Σ value, that is, the reference value as the basic symmetry ratio in the predetermined time width load (current) immediately before being collected (synonymous with “recording”) in the memory 46. Yes, it is determined more strictly than the so-called moving average of mode 2 described later. Specifically, in mode 1, the total basic Σ value (denominator) is used as a reference, and the total new Σ value (numerator) in the predetermined time width current immediately after that is divided by the calculation unit 44 as a comparison value, and the divided value is obtained. The CPU 40 shown in FIG. 2 determines that the cutting tool W is abnormal depending on whether or not it is within the predetermined range. The details of mode 2 and mode 3 will be described later.

ＣＰＵ４０は、ステップ１０８が肯定の場合、ステップ１１０でモード１（図５に示す「サブルーチン」参照）へ移行させる。引続き、このモード１について詳述する。図５に示すように、ステップ１４０では、刃具Ｗ（図２参照）の交換信号Ｓ２が入力されたか否かを判断する。ステップ１４０が肯定の場合すなわち刃具交換信号Ｓ２が入力されたのであれば、ステップ１４２で刃具交換信号Ｓ２からの１回目のデータＰ１（図７参照）の電流測定値Σ（「基準値」と同義）などを演算部４４（図２参照）で順次演算する。 If step 108 is affirmative, the CPU 40 shifts to mode 1 (see "subroutine" shown in FIG. 5) in step 110. Subsequently, this mode 1 will be described in detail. As shown in FIG. 5, in step 140, it is determined whether or not the replacement signal S2 of the cutting tool W (see FIG. 2) has been input. If step 140 is affirmative, that is, if the cutting tool replacement signal S2 is input, the current measurement value Σ (synonymous with “reference value”) of the first data P1 (see FIG. 7) from the cutting tool replacement signal S2 in step 142. ) Etc. are sequentially calculated by the calculation unit 44 (see FIG. 2).

ここで、電流測定値Σとは、刃具Ｗで加工される被加工物の加工時に生じる電流値の合計Σ（「加工時総和電流値Σ」と同義）である。即ち、図６に示す電流測定値Σの例では、上述した読取スピートを１００ｍＳ間隔で測定した値の総和（「合計」と同義）であり、図６中の線Ａ及び線Ｂの面積（図６では斜線で示す）差で良否の判定を行う。例えば、ＣＰＵ４０は、面積差が正常時の約１０％以下に低下する場合に加工異常と判断する。 Here, the measured current value Σ is the total Σ of the current values generated during machining of the workpiece to be machined by the cutting tool W (synonymous with “total current value Σ during machining”). That is, in the example of the current measurement value Σ shown in FIG. 6, it is the sum of the values measured at 100 mS intervals (synonymous with “total”), and the areas of lines A and B in FIG. 6 (FIG. 6). In 6, the quality is judged by the difference (indicated by the diagonal line). For example, the CPU 40 determines that a processing abnormality occurs when the area difference is reduced to about 10% or less of the normal state.

具体的に線Ａ（図６では破線で示す）は刃具折損発生前である正常時の例であり、そのΣ値は８２８７３である。線Ｂ（図６では実線で示す）は刃具折損発生後である欠損時の例であり、そのΣ値は７３７９１である。そして、発生前後のバラツキ比率は、−１０．９５％である。なお、測定間隔（「読取スピート」と同義）は、上述したよう例えば１０ｍＳなどに変更可能である。なお、上述した面積差のパーセント値は、任意に変更し得る。 Specifically, line A (shown by a broken line in FIG. 6) is an example of a normal state before the occurrence of breakage of the cutting tool, and its Σ value is 82873. Line B (shown by a solid line in FIG. 6) is an example of a defect after the cutting tool is broken, and its Σ value is 73791. The variation ratio before and after the occurrence is -10.95%. The measurement interval (synonymous with "reading speed") can be changed to, for example, 10 mS as described above. The percentage value of the area difference described above can be changed arbitrarily.

