## 2 Data Collection and Preprocessing
### Data Collection
Due to the lack of a sensor providing information about the reference (ambient) temperature, it was decided to convert the temperature measurement results into their derivative after time. This made it possible to make the measurements independent of changes in ambient temperature between measurement series while retaining information about rapid temperature changes occurring during faults. In addition, taking into account the sensitivity of the acceleration measurement system to factors from the environment, acceleration measurements were made with the drive turned off before the actual tests. This made it possible to determine the level of vibration caused by the surroundings, that is, nearby traffic routes and other equipment operating in the building. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Type of Fault** & **Severity** & **Description** & **Percentage** & **Chart** \\
**(Designation)** & **-** & **3,465,880** & **88.20\%** & **Chart** \\ \hline \multirow{4}{*}{ \begin{tabular}{c} No failures \\ (nu) \\ \end{tabular}  } & \multirow{4}{*}{-} & \multirow{4}{*}{3,465,880} & \multirow{4}{*}{88.20\%} \\  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \hline \multirow{4}{*}{ \begin{tabular}{c} Drive block \\ (bn) \\ \end{tabular}  } & \multirow{4}{*}{\ \begin{tabular}{c} The drive blockage causes \\ the system to halt; however, \\ if the obstructing object is \\ removed, the drive can \\ resume operation after the \\ elevator user presses a \\ button. \\ \end{tabular}  } & \multirow{4}{*}{22,880} & \multirow{4}{*}{0.58\%} \\  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \hline \multirow{4}{*}{ \begin{tabular}{c} Drive belt \\ stretched by \\ 1 tooth \\ (rp1z) \\ \end{tabular}  } \begin{table}
\begin{tabular}{c c c c c} \hline
**Type of Fault** & **Severity** & **Description** & **Percentage** & **Chart** \\
**(Designation)** & **Severity** & **Description** & **of Records** & **Chart** \\ \hline Drive belt & High & & & \\ breakage & Breakage of the drive belt & 51,116 & 1.30\% & 3 \\ (up) & completely disables the drive & movement. & & 2 \\  & & & & \\  & & & & \\ \hline \end{tabular} \begin{tabular}{c c} \hline Medium & & & \\  & Bearing damage causes an & & \\  & additional load torque on the & & \\  & motor. In extreme cases, it & & \\  & may lead to complete & & \\  & bearing seizure and, & & \\  & consequently, drive failure. & & \\  & However, early detection of & & \\  & damage can prevent such & & \\  & severe consequences. & & & \\ \hline \end{tabular} \
\begin{tabular}{c c} \hline Medium & & & \\  & A malfunction of the & & \\  & automatic closing system & & \\  & does not cause significant & & \\  & effects on the driver itself. & & \\  & However, if another door & & \\  & failure occurs & & \\  & simultaneously, the elevator & & \\  & doors will not close & & \\  & automatically, which may & & \\  & pose a safety risk to users. & & \\ \hline \end{tabular}
\begin{tabular}{c c} \hline Shift door & & & \\  & Connection system is a & \\  & serious fault that completely & & \\  & disallows the door to be & & \\  & unlocked and opened. & & \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._Fault identification models using machine learning methods require the collection of a sufficiently large dataset that contains representative examples of all considered types of device faults. Due to the nature of the signals associated with the occurrence of some faults, it is necessary to obtain measurements at a frequency sufficient to capture all the necessary information.