A method for detecting vehicle system faults, the method comprising: receiving, with a processor, a plurality of sensor signals (X1(t), X2(t)...Xn(t)) from one or more sensors; the method characterized by: thresholding, with the processor, the plurality of sensor signals for each respective sensor substantially in real time, wherein said thresholding includes determining a size of a threshold used to simplify a time series of said sensor signals X(t) and determining a maximum amount that the time series of sensor signals X(t) can change between consecutive samples; generating, with the processor, abnormal derivative frequency values (ADF1, ADF2...ADFn) for each of the plurality of thresholded sensor signals (Y1(t), Y2(t)...Yn(t)) in real time, wherein each abnormal derivative frequency value is computed as a count (Nabnormal) of abnormally large magnitudes of a one-step time-derivative of the thresholded sensor signal Y(t) as a fraction of a total count (Ntotal) of non-zero derivatives or during a predetermined total time (Ttotal); and determining an operational status of at least each of the one or more sensors based on the abnormal derivative frequency values. receiving, with a processor, a plurality of sensor signals (X1(t), X2(t)...Xn(t)) from one or more sensors; the method characterized by: thresholding, with the processor, the plurality of sensor signals for each respective sensor substantially in real time, wherein said thresholding includes determining a size of a threshold used to simplify a time series of said sensor signals X(t) and determining a maximum amount that the time series of sensor signals X(t) can change between consecutive samples; generating, with the processor, abnormal derivative frequency values (ADF1, ADF2...ADFn) for each of the plurality of thresholded sensor signals (Y1(t), Y2(t)...Yn(t)) in real time, wherein each abnormal derivative frequency value is computed as a count (Nabnormal) of abnormally large magnitudes of a one-step time-derivative of the thresholded sensor signal Y(t) as a fraction of a total count (Ntotal) of non-zero derivatives or during a predetermined total time (Ttotal); and determining an operational status of at least each of the one or more sensors based on the abnormal derivative frequency values. thresholding, with the processor, the plurality of sensor signals for each respective sensor substantially in real time, wherein said thresholding includes determining a size of a threshold used to simplify a time series of said sensor signals X(t) and determining a maximum amount that the time series of sensor signals X(t) can change between consecutive samples; generating, with the processor, abnormal derivative frequency values (ADF1, ADF2...ADFn) for each of the plurality of thresholded sensor signals (Y1(t), Y2(t)...Yn(t)) in real time, wherein each abnormal derivative frequency value is computed as a count (Nabnormal) of abnormally large magnitudes of a one-step time-derivative of the thresholded sensor signal Y(t) as a fraction of a total count (Ntotal) of non-zero derivatives or during a predetermined total time (Ttotal); and determining an operational status of at least each of the one or more sensors based on the abnormal derivative frequency values.