次に、ステップ１４４では、刃具Ｗの交換直前のΣ値（図７のＰｅｎｄ）をメモリ４６から読出しその基礎対称比であるＰｅｎｄを基準（分母）に、その直後のΣ値Ｐ１を比較値（分母）として除算する。即ち、モード１は各々判断する一つ前の電流測定値Σ（「総和基礎値Σ」と同義）のデータを基準に判定する方法であり、式としては例えば(Ｐ１／Ｐｅｎｄ)である。なお、モード１では、生データであるΣ値をそのまま利用するのは、数値対称が直前または直後のΣ値だけで判断する手法だからである。 Next, in step 144, the Σ value (Pend in FIG. 7) immediately before the replacement of the cutting tool W is read from the memory 46, the Pend which is the basic symmetry ratio thereof is used as a reference (denominator), and the Σ value P1 immediately after that is used as a comparison value (Pend). Divide as the denominator). That is, the mode 1 is a method of making a judgment based on the data of the current measured value Σ (synonymous with “total basic value Σ”) immediately before each judgment, and the formula is, for example, (P1 / Pend). In mode 1, the raw data Σ value is used as it is because the numerical symmetry is determined only by the immediately preceding or immediately preceding Σ value.

ＣＰＵ４０は、ステップ１４６において、上記除算値を図２に示すメモリ４６に順次記録させる。そして、このステップ１４６以降の処理は、再びステップ１４２に戻り、メモリ４６に記憶されるテーブル４６Ａ中の例えば図７に示す(Ｐ２／Ｐ１)・(Ｐ３／Ｐ２)・(Ｐ４／Ｐ３)・(Ｐ５／Ｐ４)など分母がＰｅｎｄとなるまで除算値を記録する。 In step 146, the CPU 40 sequentially records the division value in the memory 46 shown in FIG. Then, the processing after this step 146 returns to step 142 again, and in the table 46A stored in the memory 46, for example, (P2 / P1), (P3 / P2), (P4 / P3), ( Record the division value until the denominator becomes Pend, such as P5 / P4).

引続き図４に示すフローチャートに戻り、ステップ１１６で加工異常か否かを判断する。ステップ１１６が否定の場合すなわち正常である場合は、ステップ１１８で図２に示すサーバ６０などへ電流測定値Σまたは除算値などのデータを出力など処理する。即ち、本実施例によれば、例えば工場などの加工施設Ｈにユーザが不在でも、稼動状況を把握し得る。 Continuing to return to the flowchart shown in FIG. 4, it is determined in step 116 whether or not there is a machining abnormality. If step 116 is negative, that is, normal, data such as the current measurement value Σ or the division value is output to the server 60 or the like shown in FIG. 2 in step 118. That is, according to this embodiment, the operating status can be grasped even when the user is absent in the processing facility H such as a factory.

一方、ステップ１１６が肯定の場合すなわち加工異常である場合は、ステップ１２０において異常警告たとえば図２に示す異常信号出力部７４などで加工異常である旨のデータ出力または点灯器３２などを点灯させる。その後は、ステップ１１８でトランシーバ６４またはＳＢメモリ６２などへ上述したようなデータを出力など処理する。本実施例によれば、ユーザは上述した稼動状況（データ）をいつでも参照し得るので、検出装置１６を常時稼動していれば稼働率測定装置などとしても兼用し得る。 On the other hand, if step 116 is affirmative, that is, if the machining is abnormal, in step 120, the abnormality warning, for example, the abnormality signal output unit 74 shown in FIG. 2 lights the data output or the lighter 32 indicating that the machining is abnormal. After that, in step 118, the above-mentioned data is output to the transceiver 64, the SB memory 62, or the like. According to this embodiment, since the user can refer to the above-mentioned operating status (data) at any time, if the detection device 16 is always in operation, it can also be used as an operating rate measuring device or the like.

即ち、本実施例において、順次演算される新たな基礎演算データ（総和基礎Σ値）を基礎対称比として刃具の状態が異常の範囲内か否かを判断するので、環境変化すなわち所謂加工変動基準に即応して加工（「刃具」自体の概念をも含む）の突発的な不具合たとえば刃具の欠損などの検出精度が向上する。従って、本実施例では、基礎対称比である総和基礎Σ値（分母）を基準に比較値としての総和新Σ値（分子）で除算するので、この除算値に基づく加工時異常の検出精度が後述するモード２に比べて厳格な判断となる。
（モード２に関する処理） That is, in this embodiment, since it is determined whether or not the state of the cutting tool is within the abnormal range by using the new basic calculation data (total basic Σ value) that is sequentially calculated as the basic symmetry ratio, the environmental change, that is, the so-called machining fluctuation standard. In response to this, the detection accuracy of sudden defects in machining (including the concept of "cutting tool" itself), such as a defect in the cutting tool, is improved. Therefore, in this embodiment, the total basic Σ value (denominator), which is the basic symmetry ratio, is divided by the total new Σ value (numerator) as a comparison value, so that the detection accuracy of machining anomalies based on this division value is high. The judgment is stricter than that of mode 2, which will be described later.
(Processing related to mode 2)

