Modeling system for collected data of sensors on numerical control machine tool and method therefor

A modeling system for collected data of sensors on a numerical control machine tool, comprising a controller, a flash memory and a plurality of sensors for collected data on a running state of the numerical control machine tool as multi-channel data;

• wherein, an output end of a sensor is connected to an input end of a multi-channel sensor interface circuit, and an output end of the multi-channel sensor interface circuit is connected to the controller;
• wherein the controller is also connected to the flash memory, and the flash memory comprises a construction module, a setting module, a superposition module, an export module, and a limit module;
• wherein the construction module is configured to form received p-channel data into tensor-data-one of a p-channel, the tensor-data-one of the p-channel comprises n sample data collected by the plurality of sensors, and each sample data comprises data collected by the plurality of sensors at a certain sampling time, and data format of an i-th sample data Yi(t) is:
• Yi(t)=[Yil(t), . . . , Yip(t)], t is a sampling time of the i-th sample data;
• Yij(t) is expressed by a formula (1):
• Yij(t)=Xij(t)+εij(t) (1)
• Xij(t) is a signal function of the collected data of a jth channel, εij(t) is a noise function of the collected data of the j-th channel, i is a positive integer less than or equal to N, j is a positive integer less than or equal to p, Yij(t) represents the collected data of the j-th channel at a sampling time t;
• wherein the setting module is configured to set data format of tensor-data-two Xi(t) of the p channel as:
• Xi(t)=[Xil(t), . . . , Xip(t)], and the data format of the tensor-data-two Xi(t) of the p channel is divided into L sample subspaces Sl, l=1, 2, . . . , L, L is a positive integer, there is cross-correlation between signal functions corresponding to signals in a same sample subspace, the signal functions corresponding to signals in different sample subspaces have no correlation;
• wherein the superposition module is configured to set each sample subspace Sl as a linear superposition of Φl of dl basis functions, as shown in a formula (2), wherein Φl=[Φl1(t), . . . , Φldl(t)]:
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• for all signal functions Xij(t), I=1, . . . ,N, a sample subspace to which Xij(t) belongs remains unchanged, while basis coefficients aij corresponding to Xij(t) are different, aij=[aij1, aij2 . . . , aijdl], and aijk is a k-th component of the basis coefficients aij, where k is a positive integer less than or equal to dl;
• wherein Xl represents the signals of the respective sample subspaces, wherein Xl={Xj(t)|Xj(t)∈Sl, j=1, . . . ,p}, q and dl are both positive integers, and αg is a set real number, R is the set of real numbers;
• wherein the export module is configured to obtain a formula (3) for each signal Xij(t), Xij(t) ∈Xl, according to a self-expression property of data that each data point in the sample subspace can be jointly represented by other data points in a data set:
• Xij(t)=ΣXir(t)∈XlbjrXir(t) (3)
• that is, Xij(t) is a signal function in Xl, which can be expressed as a linear combination of other pl-1 signals in this sample subspace, r is a positive integer, and bjr is a rth component of a sparse coefficient;
• the limit module is configured to limit solution set by using an Lq norm to minimize an objective function for a solution of the sparse coefficient bj;
• wherein the modeling system comprises a computer-one, a method runs on the computer-one, and comprises following steps:
• the computer-one building an information link between the computer-one and a computer-two;
• the computer-one sending a number of reduced information frames with the sparse coefficient to the computer-two, based on conditions of the information link between the computer-one and the computer-two;
• wherein the computer-one sends different reduced information frames of the sparse coefficient under the conditions of different information links;
• after the computer-one sending a number of reduced information frames with the sparse coefficient to the computer-two, based on the conditions of the information link between the computer-one and the computer-two, the computer-one monitoring whether the information link between the computer-one and computer two is interrupted;
• when so, the computer-one registers reduced information frames of the sparse coefficient which are not sent or sent unsuccessfully, and the reduced information frames of the sparse coefficient which are not sent or sent unsuccessfully are registered as not sent;
• when the computer-one and the computer-two restore the information link, the computer-one sends a number of reduced information frames of the sparse coefficient that registered as not sent to the computer-two.