ステップ１０８が否定の場合すなわちモード１でない場合には、ステップ１１２でモード２か否かを判断する。ここで、モード２は、上述した加工変動基準に即応し、刃具Ｗを例えば新品など交換した後に最初の加工１回目からＮ回目分の平均値（「規格値」と同義）を用いて判断する手法である。そのため、モード２（いわゆる移動平均法）及びモード１では、基準値（規格値も同様）がリアルタイムに変動して計測するので、加工異常時の判断に適している。 If step 108 is negative, that is, if it is not mode 1, it is determined in step 112 whether or not it is mode 2. Here, the mode 2 is determined by using the average value (synonymous with "standard value") for the first to N times of the first processing after the cutting tool W is replaced with a new one, for example, in accordance with the above-mentioned processing fluctuation standard. It is a method. Therefore, in mode 2 (so-called moving average method) and mode 1, the reference value (similar to the standard value) fluctuates in real time for measurement, which is suitable for determining when a machining abnormality occurs.

具体的にモード２は、図２に示すメモリ４６で収集された所定時間幅の電流値における総和基礎Σ値（基準値）に、ＣＰＵ４０の演算部４４が基準値に例えば３−５％の値を乗算して、この乗算値を規格値とする。ここで、規格値として基準値に３−５％を乗算するのは、モード２が基礎対称比（分母）として平均値を用いるため、加工機械１０における真の切削などの加工能力をある程度算出して考慮するためである。 Specifically, in mode 2, the calculation unit 44 of the CPU 40 sets a value of, for example, 3-5% to the total basic Σ value (reference value) in the current value of the predetermined time width collected by the memory 46 shown in FIG. To make this multiplication value the standard value. Here, the reason why the reference value is multiplied by 3-5% as the standard value is that the mode 2 uses the average value as the basic symmetry ratio (denominator), so the machining ability such as true cutting in the machining machine 10 is calculated to some extent. This is to consider.

なお、３−５％の値は、実験データなどの経験則に基づくもので、その数値は例えば３％以下あるいは５％以上の任意の幅をもって変更でき且つ０．１％きざみにも変更し得る。また、演算部４４は、その直前までの規格値より所定Ｎ個の平均値に基づき、その直後の規格値で除算する。ＣＰＵ４０の制御部４２は、この除算した除算値が所定範囲内か否かで刃具Ｗの異常を判断する。 The value of 3-5% is based on an empirical rule such as experimental data, and the value can be changed with an arbitrary range of, for example, 3% or less or 5% or more, and can be changed in 0.1% increments. .. Further, the calculation unit 44 divides the standard value immediately before that by the standard value immediately after that based on the average value of N predetermined values. The control unit 42 of the CPU 40 determines the abnormality of the cutting tool W based on whether or not the divided value obtained by the division is within a predetermined range.

そして、ＣＰＵ４０は、ステップ１１２が肯定の場合、ステップ１１４でモード２（図８に示す「サブルーチン」参照）へ移行させる。引続き、このモード２について詳述する。図８に示すように、ステップ１５０では、刃具Ｗ（図２参照）の交換信号Ｓ２が入力されたか否かを判断する。ステップ１５０が肯定の場合すなわち刃具交換信号Ｓ２が入力されたのであれば、ＣＰＵ４０はステップ１５２で基準値を演算部４４で順次演算する。 Then, if step 112 is affirmative, the CPU 40 shifts to mode 2 (see “subroutine” shown in FIG. 8) in step 114. Subsequently, this mode 2 will be described in detail. As shown in FIG. 8, in step 150, it is determined whether or not the replacement signal S2 of the cutting tool W (see FIG. 2) has been input. If the step 150 is affirmative, that is, if the cutting tool replacement signal S2 is input, the CPU 40 sequentially calculates the reference value in the calculation unit 44 in the step 152.

ここで基準値は、モード１で説明した電流測定値から総和基礎Σ値を演算して算出する。そして、図２に示す演算部４４はステップ１５４で算出された基準値より上述した規格値を順次演算し、ステップ１５６でＮ個たとえば５個の規格値を平均値として演算する。なお、Ｎ個は６個・８個など任意に設定変更し得る。 Here, the reference value is calculated by calculating the total basic Σ value from the current measurement value described in mode 1. Then, the calculation unit 44 shown in FIG. 2 sequentially calculates the above-mentioned standard values from the reference values calculated in step 154, and calculates N, for example, five standard values as an average value in step 156. The setting of N pieces can be changed arbitrarily, such as 6 pieces or 8 pieces.

ステップ１５６で演算部４４は上記平均値（分母）を基準にその直後の規格値を比較値（分子）として除算する。本実施例において、規格値Ｎ個の平均がリアルタイムに変動する平均値データ（「移動平均値データ」と同義）を基に演算を繰返すので、除算値も刻々と変動する。 In step 156, the calculation unit 44 divides the standard value immediately after the average value (denominator) as a comparison value (numerator) based on the average value (denominator). In this embodiment, since the calculation is repeated based on the average value data (synonymous with "moving average value data") in which the average of N standard values fluctuates in real time, the division value also fluctuates every moment.

具体的には、メモリ４６に記憶されるテーブル４６Ａ中の式(Ｐ２／Ｐ１)・(Ｐ３／{(Ｐ１＋Ｐ２)／２})・(Ｐ４／{(Ｐ１＋Ｐ２＋Ｐ３)／３}）・(Ｐ５／{(Ｐ１＋Ｐ２＋Ｐ３＋Ｐ４)／４})まで５回の平均値（図９参照）を演算部４４が演算する。ここで、分母を{(Ｐ１＋Ｐ２)／２}・{(Ｐ１＋Ｐ２＋Ｐ３)／３}などとするのは、判定もれを防止するためである。 Specifically, the equations (P2 / P1), (P3 / {(P1 + P2) / 2}), (P4 / {(P1 + P2 + P3) / 3}), (P5 / {" in the table 46A stored in the memory 46 The calculation unit 44 calculates the average value (see FIG. 9) of 5 times up to (P1 + P2 + P3 + P4) / 4}). Here, the denominator is set to {(P1 + P2) / 2}, {(P1 + P2 + P3) / 3}, etc. in order to prevent omission of judgment.

また、図９に示す「Ｐ６」以降の演算は、（Ｐ６／{(Ｐ１＋Ｐ２＋Ｐ３＋Ｐ４＋Ｐ５)／５})・（Ｐ７／{(Ｐ２＋Ｐ３＋Ｐ４＋Ｐ５＋Ｐ６)／５})・（Ｐ８／{(Ｐ３＋Ｐ４＋Ｐ５＋Ｐ６＋Ｐ７)／５})・・・と順次繰返す。そして、ＣＰＵ４０はステップ１５８で上記除算値をメモリ４６に記録し、再びステップ１５２に戻り順次繰返す。その後は、図４に示すフローチャートに戻り、ステップ１１６以降の処理を行う。なお、異常か否かの判断は、モード１と同様に例えば１０％などのバラツキ比率で行う。 In addition, the operations after "P6" shown in FIG. 9 are (P6 / {(P1 + P2 + P3 + P4 + P5) / 5}), (P7 / {(P2 + P3 + P4 + P5 + P6) / 5}), (P8 / {(P3 + P4 + P5 + P6 + P7) / 5}).・・ And so on. Then, the CPU 40 records the division value in the memory 46 in step 158, returns to step 152 again, and repeats sequentially. After that, the process returns to the flowchart shown in FIG. 4 and the processes after step 116 are performed. It should be noted that the determination as to whether or not it is abnormal is performed at a variation ratio such as 10% as in mode 1.

即ち、本実施例において、順次演算される新たな基礎演算データ（所望Ｎ個の初期平均値Ｎａ）を基礎対称比として刃具の状態が異常の範囲内か否かを判断するので、いわゆる加工変動基準に即応して加工の突発的な不具合たとえば刃具の欠損などの検出精度が向上する。従って、本実施例では、基礎対称比である所望Ｎ個の初期平均値Ｎａ（分母）を基準にその直後の規格値（分子）で除算するので、この除算値に基づく加工時異常の検出精度が前述するモード１に比べて実地に即するような判断となる。
（モード３に関する処理） That is, in this embodiment, it is determined whether or not the state of the cutting tool is within the abnormal range by using the new basic calculation data (desired N initial average values Na) that are sequentially calculated as the basic symmetry ratio. The detection accuracy of sudden defects in machining, such as defects in cutting tools, is improved according to the standard. Therefore, in this embodiment, the desired N initial average value Na (denominator), which is the basic symmetry ratio, is divided by the standard value (numerator) immediately after that, and therefore, the detection accuracy of machining abnormality based on this division value. However, the judgment is more realistic than that of mode 1 described above.
(Processing related to mode 3)

更に、ステップ１１２が否定の場合すなわちモード２でない場合にはステップ１３０でモード３の処理を行う。ここで、モード３は、モード１及びモード２と異なり、蓄積データを用いて図２に示す刃具Ｗの寿命予兆を判断する手法である。この刃具寿命は、刃具Ｗの素性（「特性」と同義）で長期使用による経時劣化の傾向が検出し難いので、上述した蓄積データを用いる。 Further, if step 112 is negative, that is, if it is not mode 2, the process of mode 3 is performed in step 130. Here, unlike the mode 1 and the mode 2, the mode 3 is a method of determining the life sign of the cutting tool W shown in FIG. 2 by using the accumulated data. Since it is difficult to detect the tendency of deterioration over time due to long-term use due to the features of the cutting tool W (synonymous with "characteristics"), the accumulated data described above is used for this cutting tool life.

即ち、モード３はいわゆる相対平均による判別分析法（「ＣＶ法」ともいう）を応用した手法であり、初期平均値Ｎａ（分母）は刃具交換から初期のＮ個分たとえば１０個分を平均した値とし、その後の次回平均値Ｎｘｎ（分子）はその後の加工時におけるＮ個分たとえば１１個乃至２０個分を平均した値として演算する。具体的にモード３では、図１０のサブルーチンに示すステップ１６０で刃具Ｗの交換信号Ｓ２が入力されたか否かを判断する。 That is, mode 3 is a method that applies a so-called relative averaging discriminant analysis method (also referred to as "CV method"), and the initial average value Na (denominator) is the average of the initial N pieces, for example, 10 pieces from the blade replacement. The value is used, and the next average value Nxn (molecule) after that is calculated as the average value of N pieces, for example, 11 to 20 pieces in the subsequent processing. Specifically, in mode 3, it is determined in step 160 shown in the subroutine of FIG. 10 whether or not the replacement signal S2 of the cutting tool W is input.

ステップ１６０が肯定の場合すなわち刃具交換信号Ｓ２が入力されたのであれば、ＣＰＵ４０はステップ１６２で基準値を演算部４４で順次演算する。この基準値は、モード１で説明したように、電流測定値から総和基礎Σ値を演算して算出する。そして、演算部４４はステップ１６４で算出された基準値よりモード２で説明した規格値を順次演算し、ステップ１６６で刃具交換信号Ｓ２の入力後における最初（「１回目」と同義）の規格値よりＮ個たとえば１０個の初期平均値Ｎａを演算する。 If step 160 is affirmative, that is, if the cutting tool replacement signal S2 is input, the CPU 40 sequentially calculates the reference value in step 162 by the calculation unit 44. As described in mode 1, this reference value is calculated by calculating the total basic Σ value from the measured current value. Then, the calculation unit 44 sequentially calculates the standard value described in mode 2 from the reference value calculated in step 164, and in step 166, the first standard value (synonymous with “first time”) after the input of the cutting tool replacement signal S2. From N, for example, 10 initial average values Na are calculated.

ＣＰＵ４０はステップ１６８で初期平均値Ｎａをメモリ４６に記録し、ステップ１７０では演算部４４で規格値より次回Ｎ個たとえば刃具交換から１１回目乃至２０回目の１０個分における次回平均値（「移動平均値」と同義）Ｎｘｎを演算する。そして、ＣＰＵ４０において、演算部４４はステップ１７２で初期平均値Ｎａ（分母）を基準に次回平均値Ｎｘｎを比較値（分子）として除算し、ステップ１７４でこの除算値をメモリ４６に記録させる。 The CPU 40 records the initial average value Na in the memory 46 in step 168, and in step 170, in the calculation unit 44, the next average value (“moving average”) for the next N pieces from the standard value, for example, the 11th to 20th times from the blade replacement. Synonymous with "value") Calculates Nxn. Then, in the CPU 40, the calculation unit 44 divides the next average value Nxn as a comparison value (numerator) based on the initial average value Na (denominator) in step 172, and records the divided value in the memory 46 in step 174.

具体的に初期平均値Ｎａは、式{(Ｐ１＋Ｐ２＋Ｐ３・・・Ｐ８＋Ｐ９＋Ｐ１０)／１０})まで１回乃至１０回分の平均値を演算部４４が演算する。また、次回平均値Ｎｘｎは、式{(Ｐ１１＋Ｐ１２＋Ｐ１３・・・Ｐ１８＋Ｐ１９＋Ｐ２０)／１０})まで１０回分の平均値（「比較値」と同義）Ｎｘ2を演算部４４が演算する。この比較値は、例えば式{(Ｐ２１・・・Ｐ３０)／１０})Ｎｘ3または式{(Ｐ３１・・・Ｐ４０)／１０})Ｎｘ4 ・・式{(Ｐ２５１・・・Ｐ２６０)／１０})Ｎｘ26・・・と順次繰返す。 Specifically, for the initial average value Na, the calculation unit 44 calculates the average value for 1 to 10 times up to the formula {(P1 + P2 + P3 ... P8 + P9 + P10) / 10}). Further, for the next average value Nxn, the calculation unit 44 calculates the average value (synonymous with "comparison value") Nx2 for 10 times up to the formula {(P11 + P12 + P13 ... P18 + P19 + P20) / 10}). This comparison value is, for example, formula {(P21 ... P30) / 10}) Nx3 or formula {(P31 ... P40) / 10}) Nx4 ... formula {(P251 ... P260) / 10}) Nx26 ... And so on.

即ち、上述したステップ１７４以降の処理は、再びステップ１７０に戻り、上述した演算などを順次繰返す。具体的に演算部４４は、メモリ４６に記憶されるテーブル４６Ａ中の式(Ｎｘｎ／Ｎａ）に基づき、(Ｎｘ2／Ｎａ)・・・と順次繰返して演算する。引続き図４に示すフローチャートに戻り、ＣＰＵ４０はステップ１３２でメモリ４６に記録された除算値（図１０に示す「ステップ１７４」参照）が、刃具Ｗの寿命予兆を予め任意に設定している設定値以上か否かを判断する。 That is, the processing after step 174 described above returns to step 170 again, and the above-mentioned calculation and the like are sequentially repeated. Specifically, the calculation unit 44 sequentially repeats (Nx2 / Na) ... Based on the formula (Nxn / Na) in the table 46A stored in the memory 46. Continuing to return to the flowchart shown in FIG. 4, the CPU 40 sets the division value (see “step 174” shown in FIG. 10) recorded in the memory 46 in step 132 to arbitrarily set the life sign of the cutting tool W in advance. Judge whether it is above or not.

この設定値は初期平均値Ｎａの３％として、ＣＰＵ４０は（除算値（％）≦設定値または除算値（％）≧設定値）で判断する。この除算値（％）≦設定値の場合は設定値以下と判断し、除算値（％）≧設定値の場合は設定値以上を越えると判断する。即ち、図１１乃至図１３に示すように、モード３は除算値として表れる測定値の急激な変化が始まるポイントを、寿命予兆警告点とする手法である。ここで、図１１乃至図１３の各図は、複数の実験データのうちの一例であり、刃具Ｗの上述した種類別の例および同一種類の刃具Ｗであってもそれぞれの特性曲線はそれぞれ変動している。 This set value is 3% of the initial average value Na, and the CPU 40 determines by (division value (%) ≤ set value or division value (%) ≥ set value). When the division value (%) ≤ the set value, it is determined that the value is equal to or less than the set value, and when the division value (%) ≥ the set value, it is determined that the value exceeds the set value. That is, as shown in FIGS. 11 to 13, the mode 3 is a method in which the point at which the sudden change of the measured value appearing as the division value starts is set as the life predictive warning point. Here, each of FIGS. 11 to 13 is an example of a plurality of experimental data, and the characteristic curves of the above-mentioned examples of the cutting tool W and the same type of cutting tool W vary. doing.

ステップ１３２が肯定の場合すなわち刃具Ｗが寿命予兆点（上述した「寿命予兆警告点」と同義）である設定値以上の場合は、ステップ１３４で指定回数たとえば２回目か否かを判断する。ステップ１３４が肯定の場合すなわち指定回数に亘って寿命予兆であると判断である場合、ＣＰＵ４０はステップ１３６で予兆警告出力たとえば異常信号出力部７４を介して刃具Ｗが上記警告点を越えた旨の警告信号などを出力させる。即ち、本実施例によれば、初期平均値Ｎａ（分母）を基準に次回平均値Ｎｘｎを比較値（分子）として演算するので、この演算される除算値に基づく刃具寿命の予測精度が向上し得る。 If step 132 is affirmative, that is, if the cutting tool W is equal to or greater than the set value that is the life sign warning point (synonymous with the above-mentioned “life sign warning point”), it is determined in step 134 whether or not the specified number of times is, for example, the second time. If step 134 is affirmative, that is, if it is determined that the life is a sign over a specified number of times, the CPU 40 indicates that the cutting tool W has exceeded the warning point in step 136 via a sign warning output, for example, an abnormal signal output unit 74. Output a warning signal, etc. That is, according to this embodiment, the next mean value Nxn is calculated as the comparison value (numerator) based on the initial mean value Na (denominator), so that the accuracy of predicting the tool life based on the calculated division value is improved. obtain.

ステップ１３６が終了した後、ＣＰＵ４０はステップ１１８で図２に示すサーバ６０などへ例えば除算値などのデータを出力など処理させる。一方、ステップ１３４又はステップ１３２が否定の場合すなわち指定回数でない又は除算値が設定値以下の場合は、ステップ１３２に戻り除算値が設定値以上か否かの判断を再び繰返す。なお、本実施例において、上述した設定値は任意に変更でき、例えば５％などに変更設定し得る。 After the completion of step 136, the CPU 40 causes the server 60 or the like shown in FIG. 2 to process data such as a division value in step 118. On the other hand, if step 134 or step 132 is negative, that is, if the number of times is not specified or the division value is equal to or less than the set value, the process returns to step 132 and the determination of whether or not the division value is equal to or greater than the set value is repeated again. In this embodiment, the above-mentioned set value can be arbitrarily changed, and can be changed to, for example, 5%.

また、本実施例によれば、ステップ１３４の指定回数処理は予兆警告の確実性を担保するもので、その回数は例えば３回など任意に設定変更し得る。更に、上述したプログラムの処理の流れ（図４など参照）は一例であり、本発明の主旨を逸脱しない範囲内において適宜変更可能である。例えば、本発明は、モード１乃至モード３を任意に選択し得、それぞれ単独あるいは複数のモードをそれぞれ任意に組合せることができる。 Further, according to the present embodiment, the designated number of times processing in step 134 ensures the certainty of the sign warning, and the number of times can be arbitrarily changed, for example, three times. Further, the processing flow of the program described above (see FIG. 4 and the like) is an example, and can be appropriately changed within a range that does not deviate from the gist of the present invention. For example, in the present invention, modes 1 to 3 can be arbitrarily selected, and individual modes or a plurality of modes can be arbitrarily combined.

１０…加工機械、１３…電流センサ（負荷検出手段またはデータ収集手段）、１６…加工異常検出装置、４０…ＣＰＵ、４２…制御部（判断手段または処理手段）、４４…演算部（演算手段）、４６…メモリ（記憶手段またはデータ収集手段）、４８…Ａ／Ｄ（負荷検出手段またはデータ収集手段）、５０…通信部（通信手段）、５６…通信回路（通信手段）、５８…通信器（通信手段）、７２…電圧入力部（負荷検出手段またはデータ収集手段）、Ｗ…刃具、Ｍ…駆動モータ、Ｓ…加工設備システム、Ｈ…加工設備 10 ... Machining machine, 13 ... Current sensor (load detecting means or data collecting means), 16 ... Machining abnormality detecting device, 40 ... CPU, 42 ... Control unit (judgment means or processing means), 44 ... Arithmetic unit (calculation means) , 46 ... Memory (storage means or data collecting means), 48 ... A / D (load detecting means or data collecting means), 50 ... Communication unit (communication means), 56 ... Communication circuit (communication means), 58 ... Communication device (Communication means), 72 ... Voltage input unit (load detecting means or data collecting means), W ... Cutting tool, M ... Drive motor, S ... Machining equipment system, H ... Machining equipment

Claims

A machining abnormality detection device that detects abnormalities in cutting tools placed in a machining machine.
A load detecting means for detecting the load during machining supplied to the drive motor of the machining machine, and
A data collecting means that captures and records the load data during processing detected by the load detecting means, and
Based on the load data collected by the data collecting means, a calculation means for calculating the total basic Σ value in the immediately preceding predetermined time width load and the total new Σ value in the predetermined time width load immediately after that, respectively .
Based on the total basic Σ value as new basic calculation data sequentially calculated by the above calculation means, the above total new Σ value is divided by the above calculation means as a comparison value, and the above division value is determined by whether or not the division value is within a predetermined range. A means of determining whether the condition of the cutting tool is within the abnormal range, and
A machining abnormality detection device equipped with.

In the processing abnormality detection device according to claim 1,
The calculation means calculates the total basic Σ value in the predetermined time width load collected by the data collection means as a reference value, and the calculation means multiplies the reference value up to that point by a numerical value of a preset ratio. The standard value is calculated, and the standard value immediately after that is divided as a comparison value based on the average value of the desired N pieces of the basic calculation data from the standard value, and the above-mentioned is determined by whether or not the divided division value is within a predetermined range. The determination means is a machining abnormality detection device that determines the abnormality of the cutting tool.

A machining abnormality detection device that detects abnormalities in cutting tools placed in a machining machine.
A load detecting means for detecting the load during machining supplied to the drive motor of the machining machine, and
A data collecting means that captures and records the load data during processing detected by the load detecting means, and
Calculate using the total basic Σ value in the predetermined time width load collected by the data collecting means as the reference value, multiply the reference value by a preset ratio value as the standard value, and N desired values from the standard value. And the calculation means for calculating the initial average value Na of the above and the next desired N next average values Nxn after that, respectively.
The calculation means divides the next average value Nxn as a comparison value based on the initial average value Na, and determines whether or not the set value for setting the life sign of the cutting tool is equal to or greater than the above set value based on the divided value. Judgment means and
When the above-mentioned determination means determines that the value is equal to or greater than the above-mentioned set value, the processing means for performing the predictive processing of the above-mentioned life sign and the processing means.
A machining abnormality detection device equipped with.

In the processing abnormality detection device according to claim 3 ,
The determination means is a processing abnormality detection device in which the processing means performs predictive warning processing when it is determined that the division value is the predictive life sign over a specified number of times.

In the processing abnormality detection device according to claim 2 or 3 .
The total basic Σ value or the initial average value Na is a machining abnormality detection device in which the calculation means starts calculation from the time when the cutting tool is replaced.

A machining abnormality detection device having a built-in mode in which the machining abnormality detection device according to any one of claims 1 to 5 is integrally incorporated as a machining equipment system.

In a machining abnormality detection device that detects abnormalities in cutting tools placed in a machining machine
The load detecting means detects the load during machining supplied to the drive motor of the machining machine, and the data collecting means captures and records the load data during machining detected by the load detecting means.
Based on the load data collected by the data collecting means, the calculation means calculates the total basic Σ value in the immediately preceding predetermined time width load and the total new Σ value in the predetermined time width load immediately after that, and the calculation means sequentially calculates the total new Σ value. Based on the total basic Σ value as new basic calculation data to be calculated, the total new Σ value is used as a comparison value and divided by the above calculation means, and the state of the cutting tool is abnormal depending on whether or not the divided value is within a predetermined range. A machining abnormality detection control method in which the determination means determines whether or not the data is within the range of.

In a machining abnormality detection device that detects abnormalities in cutting tools placed in a machining machine
The load detecting means detects the load during machining supplied to the drive motor of the machining machine, and the data collecting means captures and records the load data during machining detected by the load detecting means.
The calculation means calculates using the total basic Σ value in the predetermined time width load collected by the data collecting means as a reference value, and multiplies the reference value by a numerical value of a preset ratio as a standard value, and from the standard value. The initial average value Na of the desired N pieces and the next average value Nxn of the desired N pieces after that are calculated, respectively.
The calculation means divides the next average value Nxn as a comparison value based on the initial average value Na, and determines whether or not the set value for setting the life sign of the cutting tool is equal to or more than the above set value based on the divided value. A processing abnormality detection control method in which the processing means performs a predictive processing indicating that the life is a sign when the determination means determines that the value is equal to or greater than the set value.